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Wang YP, Karmakar R, Mukundan A, Tsao YM, Sung TC, Lu CL, Wang HC. Spectrum aided vision enhancer enhances mucosal visualization by hyperspectral imaging in capsule endoscopy. Sci Rep 2024; 14:22243. [PMID: 39333620 PMCID: PMC11436966 DOI: 10.1038/s41598-024-73387-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2024] [Accepted: 09/17/2024] [Indexed: 09/29/2024] Open
Abstract
Narrow-band imaging (NBI) is more efficient in detecting early gastrointestinal cancer than white light imaging (WLI). NBI technology is available only in conventional endoscopy, but unavailable in magnetic-assisted capsule endoscopy (MACE) systems due to MACE's small size and obstacles in image processing issues. MACE is an easy, safe, and convenient tool for both patients and physicians to avoid the disadvantages of conventional endoscopy. Enabling NBI technology in MACE is mandatory. We developed a novel method to improve mucosal visualization using hyperspectral imaging (HSI) known as Spectrum Aided Visual Enhancer (SAVE, Transfer N, Hitspectra Intelligent Technology Co., Kaohsiung, Taiwan). The technique was developed by converting the WLI image captured by MACE to enhance SAVE images. The structural similarity index metric (SSIM) between the WLI MACE images and the enhanced SAVE images was 91%, while the entropy difference between the WLI MACE images and the enhanced SAVE images was only 0.47%. SAVE algorithm can identify the mucosal break on the esophagogastric junction in patients with gastroesophageal reflux disorder. We successfully developed a novel image-enhancing technique, SAVE, in the MACE system, showing close similarity to the NBI from the conventional endoscopy system. The future application of this novel technology in the MACE system can be promising.
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Affiliation(s)
- Yen-Po Wang
- Endoscopy Center for Diagnosis and Treatment, Taipei Veterans General Hospital, No.201, Sec. 2, Shipai Rd., Beitou District, Taipei City, 11217, Taiwan
- Institute of Brain Sciences, National Yang Ming Chiao Tung University, 155, Li-Nong St., Sec.2, Peitou, Taipei City, 11217, Taiwan
| | - Riya Karmakar
- Department of Mechanical Engineering, National Chung Cheng University, 168, University Rd., Min Hsiung, Chia Yi, 62102, Taiwan
| | - Arvind Mukundan
- Department of Mechanical Engineering, National Chung Cheng University, 168, University Rd., Min Hsiung, Chia Yi, 62102, Taiwan
| | - Yu-Ming Tsao
- Department of Mechanical Engineering, National Chung Cheng University, 168, University Rd., Min Hsiung, Chia Yi, 62102, Taiwan
| | - Te-Chin Sung
- Insight Medical Solutions Inc., No. 1, Lixing 6th Rd., East Dist., Hsinchu City, 300096, Taiwan
| | - Ching-Liang Lu
- Endoscopy Center for Diagnosis and Treatment, Taipei Veterans General Hospital, No.201, Sec. 2, Shipai Rd., Beitou District, Taipei City, 11217, Taiwan.
- Institute of Brain Sciences, National Yang Ming Chiao Tung University, 155, Li-Nong St., Sec.2, Peitou, Taipei City, 11217, Taiwan.
| | - Hsiang-Chen Wang
- Department of Mechanical Engineering, National Chung Cheng University, 168, University Rd., Min Hsiung, Chia Yi, 62102, Taiwan.
- Department of Medical Research, Dalin Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, No. 2, Minsheng Road, Dalin, Chiayi, 62247, Taiwan.
- Hitspectra Intelligent Technology Co., Ltd., 8F.11-1, No. 25, Chenggong 2nd Rd., Kaohsiung, 80661, Taiwan.
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Chang CL, Karmakar R, Mukundan A, Lu SH, Choomjinda U, Chen MM, Chen YL, Wang HC. Mechanical Integrity of All-on-Four Dental Implant Systems: Finite Element Simulation of Material Properties of Zirconia, Titanium, and PEEK. Open Dent J 2024; 18. [DOI: 10.2174/0118742106325708240614044708] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2024] [Revised: 06/07/2024] [Accepted: 06/07/2024] [Indexed: 08/15/2024] Open
Abstract
Background
Dental implants are critical for restoring functionality and aesthetics in patients with missing teeth. The all-on-four treatment concept utilizes four dental implants to support a full-arch prosthesis. Material choice for these implants plays a crucial role in the long-term success of the treatment, affecting everything from biomechanical stability to osseointegration and patient comfort.
Aim
The purpose of this study is to analyze the biomechanical performance of three different materials used in all-on-four dental implant designs through finite element analysis (FEA). The aim is to determine which material optimally balances stress and deformation under various loading conditions.
Objective
The main objective of this research is to evaluate the effects of stress, strain, and deformation on all-on-four dental implants made from titanium, zirconia, and polyether ether ketone (PEEK). The study seeks to identify which material demonstrates the best mechanical properties under simulated functional loads.
Methods
A 3D model simulating the dental implants integrated with cancellous and cortical bone was developed. Finite element analysis was conducted to assess the biomechanical performance of the implants made from titanium, zirconia, and PEEK. A perpendicular load of 100 N was applied to the tips of the implants, followed by an oblique load of 100 N at a 30-degree angle, to simulate different chewing forces.
Results
The deformation analysis indicated that implants made of zirconia exhibited significantly lower maximum and average deformation compared to those made from titanium and PEEK. Although PEEK implants showed lower maximum and average stress, they did not perform well in stress dissipation compared to zirconia. Similar patterns of stress and deformation were observed under both perpendicular and oblique loading conditions.
Conclusion
Zirconia implants outperformed titanium and PEEK in terms of deformation and stress distribution under simulated loading conditions. This suggests that zirconia could be a superior material for all-on-four dental implants, offering better mechanical stability and potentially enhancing the longevity and success of dental restorations. Further clinical trials are recommended to validate these findings and assess the long-term outcomes of zirconia-based implants.
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Lai CL, Karmakar R, Mukundan A, Chen WC, Wu IC, Fedorov VE, Feng SW, Choomjinda U, Huang SF, Wang HC. Lung cancer cells detection by a photoelectrochemical MoS 2 biosensing chip. BIOMEDICAL OPTICS EXPRESS 2024; 15:753-771. [PMID: 38404333 PMCID: PMC10890875 DOI: 10.1364/boe.511900] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Revised: 12/22/2023] [Accepted: 12/22/2023] [Indexed: 02/27/2024]
Abstract
This research aims to explore the potential application of this approach in the production of biosensor chips. The biosensor chip is utilized for the identification and examination of early-stage lung cancer cells. The findings of the optical microscope were corroborated by the field emission scanning electron microscopy, which provided further evidence that the growth of MoS2 is uniform and that there is minimal disruption in the electrode, hence minimizing the likelihood of an open circuit creation. Furthermore, the bilayer structure of the produced MoS2 has been validated through the utilization of Raman spectroscopy. A research investigation was undertaken to measure the photoelectric current generated by three various types of clinical samples containing lung cancer cells, specifically the CL1, NCI-H460, and NCI-H520 cell lines. The findings from the empirical analysis indicate that the coefficient of determination (R-Square) for the linear regression model was approximately 98%. Furthermore, the integration of a double-layer MoS2 film resulted in a significant improvement of 38% in the photocurrent, as observed in the device's performance.
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Affiliation(s)
- Chun-Liang Lai
- Division of Pulmonology and Critical Care, Department of Internal Medicine, Dalin Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, No. 2, Minsheng Road, Dalin, Chiayi 62247, Taiwan
- School of Medicine, Tzu Chi University, 701 Zhongyang Rd., Sec. 3, Hualien 97004, Taiwan
| | - Riya Karmakar
- Department of Mechanical Engineering and Center for Innovative Research on Aging Society (CIRAS), National Chung Cheng University, 168, University Road, Min Hsiung, Chiayi City 62102, Taiwan
| | - Arvind Mukundan
- Department of Mechanical Engineering and Center for Innovative Research on Aging Society (CIRAS), National Chung Cheng University, 168, University Road, Min Hsiung, Chiayi City 62102, Taiwan
| | - Wei-Chung Chen
- Ph.D. Program in Environmental and Occupational Medicine, Kaohsiung Medical University, Kaohsiung 807, Taiwan
| | - I-Chen Wu
- Department of Medicine and Graduate Institute of Clinical Medicine, College of Medicine, Kaohsiung Medical University, No. 100, Tzyou 1st Rd., Sanmin Dist., Kaohsiung City 80756, Taiwan
| | - Vladimir E Fedorov
- Nikolaev Institute of Inorganic Chemistry, Siberian Branch of Russian Academy of Sciences, Novosibirsk 630090, Russia
- Department of Natural Sciences, Novosibirsk State University, 1, Pirogova str., Novosibirsk 630090, Russia
| | - Shih-Wei Feng
- Department of Applied Physics, National University of Kaohsiung, 700 Kaohsiung University Rd., Nanzih District, Kaohsiung 81148, Taiwan
| | - Ubol Choomjinda
- School of Nursing, Shinawatra University, 99 Moo 10, Bangtoey, Samkhok, Pathum Thani 12160, Thailand
| | - Shu-Fang Huang
- Division of Chest Medicine, Kaohsiung Armed Forces General Hospital, 2, Zhongzheng 1st. Rd., Kaohsiung City 80284, Taiwan
| | - Hsiang-Chen Wang
- Department of Mechanical Engineering and Center for Innovative Research on Aging Society (CIRAS), National Chung Cheng University, 168, University Road, Min Hsiung, Chiayi City 62102, Taiwan
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Fang YJ, Huang CW, Karmakar R, Mukundan A, Tsao YM, Yang KY, Wang HC. Assessment of Narrow-Band Imaging Algorithm for Video Capsule Endoscopy Based on Decorrelated Color Space for Esophageal Cancer: Part II, Detection and Classification of Esophageal Cancer. Cancers (Basel) 2024; 16:572. [PMID: 38339322 PMCID: PMC10854620 DOI: 10.3390/cancers16030572] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2024] [Revised: 01/26/2024] [Accepted: 01/26/2024] [Indexed: 02/12/2024] Open
Abstract
Esophageal carcinoma (EC) is a prominent contributor to cancer-related mortality since it lacks discernible features in its first phases. Multiple studies have shown that narrow-band imaging (NBI) has superior accuracy, sensitivity, and specificity in detecting EC compared to white light imaging (WLI). Thus, this study innovatively employs a color space linked to décor to transform WLIs into NBIs, offering a novel approach to enhance the detection capabilities of EC in its early stages. In this study a total of 3415 WLI along with the corresponding 3415 simulated NBI images were used for analysis combined with the YOLOv5 algorithm to train the WLI images and the NBI images individually showcasing the adaptability of advanced object detection techniques in the context of medical image analysis. The evaluation of the model's performance was based on the produced confusion matrix and five key metrics: precision, recall, specificity, accuracy, and F1-score of the trained model. The model underwent training to accurately identify three specific manifestations of EC, namely dysplasia, squamous cell carcinoma (SCC), and polyps demonstrates a nuanced and targeted analysis, addressing diverse aspects of EC pathology for a more comprehensive understanding. The NBI model effectively enhanced both its recall and accuracy rates in detecting dysplasia cancer, a pre-cancerous stage that might improve the overall five-year survival rate. Conversely, the SCC category decreased its accuracy and recall rate, although the NBI and WLI models performed similarly in recognizing the polyp. The NBI model demonstrated an accuracy of 0.60, 0.81, and 0.66 in the dysplasia, SCC, and polyp categories, respectively. Additionally, it attained a recall rate of 0.40, 0.73, and 0.76 in the same categories. The WLI model demonstrated an accuracy of 0.56, 0.99, and 0.65 in the dysplasia, SCC, and polyp categories, respectively. Additionally, it obtained a recall rate of 0.39, 0.86, and 0.78 in the same categories, respectively. The limited number of training photos is the reason for the suboptimal performance of the NBI model which can be improved by increasing the dataset.
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Affiliation(s)
- Yu-Jen Fang
- Department of Internal Medicine, National Taiwan University Hospital, Yun-Lin Branch, No. 579, Sec. 2, Yunlin Rd., Dou-Liu 64041, Taiwan;
- Department of Internal Medicine, National Taiwan University College of Medicine, No. 1, Jen Ai Rd., Sec. 1, Taipei 10051, Taiwan
| | - Chien-Wei Huang
- Department of Gastroenterology, Kaohsiung Armed Forces General Hospital, 2, Zhongzheng 1st Rd., Lingya District, Kaohsiung 80284, Taiwan;
- Department of Nursing, Tajen University, 20, Weixin Rd., Yanpu Township, Pingtung County 90741, Taiwan
| | - Riya Karmakar
- Department of Mechanical Engineering, National Chung Cheng University, 168, University Rd., Min Hsiung, Chia Yi 62102, Taiwan; (R.K.); (A.M.); (Y.-M.T.)
| | - Arvind Mukundan
- Department of Mechanical Engineering, National Chung Cheng University, 168, University Rd., Min Hsiung, Chia Yi 62102, Taiwan; (R.K.); (A.M.); (Y.-M.T.)
| | - Yu-Ming Tsao
- Department of Mechanical Engineering, National Chung Cheng University, 168, University Rd., Min Hsiung, Chia Yi 62102, Taiwan; (R.K.); (A.M.); (Y.-M.T.)
| | - Kai-Yao Yang
- Department of Gastroenterology, Kaohsiung Armed Forces General Hospital, 2, Zhongzheng 1st Rd., Lingya District, Kaohsiung 80284, Taiwan;
| | - Hsiang-Chen Wang
- Department of Mechanical Engineering, National Chung Cheng University, 168, University Rd., Min Hsiung, Chia Yi 62102, Taiwan; (R.K.); (A.M.); (Y.-M.T.)
- Department of Medical Research, Dalin Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, No. 2, Minsheng Road, Dalin, Chia Yi 62247, Taiwan
- Hitspectra Intelligent Technology Co., Ltd., 4F, No. 2, Fuxing 4th Rd., Qianzhen District, Kaohsiung 80661, Taiwan
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Ramezani G, Stiharu I, van de Ven TGM, Nerguizian V. Advancement in Biosensor Technologies of 2D MaterialIntegrated with Cellulose-Physical Properties. MICROMACHINES 2023; 15:82. [PMID: 38258201 PMCID: PMC10819598 DOI: 10.3390/mi15010082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/09/2023] [Revised: 12/27/2023] [Accepted: 12/28/2023] [Indexed: 01/24/2024]
Abstract
This review paper provides an in-depth analysis of recent advancements in integrating two-dimensional (2D) materials with cellulose to enhance biosensing technology. The incorporation of 2D materials such as graphene and transition metal dichalcogenides, along with nanocellulose, improves the sensitivity, stability, and flexibility of biosensors. Practical applications of these advanced biosensors are explored in fields like medical diagnostics and environmental monitoring. This innovative approach is driving research opportunities and expanding the possibilities for diverse applications in this rapidly evolving field.
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Affiliation(s)
- Ghazaleh Ramezani
- Department of Mechanical, Industrial, and Aerospace Engineering, Concordia University, Montreal, QC H3G 1M8, Canada;
| | - Ion Stiharu
- Department of Mechanical, Industrial, and Aerospace Engineering, Concordia University, Montreal, QC H3G 1M8, Canada;
| | - Theo G. M. van de Ven
- Department of Chemistry, McGill University, 801 Sherbrooke St. West, Montreal, QC H3A 0B8, Canada;
| | - Vahe Nerguizian
- Department of Electrical Engineering, École de Technologie Supérieure, 1100 Notre Dame West, Montreal, QC H3C 1K3, Canada;
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Huang HY, Hsiao YP, Karmakar R, Mukundan A, Chaudhary P, Hsieh SC, Wang HC. A Review of Recent Advances in Computer-Aided Detection Methods Using Hyperspectral Imaging Engineering to Detect Skin Cancer. Cancers (Basel) 2023; 15:5634. [PMID: 38067338 PMCID: PMC10705122 DOI: 10.3390/cancers15235634] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Revised: 11/20/2023] [Accepted: 11/24/2023] [Indexed: 08/15/2024] Open
Abstract
Skin cancer, a malignant neoplasm originating from skin cell types including keratinocytes, melanocytes, and sweat glands, comprises three primary forms: basal cell carcinoma (BCC), squamous cell carcinoma (SCC), and malignant melanoma (MM). BCC and SCC, while constituting the most prevalent categories of skin cancer, are generally considered less aggressive compared to MM. Notably, MM possesses a greater capacity for invasiveness, enabling infiltration into adjacent tissues and dissemination via both the circulatory and lymphatic systems. Risk factors associated with skin cancer encompass ultraviolet (UV) radiation exposure, fair skin complexion, a history of sunburn incidents, genetic predisposition, immunosuppressive conditions, and exposure to environmental carcinogens. Early detection of skin cancer is of paramount importance to optimize treatment outcomes and preclude the progression of disease, either locally or to distant sites. In pursuit of this objective, numerous computer-aided diagnosis (CAD) systems have been developed. Hyperspectral imaging (HSI), distinguished by its capacity to capture information spanning the electromagnetic spectrum, surpasses conventional RGB imaging, which relies solely on three color channels. Consequently, this study offers a comprehensive exploration of recent CAD investigations pertaining to skin cancer detection and diagnosis utilizing HSI, emphasizing diagnostic performance parameters such as sensitivity and specificity.
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Affiliation(s)
- Hung-Yi Huang
- Department of Dermatology, Ditmanson Medical Foundation Chiayi Christian Hospital, Chia Yi City 60002, Taiwan;
| | - Yu-Ping Hsiao
- Department of Dermatology, Chung Shan Medical University Hospital, No.110, Sec. 1, Jianguo N. Rd., South District, Taichung City 40201, Taiwan;
- Institute of Medicine, School of Medicine, Chung Shan Medical University, No.110, Sec. 1, Jianguo N. Rd., South District, Taichung City 40201, Taiwan
| | - Riya Karmakar
- Department of Mechanical Engineering, National Chung Cheng University, 168, University Rd., Min Hsiung, Chia Yi City 62102, Taiwan; (R.K.); (A.M.)
| | - Arvind Mukundan
- Department of Mechanical Engineering, National Chung Cheng University, 168, University Rd., Min Hsiung, Chia Yi City 62102, Taiwan; (R.K.); (A.M.)
| | - Pramod Chaudhary
- Department of Aeronautical Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Avadi, Chennai 600 062, India;
| | - Shang-Chin Hsieh
- Department of Plastic Surgery, Kaohsiung Armed Forces General Hospital, 2, Zhongzheng 1st. Rd., Lingya District, Kaohsiung 80284, Taiwan
| | - Hsiang-Chen Wang
- Department of Mechanical Engineering, National Chung Cheng University, 168, University Rd., Min Hsiung, Chia Yi City 62102, Taiwan; (R.K.); (A.M.)
- Department of Medical Research, Dalin Tzu Chi General Hospital, No. 2, Min-Sheng Rd., Dalin Town, Chia Yi City 62247, Taiwan
- Technology Development, Hitspectra Intelligent Technology Co., Ltd., Kaohsiung 80661, Taiwan
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Liao WC, Mukundan A, Sadiaza C, Tsao YM, Huang CW, Wang HC. Systematic meta-analysis of computer-aided detection to detect early esophageal cancer using hyperspectral imaging. BIOMEDICAL OPTICS EXPRESS 2023; 14:4383-4405. [PMID: 37799695 PMCID: PMC10549751 DOI: 10.1364/boe.492635] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Revised: 07/05/2023] [Accepted: 07/06/2023] [Indexed: 10/07/2023]
Abstract
One of the leading causes of cancer deaths is esophageal cancer (EC) because identifying it in early stage is challenging. Computer-aided diagnosis (CAD) could detect the early stages of EC have been developed in recent years. Therefore, in this study, complete meta-analysis of selected studies that only uses hyperspectral imaging to detect EC is evaluated in terms of their diagnostic test accuracy (DTA). Eight studies are chosen based on the Quadas-2 tool results for systematic DTA analysis, and each of the methods developed in these studies is classified based on the nationality of the data, artificial intelligence, the type of image, the type of cancer detected, and the year of publishing. Deeks' funnel plot, forest plot, and accuracy charts were made. The methods studied in these articles show the automatic diagnosis of EC has a high accuracy, but external validation, which is a prerequisite for real-time clinical applications, is lacking.
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Affiliation(s)
- Wei-Chih Liao
- Department of Internal Medicine, National Taiwan University Hospital, National Taiwan University College of Medicine, Taipei, Taiwan
- Graduate Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei, Taiwan
| | - Arvind Mukundan
- Department of Mechanical Engineering, National Chung Cheng University, 168, University Rd., Min Hsiung, Chia Yi 62102, Taiwan
| | - Cleorita Sadiaza
- Department of Mechanical Engineering, Far Eastern University, P. Paredes St., Sampaloc, Manila, 1015, Philippines
| | - Yu-Ming Tsao
- Department of Mechanical Engineering, National Chung Cheng University, 168, University Rd., Min Hsiung, Chia Yi 62102, Taiwan
| | - Chien-Wei Huang
- Department of Gastroenterology, Kaohsiung Armed Forces General Hospital, 2, Zhongzheng 1st.Rd., Lingya District, Kaohsiung City 80284, Taiwan
- Department of Nursing, Tajen University, 20, Weixin Rd., Yanpu Township, Pingtung County 90741, Taiwan
| | - Hsiang-Chen Wang
- Department of Mechanical Engineering, National Chung Cheng University, 168, University Rd., Min Hsiung, Chia Yi 62102, Taiwan
- Department of Medical Research, Dalin Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, No. 2, Minsheng Road, Dalin, Chiayi, 62247, Taiwan
- Director of Technology Development, Hitspectra Intelligent Technology Co., Ltd., 4F., No. 2, Fuxing 4th Rd., Qianzhen Dist., Kaohsiung City 80661, Taiwan
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Mukundan A, Patel A, Saraswat KD, Tomar A, Wang HC. Design of a Foldable Laser-Based Energy Transmission System for a Mini Lunar Rover. 2023 3RD INTERNATIONAL CONFERENCE ON ELECTRICAL, COMPUTER, COMMUNICATIONS AND MECHATRONICS ENGINEERING (ICECCME) 2023. [DOI: 10.1109/iceccme57830.2023.10252208] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/15/2024]
Affiliation(s)
- Arvind Mukundan
- National Chung Cheng University City,Department of Mechanical Engineering and Advanced Institute of Manufacturing With High Tech Innovations,Chia Yi,62102
| | - Akash Patel
- Luleå University of Technolog City,Department of Computer Science, Electrical and Space Engineering,Sweden
| | | | - Ankit Tomar
- Indian Institute of Space Science & Technology,Department of Aerospace,Kerala,India,695547
| | - Hsiang-Chen Wang
- National Chung Cheng University City,Department of Mechanical Engineering and Advanced Institute of Manufacturing With High Tech Innovations,Chia Yi,62102
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Mukundan A, Patel A, Saraswat KD, Tomar A, Wang H.. Novel Design of a Sweeping 6-Degree of Freedom Lunar Penetrating Radar. AIAA AVIATION 2023 FORUM 2023. [DOI: 10.2514/6.2023-4124] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/15/2024]
Affiliation(s)
| | | | | | - Ankit Tomar
- Indian Institute of Space Science and Technology
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Mukundan A, Patel A, Saraswat KD, Tomar A, Wang H.. Spriallift Mechanism Based Drill for Deep Subsurface Lunar Exploration. AIAA AVIATION 2023 FORUM 2023. [DOI: 10.2514/6.2023-4123] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/15/2024]
Affiliation(s)
| | | | | | - Ankit Tomar
- Indian Institute of Space Science and Technology
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Wang CY, Mukundan A, Liu YS, Tsao YM, Lin FC, Fan WS, Wang HC. Optical Identification of Diabetic Retinopathy Using Hyperspectral Imaging. J Pers Med 2023; 13:939. [PMID: 37373927 DOI: 10.3390/jpm13060939] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Revised: 05/23/2023] [Accepted: 05/30/2023] [Indexed: 06/29/2023] Open
Abstract
The severity of diabetic retinopathy (DR) is directly correlated to changes in both the oxygen utilization rate of retinal tissue as well as the blood oxygen saturation of both arteries and veins. Therefore, the current stage of DR in a patient can be identified by analyzing the oxygen content in blood vessels through fundus images. This enables medical professionals to make accurate and prompt judgments regarding the patient's condition. However, in order to use this method to implement supplementary medical treatment, blood vessels under fundus images need to be determined first, and arteries and veins then need to be differentiated from one another. Therefore, the entire study was split into three sections. After first removing the background from the fundus images using image processing, the blood vessels in the images were then separated from the background. Second, the method of hyperspectral imaging (HSI) was utilized in order to construct the spectral data. The HSI algorithm was utilized in order to perform analysis and simulations on the overall reflection spectrum of the retinal image. Thirdly, principal component analysis (PCA) was performed in order to both simplify the data and acquire the major principal components score plot for retinopathy in arteries and veins at all stages. In the final step, arteries and veins in the original fundus images were separated using the principal components score plots for each stage. As retinopathy progresses, the difference in reflectance between the arteries and veins gradually decreases. This results in a more difficult differentiation of PCA results in later stages, along with decreased precision and sensitivity. As a consequence of this, the precision and sensitivity of the HSI method in DR patients who are in the normal stage and those who are in the proliferative DR (PDR) stage are the highest and lowest, respectively. On the other hand, the indicator values are comparable between the background DR (BDR) and pre-proliferative DR (PPDR) stages due to the fact that both stages exhibit comparable clinical-pathological severity characteristics. The results indicate that the sensitivity values of arteries are 82.4%, 77.5%, 78.1%, and 72.9% in the normal, BDR, PPDR, and PDR, while for veins, these values are 88.5%, 85.4%, 81.4%, and 75.1% in the normal, BDR, PPDR, and PDR, respectively.
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Affiliation(s)
- Ching-Yu Wang
- Department of Ophthalmology, Dalin Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Chiayi 62247, Taiwan
| | - Arvind Mukundan
- Department of Mechanical Engineering, National Chung Cheng University, Chiayi 62102, Taiwan
| | - Yu-Sin Liu
- Department of Mechanical Engineering, National Chung Cheng University, Chiayi 62102, Taiwan
| | - Yu-Ming Tsao
- Department of Mechanical Engineering, National Chung Cheng University, Chiayi 62102, Taiwan
| | - Fen-Chi Lin
- Department of Ophthalmology, Kaohsiung Armed Forces General Hospital, Kaohsiung 80284, Taiwan
| | - Wen-Shuang Fan
- Department of Ophthalmology, Dalin Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Chiayi 62247, Taiwan
| | - Hsiang-Chen Wang
- Department of Mechanical Engineering, National Chung Cheng University, Chiayi 62102, Taiwan
- Director of Technology Development, Hitspectra Intelligent Technology Co., Ltd., Kaohsiung 80661, Taiwan
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Lab-on-a-chip systems for cancer biomarker diagnosis. J Pharm Biomed Anal 2023; 226:115266. [PMID: 36706542 DOI: 10.1016/j.jpba.2023.115266] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Revised: 01/20/2023] [Accepted: 01/20/2023] [Indexed: 01/22/2023]
Abstract
Lab-on-a-chip (LOC) or micro total analysis system is one of the microfluidic technologies defined as the adaptation, miniaturization, integration, and automation of analytical laboratory procedures into a single instrument or "chip". In this article, we review developments over the past five years in the application of LOC biosensors for the detection of different types of cancer. Microfluidics encompasses chemistry and biotechnology skills and has revolutionized healthcare diagnosis. Superior to traditional cell culture or animal models, microfluidic technology has made it possible to reconstruct functional units of organs on chips to study human diseases such as cancer. LOCs have found numerous biomedical applications over the past five years, including integrated bioassays, cell analysis, metabolomics, drug discovery and delivery systems, tissue and organ physiology and disease modeling, and personalized medicine. This review provides an overview of the latest developments in microfluidic-based cancer research, with pros, cons, and prospects.
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Mukundan A, Patel A, Shastri B, Bhatt H, Phen A, Wang HC. The Dvaraka Initiative: Mars’s First Permanent Human Settlement Capable of Self-Sustenance. AEROSPACE 2023; 10:265. [DOI: 10.3390/aerospace10030265] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/15/2024]
Abstract
From the farthest reaches of the universe to our own galaxy, there are many different celestial bodies that, even though they are very different, each have their own way of being beautiful. Earth, the planet with the best location, has been home to people for as long as we can remember. Even though we cannot be more thankful for all that Earth has given us, the human population needs to grow so that Earth is not the only place where people can live. Mars, which is right next to Earth, is the answer to this problem. Mars is the closest planet and might be able to support human life because it is close to Earth and shares many things in common. This paper will talk about how the first settlement on Mars could be planned and consider a 1000-person colony and the best place to settle on Mars, and make suggestions for the settlement’s technical, architectural, social, and economic layout. By putting together assumptions, research, and estimates, the first settlement project proposed in this paper will suggest the best way to colonize, explore, and live on Mars, which is our sister planet.
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Affiliation(s)
- Arvind Mukundan
- Department of Mechanical Engineering, Advanced Institute of Manufacturing with High Tech Innovations (AIM-HI), Center for Innovative Research on Aging Society (CIRAS), National Chung Cheng University, 168, University Road, Min Hsiung, Chiayi City 62102, Taiwan
| | - Akash Patel
- Robotics & AI Team, Department of Computer, Electrical and Space Engineering, Luleå University of Technology, SE-97187 Luleå, Sweden
| | - Bharadwaj Shastri
- Department of Mechanical Engineering, Advanced Institute of Manufacturing with High Tech Innovations (AIM-HI), Center for Innovative Research on Aging Society (CIRAS), National Chung Cheng University, 168, University Road, Min Hsiung, Chiayi City 62102, Taiwan
| | - Heeral Bhatt
- Department of Computer, Electrical and Space Engineering, Luleå University of Technology, SE-97187 Luleå, Sweden
| | - Alice Phen
- Department of Computer, Electrical and Space Engineering, Luleå University of Technology, SE-97187 Luleå, Sweden
| | - Hsiang-Chen Wang
- Department of Mechanical Engineering, Advanced Institute of Manufacturing with High Tech Innovations (AIM-HI), Center for Innovative Research on Aging Society (CIRAS), National Chung Cheng University, 168, University Road, Min Hsiung, Chiayi City 62102, Taiwan
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Huang HY, Hsiao YP, Mukundan A, Tsao YM, Chang WY, Wang HC. Classification of Skin Cancer Using Novel Hyperspectral Imaging Engineering via YOLOv5. J Clin Med 2023; 12:1134. [PMID: 36769781 PMCID: PMC9918106 DOI: 10.3390/jcm12031134] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2023] [Revised: 01/30/2023] [Accepted: 01/30/2023] [Indexed: 02/04/2023] Open
Abstract
Many studies have recently used several deep learning methods for detecting skin cancer. However, hyperspectral imaging (HSI) is a noninvasive optics system that can obtain wavelength information on the location of skin cancer lesions and requires further investigation. Hyperspectral technology can capture hundreds of narrow bands of the electromagnetic spectrum both within and outside the visible wavelength range as well as bands that enhance the distinction of image features. The dataset from the ISIC library was used in this study to detect and classify skin cancer on the basis of basal cell carcinoma (BCC), squamous cell carcinoma (SCC), and seborrheic keratosis (SK). The dataset was divided into training and test sets, and you only look once (YOLO) version 5 was applied to train the model. The model performance was judged according to the generated confusion matrix and five indicating parameters, including precision, recall, specificity, accuracy, and the F1-score of the trained model. Two models, namely, hyperspectral narrowband image (HSI-NBI) and RGB classification, were built and then compared in this study to understand the performance of HSI with the RGB model. Experimental results showed that the HSI model can learn the SCC feature better than the original RGB image because the feature is more prominent or the model is not captured in other categories. The recall rate of the RGB and HSI models were 0.722 to 0.794, respectively, thereby indicating an overall increase of 7.5% when using the HSI model.
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Affiliation(s)
- Hung-Yi Huang
- Department of Dermatology, Ditmanson Medical Foundation Chiayi Christian Hospital, Chiayi 60002, Taiwan
| | - Yu-Ping Hsiao
- Department of Dermatology, Chung Shan Medical University Hospital, No. 110, Sec. 1, Jianguo N. Rd., South District, Taichung City 40201, Taiwan
- Institute of Medicine, School of Medicine, Chung Shan Medical University, No. 110, Sec. 1, Jianguo N. Rd., South District, Taichung City 40201, Taiwan
| | - Arvind Mukundan
- Department of Mechanical Engineering, Advanced Institute of Manufacturing with High Tech Innovations (AIM-HI) and Center for Innovative Research on Aging Society (CIRAS), National Chung Cheng University, No. 168, University Rd., Min Hsiung, Chiayi 62102, Taiwan
| | - Yu-Ming Tsao
- Department of Mechanical Engineering, Advanced Institute of Manufacturing with High Tech Innovations (AIM-HI) and Center for Innovative Research on Aging Society (CIRAS), National Chung Cheng University, No. 168, University Rd., Min Hsiung, Chiayi 62102, Taiwan
| | - Wen-Yen Chang
- Department of General Surgery, Kaohsiung Armed Forces General Hospital, No. 2, Zhongzheng 1st Rd., Lingya District, Kaohsiung 80284, Taiwan
| | - Hsiang-Chen Wang
- Department of Mechanical Engineering, Advanced Institute of Manufacturing with High Tech Innovations (AIM-HI) and Center for Innovative Research on Aging Society (CIRAS), National Chung Cheng University, No. 168, University Rd., Min Hsiung, Chiayi 62102, Taiwan
- Hitspectra Intelligent Technology Co., Ltd., 4F, No. 2, Fuxing 4th Rd., Qianzhen District, Kaohsiung 80661, Taiwan
- Department of Medical Research, Dalin Tzu Chi General Hospital, No. 2, Min-Sheng Rd., Dalin Town, Chiayi 62247, Taiwan
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Chen YS, Huang CH, Pai PC, Seo J, Lei KF. A Review on Microfluidics-Based Impedance Biosensors. BIOSENSORS 2023; 13:bios13010083. [PMID: 36671918 PMCID: PMC9855525 DOI: 10.3390/bios13010083] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Revised: 12/20/2022] [Accepted: 12/28/2022] [Indexed: 05/30/2023]
Abstract
Electrical impedance biosensors are powerful and continuously being developed for various biological sensing applications. In this line, the sensitivity of impedance biosensors embedded with microfluidic technologies, such as sheath flow focusing, dielectrophoretic focusing, and interdigitated electrode arrays, can still be greatly improved. In particular, reagent consumption reduction and analysis time-shortening features can highly increase the analytical capabilities of such biosensors. Moreover, the reliability and efficiency of analyses are benefited by microfluidics-enabled automation. Through the use of mature microfluidic technology, complicated biological processes can be shrunk and integrated into a single microfluidic system (e.g., lab-on-a-chip or micro-total analysis systems). By incorporating electrical impedance biosensors, hand-held and bench-top microfluidic systems can be easily developed and operated by personnel without professional training. Furthermore, the impedance spectrum provides broad information regarding cell size, membrane capacitance, cytoplasmic conductivity, and cytoplasmic permittivity without the need for fluorescent labeling, magnetic modifications, or other cellular treatments. In this review article, a comprehensive summary of microfluidics-based impedance biosensors is presented. The structure of this article is based on the different substrate material categorizations. Moreover, the development trend of microfluidics-based impedance biosensors is discussed, along with difficulties and challenges that may be encountered in the future.
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Affiliation(s)
- Yu-Shih Chen
- Department of Biomedical Engineering, Chang Gung University, Taoyuan 33302, Taiwan
| | - Chun-Hao Huang
- Department of Biomedical Engineering, Chang Gung University, Taoyuan 33302, Taiwan
| | - Ping-Ching Pai
- Department of Radiation Oncology, Linkou Chang Gung Memorial Hospital, Taoyuan 33305, Taiwan
| | - Jungmok Seo
- Department of Biomedical Engineering, Chang Gung University, Taoyuan 33302, Taiwan
- Department of Electrical & Electronic Engineering, Yonsei University, Seoul 120-749, Republic of Korea
| | - Kin Fong Lei
- Department of Biomedical Engineering, Chang Gung University, Taoyuan 33302, Taiwan
- Department of Radiation Oncology, Linkou Chang Gung Memorial Hospital, Taoyuan 33305, Taiwan
- Department of Electrical & Electronic Engineering, Yonsei University, Seoul 120-749, Republic of Korea
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Lovecchio N, Costantini F, Nascetti A, de Cesare G, Caputo D. Thin-Film-Based Multifunctional System for Optical Detection and Thermal Treatment of Biological Samples. BIOSENSORS 2022; 12:bios12110969. [PMID: 36354478 PMCID: PMC9688047 DOI: 10.3390/bios12110969] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Revised: 10/24/2022] [Accepted: 10/31/2022] [Indexed: 05/31/2023]
Abstract
In this work, we present a multifunctional Lab-on-Chip (LoC) platform based on hydrogenated amorphous silicon sensors suitable for a wide range of application in the fields of biochemical and food quality control analysis. The proposed system includes a LoC fabricated on a 5 cm × 5 cm glass substrate and a set of electronic boards for controlling the LoC functionalities. The presented Lab-on-Chip comprises light and temperature sensors, a thin film resistor acting as a heating source, and an optional thin film interferential filter suitable for fluorescence analysis. The developed electronics allows to control the thin film heater, a light source for fluorescence and absorption measurements, and the photosensors to acquire luminescent signals. All these modules are enclosed in a black metal box ensuring the portability of the whole platform. System performances have been evaluated in terms of sensor optical performances and thermal control achievements. For optical sensors, we have found a minimum number of detectable photons of 8 × 104 s-1·cm-2 at room temperature, 1.6 × 106 s-1·cm-2 in presence of fluorescence excitation source, and 2.4 × 106 s-1·cm-2 at 90 °C. From a thermal management point of view, we have obtained heating and cooling rates both equal to 2.2 °C/s, and a temperature sensor sensitivity of about 3 mV/°C even in presence of light. The achieved performances demonstrate the possibility to simultaneously use all integrated sensors and actuators, making promising the presented platform for a wide range of application fields.
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Affiliation(s)
- Nicola Lovecchio
- Department of Information Engineering, Electronics and Telecommunications, Sapienza University of Rome, 00184 Rome, Italy
| | - Francesca Costantini
- Department of Information Engineering, Electronics and Telecommunications, Sapienza University of Rome, 00184 Rome, Italy
- CREA-DC Research Centre for Plant Protection and Certification, 00156 Rome, Italy
| | - Augusto Nascetti
- School of Aerospace Engineering, Sapienza University of Rome, 00138 Rome, Italy
| | - Giampiero de Cesare
- Department of Information Engineering, Electronics and Telecommunications, Sapienza University of Rome, 00184 Rome, Italy
| | - Domenico Caputo
- Department of Information Engineering, Electronics and Telecommunications, Sapienza University of Rome, 00184 Rome, Italy
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17
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Mukundan A, Wang HC. The Brahmavarta Initiative: A Roadmap for the First Self-Sustaining City-State on Mars. UNIVERSE 2022; 8:550. [DOI: 10.3390/universe8110550] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/15/2024]
Abstract
The vast universe, from its unfathomable ends to our very own Milky Way galaxy, is comprised of numerous celestial bodies—disparate yet each having their uniqueness. Amongst these bodies exist only a handful that have an environment that can nurture and sustain life. The Homo sapiens species has inhabited the planet, which is positioned in a precise way—Earth. It is an irrefutable truth that the planet Earth has provided us with all necessities for survival—for the human race to flourish and prosper and make scientific and technological advancements. Humans have always had an innate ardor for exploration—and now, since they have explored every nook and corner of this planet, inhabiting it and utilizing its resources, the time has come to alleviate the burden we have placed upon Earth to be the sole life-sustaining planet. With limited resources in our grasp and an ever-proliferating population, it is the need of the hour that we take a leap and go beyond the planet for inhabitation—explore the other celestial objects in our galaxy. Then, however, there arises a confounding conundrum—where do we go? The answer is right next to our home—the Red Planet, Mars. Space scientists have confirmed that Mars has conditions to support life and is the closest candidate for human inhabitation. The planet has certain similarities to Earth and its proximity provides us with convenient contact. This paper will be dealing with the conceptual design for the first city-state on Mars. Aggregating assumptions, research, and estimations, this first settlement project shall propose the most optimal means to explore, inhabit and colonize our sister planet, Mars.
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Affiliation(s)
- Arvind Mukundan
- Department of Mechanical Engineering, Advanced Institute of Manufacturing with High Tech Innovations (AIM-HI) and Center for Innovative Research on Aging Society (CIRAS), National Chung Cheng Univesity, 168, University Rd., Min Hsiung, Chia Yi 62102, Taiwan
| | - Hsiang-Chen Wang
- Department of Mechanical Engineering, Advanced Institute of Manufacturing with High Tech Innovations (AIM-HI) and Center for Innovative Research on Aging Society (CIRAS), National Chung Cheng Univesity, 168, University Rd., Min Hsiung, Chia Yi 62102, Taiwan
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18
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Huang SY, Mukundan A, Tsao YM, Kim Y, Lin FC, Wang HC. Recent Advances in Counterfeit Art, Document, Photo, Hologram, and Currency Detection Using Hyperspectral Imaging. SENSORS (BASEL, SWITZERLAND) 2022; 22:7308. [PMID: 36236407 PMCID: PMC9571956 DOI: 10.3390/s22197308] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Revised: 09/15/2022] [Accepted: 09/23/2022] [Indexed: 05/08/2023]
Abstract
Forgery and tampering continue to provide unnecessary economic burdens. Although new anti-forgery and counterfeiting technologies arise, they inadvertently lead to the sophistication of forgery techniques over time, to a point where detection is no longer viable without technological aid. Among the various optical techniques, one of the recently used techniques to detect counterfeit products is HSI, which captures a range of electromagnetic data. To aid in the further exploration and eventual application of the technique, this study categorizes and summarizes existing related studies on hyperspectral imaging and creates a mini meta-analysis of this stream of literature. The literature review has been classified based on the product HSI has used in counterfeit documents, photos, holograms, artwork, and currency detection.
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Affiliation(s)
- Shuan-Yu Huang
- Department of Optometry, Central Taiwan University of Science and Technology, No. 666, Buzih Road, Beitun District, Taichung City 406053, Taiwan
| | - Arvind Mukundan
- Department of Mechanical Engineering, Advanced Institute of Manufacturing with High Tech Innovations (AIM-HI), Center for Innovative Research on Aging Society (CIRAS), National Chung Cheng University, 168, University Rd., Min Hsiung, Chia Yi 62102, Taiwan
| | - Yu-Ming Tsao
- Department of Mechanical Engineering, Advanced Institute of Manufacturing with High Tech Innovations (AIM-HI), Center for Innovative Research on Aging Society (CIRAS), National Chung Cheng University, 168, University Rd., Min Hsiung, Chia Yi 62102, Taiwan
| | - Youngjo Kim
- Department of Mechanical Engineering, Far Eastern University, P. Paredes St., Sampaloc, Manila 1015, Philippines
| | - Fen-Chi Lin
- Department of Ophthalmology, Kaohsiung Armed Forces General Hospital, 2, Zhongzheng 1st Rd., Lingya District, Kaohsiung City 80284, Taiwan
| | - Hsiang-Chen Wang
- Department of Mechanical Engineering, Advanced Institute of Manufacturing with High Tech Innovations (AIM-HI), Center for Innovative Research on Aging Society (CIRAS), National Chung Cheng University, 168, University Rd., Min Hsiung, Chia Yi 62102, Taiwan
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19
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Tsai TJ, Mukundan A, Chi YS, Tsao YM, Wang YK, Chen TH, Wu IC, Huang CW, Wang HC. Intelligent Identification of Early Esophageal Cancer by Band-Selective Hyperspectral Imaging. Cancers (Basel) 2022; 14:4292. [PMID: 36077827 PMCID: PMC9454598 DOI: 10.3390/cancers14174292] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Revised: 08/30/2022] [Accepted: 08/30/2022] [Indexed: 12/18/2022] Open
Abstract
In this study, the combination of hyperspectral imaging (HSI) technology and band selection was coupled with color reproduction. The white-light images (WLIs) were simulated as narrow-band endoscopic images (NBIs). As a result, the blood vessel features in the endoscopic image became more noticeable, and the prediction performance was improved. In addition, a single-shot multi-box detector model for predicting the stage and location of esophageal cancer was developed to evaluate the results. A total of 1780 esophageal cancer images, including 845 WLIs and 935 NBIs, were used in this study. The images were divided into three stages based on the pathological features of esophageal cancer: normal, dysplasia, and squamous cell carcinoma. The results showed that the mean average precision (mAP) reached 80% in WLIs, 85% in NBIs, and 84% in HSI images. This study's results showed that HSI has more spectral features than white-light imagery, and it improves accuracy by about 5% and matches the results of NBI predictions.
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Affiliation(s)
- Tsung-Jung Tsai
- Division of Gastroenterology and Hepatology, Department of Internal Medicine, Ditmanson Medical Foundation Chiayi Christian Hospital, Chia Yi City 60002, Taiwan
| | - Arvind Mukundan
- Department of Mechanical Engineering, Advanced Institute of Manufacturing with High Tech Innovations (AIM-HI) and Center for Innovative Research on Aging Society (CIRAS), National Chung Cheng University, 168, University Rd., Min Hsiung, Chia Yi City 62102, Taiwan
| | - Yu-Sheng Chi
- Department of Mechanical Engineering, Advanced Institute of Manufacturing with High Tech Innovations (AIM-HI) and Center for Innovative Research on Aging Society (CIRAS), National Chung Cheng University, 168, University Rd., Min Hsiung, Chia Yi City 62102, Taiwan
| | - Yu-Ming Tsao
- Department of Mechanical Engineering, Advanced Institute of Manufacturing with High Tech Innovations (AIM-HI) and Center for Innovative Research on Aging Society (CIRAS), National Chung Cheng University, 168, University Rd., Min Hsiung, Chia Yi City 62102, Taiwan
| | - Yao-Kuang Wang
- Division of Gastroenterology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, No. 100, Tzyou 1st Rd., Sanmin Dist., Kaohsiung City 80756, Taiwan
- Department of Medicine, Faculty of Medicine, College of Medicine, Kaohsiung Medical University, No. 100, Tzyou 1st Rd., Sanmin Dist., Kaohsiung City 80756, Taiwan
- Graduate Institute of Clinical Medicine, College of Medicine, Kaohsiung Medical University, No. 100, Tzyou 1st Rd., Sanmin Dist., Kaohsiung City 80756, Taiwan
| | - Tsung-Hsien Chen
- Division of Gastroenterology and Hepatology, Department of Internal Medicine, Ditmanson Medical Foundation Chiayi Christian Hospital, Chia Yi City 60002, Taiwan
| | - I-Chen Wu
- Department of Medicine, Faculty of Medicine, College of Medicine, Kaohsiung Medical University, No. 100, Tzyou 1st Rd., Sanmin Dist., Kaohsiung City 80756, Taiwan
- Graduate Institute of Clinical Medicine, College of Medicine, Kaohsiung Medical University, No. 100, Tzyou 1st Rd., Sanmin Dist., Kaohsiung City 80756, Taiwan
| | - Chien-Wei Huang
- Department of Gastroenterology, Kaohsiung Armed Forces General Hospital, 2, Zhongzheng 1st Rd., Lingya District, Kaohsiung City 80284, Taiwan
- Department of Nursing, Tajen University, 20, Weixin Rd., Yanpu Township, Pingtung County 90741, Taiwan
| | - Hsiang-Chen Wang
- Department of Mechanical Engineering, Advanced Institute of Manufacturing with High Tech Innovations (AIM-HI) and Center for Innovative Research on Aging Society (CIRAS), National Chung Cheng University, 168, University Rd., Min Hsiung, Chia Yi City 62102, Taiwan
- Director of Technology Development, Hitspectra Intelligent Technology Co., Ltd., 4F., No. 2, Fuxing 4th Rd., Qianzhen Dist., Kaohsiung City 80661, Taiwan
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Mukundan A, Huang CC, Men TC, Lin FC, Wang HC. Air Pollution Detection Using a Novel Snap-Shot Hyperspectral Imaging Technique. SENSORS (BASEL, SWITZERLAND) 2022; 22:s22166231. [PMID: 36015992 PMCID: PMC9416790 DOI: 10.3390/s22166231] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Revised: 08/11/2022] [Accepted: 08/16/2022] [Indexed: 05/04/2023]
Abstract
Air pollution has emerged as a global problem in recent years. Particularly, particulate matter (PM2.5) with a diameter of less than 2.5 μm can move through the air and transfer dangerous compounds to the lungs through human breathing, thereby creating major health issues. This research proposes a large-scale, low-cost solution for detecting air pollution by combining hyperspectral imaging (HSI) technology and deep learning techniques. By modeling the visible-light HSI technology of the aerial camera, the image acquired by the drone camera is endowed with hyperspectral information. Two methods are used for the classification of the images. That is, 3D Convolutional Neural Network Auto Encoder and principal components analysis (PCA) are paired with VGG-16 (Visual Geometry Group) to find the optical properties of air pollution. The images are classified into good, moderate, and severe based on the concentration of PM2.5 particles in the images. The results suggest that the PCA + VGG-16 has the highest average classification accuracy of 85.93%.
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Affiliation(s)
- Arvind Mukundan
- Department of Mechanical Engineering, Advanced Institute of Manufacturing with High Tech Innovations (AIM-HI), Center for Innovative Research on Aging Society (CIRAS), National Chung Cheng University, 168, University Rd., Min Hsiung, Chiayi City 62102, Taiwan
| | - Chia-Cheng Huang
- Department of Mechanical Engineering, Advanced Institute of Manufacturing with High Tech Innovations (AIM-HI), Center for Innovative Research on Aging Society (CIRAS), National Chung Cheng University, 168, University Rd., Min Hsiung, Chiayi City 62102, Taiwan
| | - Ting-Chun Men
- Department of Mechanical Engineering, Advanced Institute of Manufacturing with High Tech Innovations (AIM-HI), Center for Innovative Research on Aging Society (CIRAS), National Chung Cheng University, 168, University Rd., Min Hsiung, Chiayi City 62102, Taiwan
| | - Fen-Chi Lin
- Ophthalmology, Kaohsiung Armed Forces General Hospital, 2, Zhongzheng 1st. Rd., Lingya District, Kaohsiung City 80284, Taiwan
- Correspondence: (F.-C.L.); (H.-C.W.)
| | - Hsiang-Chen Wang
- Department of Mechanical Engineering, Advanced Institute of Manufacturing with High Tech Innovations (AIM-HI), Center for Innovative Research on Aging Society (CIRAS), National Chung Cheng University, 168, University Rd., Min Hsiung, Chiayi City 62102, Taiwan
- Correspondence: (F.-C.L.); (H.-C.W.)
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Fang YJ, Mukundan A, Tsao YM, Huang CW, Wang HC. Identification of Early Esophageal Cancer by Semantic Segmentation. J Pers Med 2022; 12:jpm12081204. [PMID: 35893299 PMCID: PMC9331549 DOI: 10.3390/jpm12081204] [Citation(s) in RCA: 29] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2022] [Revised: 07/19/2022] [Accepted: 07/22/2022] [Indexed: 02/06/2023] Open
Abstract
Early detection of esophageal cancer has always been difficult, thereby reducing the overall five-year survival rate of patients. In this study, semantic segmentation was used to predict and label esophageal cancer in its early stages. U-Net was used as the basic artificial neural network along with Resnet to extract feature maps that will classify and predict the location of esophageal cancer. A total of 75 white-light images (WLI) and 90 narrow-band images (NBI) were used. These images were classified into three categories: normal, dysplasia, and squamous cell carcinoma. After labeling, the data were divided into a training set, verification set, and test set. The training set was approved by the encoder–decoder model to train the prediction model. Research results show that the average time of 111 ms is used to predict each image in the test set, and the evaluation method is calculated in pixel units. Sensitivity is measured based on the severity of the cancer. In addition, NBI has higher accuracy of 84.724% when compared with the 82.377% accuracy rate of WLI, thereby making it a suitable method to detect esophageal cancer using the algorithm developed in this study.
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Affiliation(s)
- Yu-Jen Fang
- Department of Internal Medicine, National Taiwan University Hospital, Yun-Lin Branch, No. 579, Sec. 2, Yunlin Rd., Dou-Liu 64041, Taiwan;
- Department of Internal Medicine, National Taiwan University College of Medicine, No. 1 Jen Ai Rd. Sec. 1, Taipei 10051, Taiwan
| | - Arvind Mukundan
- Department of Mechanical Engineering, Advanced Institute of Manufacturing with High Tech Innovations (AIM-HI), Center for Innovative Research on Aging Society (CIRAS), National Chung Cheng University, 168, University Rd., Min Hsiung, Chiayi 62102, Taiwan; (A.M.); (Y.-M.T.)
| | - Yu-Ming Tsao
- Department of Mechanical Engineering, Advanced Institute of Manufacturing with High Tech Innovations (AIM-HI), Center for Innovative Research on Aging Society (CIRAS), National Chung Cheng University, 168, University Rd., Min Hsiung, Chiayi 62102, Taiwan; (A.M.); (Y.-M.T.)
- Hitspectra Intelligent Technology Co., Ltd., 4F., No. 2, Fuxing 4th Rd., Qianzhen Dist., Kaohsiung 80661, Taiwan
| | - Chien-Wei Huang
- Department of Gastroenterology, Kaohsiung Armed Forces General Hospital, 2, Zhongzheng 1st. Rd., Lingya Dist., Kaohsiung 80284, Taiwan
- Department of Nursing, Tajen University, 20, Weixin Rd., Yanpu Township, Pingtung 90741, Taiwan
- Correspondence: (C.-W.H.); (H.-C.W.)
| | - Hsiang-Chen Wang
- Department of Mechanical Engineering, Advanced Institute of Manufacturing with High Tech Innovations (AIM-HI), Center for Innovative Research on Aging Society (CIRAS), National Chung Cheng University, 168, University Rd., Min Hsiung, Chiayi 62102, Taiwan; (A.M.); (Y.-M.T.)
- Correspondence: (C.-W.H.); (H.-C.W.)
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