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Mohammadi FS, Shabani H, Zarei M. Fast and robust feature-based stitching algorithm for microscopic images. Sci Rep 2024; 14:13304. [PMID: 38858367 PMCID: PMC11164998 DOI: 10.1038/s41598-024-61970-y] [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: 12/17/2023] [Accepted: 05/13/2024] [Indexed: 06/12/2024] Open
Abstract
The limited field of view of high-resolution microscopic images hinders the study of biological samples in a single shot. Stitching of microscope images (tiles) captured by the whole-slide imaging (WSI) technique solves this problem. However, stitching is challenging due to the repetitive textures of tissues, the non-informative background part of the slide, and the large number of tiles that impact performance and computational time. To address these challenges, we proposed the Fast and Robust Microscopic Image Stitching (FRMIS) algorithm, which relies on pairwise and global alignment. The speeded up robust features (SURF) were extracted and matched within a small part of the overlapping region to compute the transformation and align two neighboring tiles. In cases where the transformation could not be computed due to an insufficient number of matched features, features were extracted from the entire overlapping region. This enhances the efficiency of the algorithm since most of the computational load is related to pairwise registration and reduces misalignment that may occur by matching duplicated features in tiles with repetitive textures. Then, global alignment was achieved by constructing a weighted graph where the weight of each edge is determined by the normalized inverse of the number of matched features between two tiles. FRMIS has been evaluated on experimental and synthetic datasets from different modalities with different numbers of tiles and overlaps, demonstrating faster stitching time compared to existing algorithms such as the Microscopy Image Stitching Tool (MIST) toolbox. FRMIS outperforms MIST by 481% for bright-field, 259% for phase-contrast, and 282% for fluorescence modalities, while also being robust to uneven illumination.
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Affiliation(s)
| | - Hasti Shabani
- Institute of Medical Science and Technology, Shahid Beheshti University, Tehran, Iran.
| | - Mojtaba Zarei
- Department of Clinical Research, University of Southern Denmark, Odense, Denmark
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Zhao B, Zhang K, Liu P, Chen Y. Large-scale time-lapse scanning electron microscopy image mosaic using a smooth stitching strategy. Microsc Res Tech 2023. [PMID: 37119500 DOI: 10.1002/jemt.24334] [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: 01/10/2023] [Revised: 03/23/2023] [Accepted: 04/15/2023] [Indexed: 05/01/2023]
Abstract
Due to the trade-off between the field of view and resolution of various microscopes, obtaining a wide-view panoramic image through high-resolution image tiles is frequently encountered and demanded in numerous applications. Here, we propose an automatic image mosaic strategy for sequential 2D time-lapse scanning electron microscopy (SEM) images. This method can accurately compute pairwise translations among serial image tiles with indeterminate overlapping areas. The detection and matching of feature points are limited by geographical coordinates, thus avoiding accidental mismatching. Moreover, the nonlinear deformation of the mosaic part is also taken into account. A smooth stitching field is utilized to gradually transform the perspective transformation in overlapping regions into the linear transformation in non-overlapping regions. Experimental results demonstrate that better image stitching accuracy can be achieved compared with some other image mosaic algorithms. Such a method has potential applications in high-resolution large-area analysis using serial microscopy images. RESEARCH HIGHLIGHTS: An automatic image mosaic strategy for processing sequential scanning electron microscopy images is proposed. A smooth stitching field is applied in the image mosaic. Improved stitching accuracy is achieved compared with other conventional mosaic methods.
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Affiliation(s)
- Binglu Zhao
- Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei, China
- Key Laboratory of Precision Scientific Instrumentation of Anhui Higher Education Institutes, University of Science and Technology of China, Hefei, China
| | - Kaidi Zhang
- Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei, China
- Key Laboratory of Precision Scientific Instrumentation of Anhui Higher Education Institutes, University of Science and Technology of China, Hefei, China
| | - Peng Liu
- Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei, China
- Key Laboratory of Precision Scientific Instrumentation of Anhui Higher Education Institutes, University of Science and Technology of China, Hefei, China
| | - Yuhang Chen
- Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei, China
- Key Laboratory of Precision Scientific Instrumentation of Anhui Higher Education Institutes, University of Science and Technology of China, Hefei, China
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Mach M, Stašík M, Kaván F, Mokrý P, Lédl V, Psota P. Subaperture stitching digital holographic microscopy for precise wear volume measurement in tribology. APPLIED OPTICS 2023; 62:2137-2144. [PMID: 37133103 DOI: 10.1364/ao.484468] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
Digital holographic microscopy (DHM) is an effective method for the evaluation of surface topography. It combines the high lateral resolution of microscopy with the high axial resolution of interferometry. In this paper, DHM with subaperture stitching for tribology is presented. The developed approach allows large surface area inspection by stitching together multiple measurements, which brings a big advantage to the evaluation of tribological tests such as a tribological track on a thin layer. The whole track measurement provides additional parameters, which can offer more information on the result of the tribological test than the conventional four-profile measurement by a contact profilometer.
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A Novel Approach for UAV Image Crack Detection. SENSORS 2022; 22:s22093305. [PMID: 35590994 PMCID: PMC9104641 DOI: 10.3390/s22093305] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Revised: 04/23/2022] [Accepted: 04/25/2022] [Indexed: 02/01/2023]
Abstract
Cracks are the most significant pre-disaster of a road, and are also important indicators for evaluating the damage level of a road. At present, road crack detection mainly depends on manual detection and road detection vehicles, with which the safety of detection workers is not guaranteed and the detection efficiency is low. A road detection vehicle can speed up the efficiency to a certain extent, but the automation level is low and it is easy to block the traffic. Unmanned Aerial Vehicles (UAV) have the characteristics of low energy consumption and easy control. If UAV technology can be applied to road crack detection, it will greatly improve the detection efficiency and produce huge economic benefits. In order to find a way to apply UAV to road crack detection, we developed a new technique for road crack detection based on UAV pictures, called DenxiDeepCrack, which is a trainable deep convolutional neural network for automatic crack detection which utilises learning high-level features for crack representation. In addition, we create a new dataset based on drone images called UCrack 11 to enrich the crack database of drone images for future crack detection research.
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Liu Y, Levenson RM, Jenkins MW. Slide Over: Advances in Slide-Free Optical Microscopy as Drivers of Diagnostic Pathology. THE AMERICAN JOURNAL OF PATHOLOGY 2022; 192:180-194. [PMID: 34774514 PMCID: PMC8883436 DOI: 10.1016/j.ajpath.2021.10.010] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Revised: 10/12/2021] [Accepted: 10/18/2021] [Indexed: 02/03/2023]
Abstract
Conventional analysis using clinical histopathology is based on bright-field microscopy of thinly sliced tissue specimens. Although bright-field microscopy is a simple and robust method of examining microscope slides, the preparation of the slides needed is a lengthy and labor-intensive process. Slide-free histopathology, however, uses direct imaging of intact, minimally processed tissue samples using advanced optical-imaging systems, bypassing the extended workflow now required for the preparation of tissue sections. This article explains the technical basis of slide-free microscopy, reviews common slide-free optical microscopy techniques, and discusses the opportunities and challenges involved in clinical implementation.
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Affiliation(s)
- Yehe Liu
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio
| | - Richard M. Levenson
- Department of Pathology and Laboratory Medicine, University of California–Davis, Sacramento, California,Address correspondence to Richard M. Levenson, M.D., UC Davis Health, Path Building, 4400 V St., Sacramento, CA 95817; or Michael W. Jenkins, Ph.D., 2109 Adelbert Rd., Wood Bldg., WG28, Cleveland, OH 44106.
| | - Michael W. Jenkins
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio,Address correspondence to Richard M. Levenson, M.D., UC Davis Health, Path Building, 4400 V St., Sacramento, CA 95817; or Michael W. Jenkins, Ph.D., 2109 Adelbert Rd., Wood Bldg., WG28, Cleveland, OH 44106.
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Dauleac C, Bannier E, Cotton F, Frindel C. Effect of distortion corrections on the tractography quality in spinal cord diffusion-weighted imaging. Magn Reson Med 2021; 85:3241-3255. [PMID: 33475180 DOI: 10.1002/mrm.28665] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2020] [Revised: 12/03/2020] [Accepted: 12/10/2020] [Indexed: 12/20/2022]
Abstract
PURPOSE To assess the impact of a different distortion correction (DC) method and patient geometry (sagittal balance) on the quality of spinal cord tractography rendering according to different tractography approaches. METHODS Forty-four adults free of spinal cord diseases underwent cervical diffusion-weighted imaging. The phase-encoding direction was head→foot. Sequence with opposed polarities (foot→head) was acquired to perform DC. Eddy-current, motion effects, and susceptibility artifact correction methods were used for DC, and two deterministic and one probabilistic tractography approaches were evaluated using MRtrix and DSI Studio tractography software. Fiber length and number of fibers were extracted to evaluate the quality of the tractography rendering. For each subject, cervical lordosis was measured to assess patient geometry. The angle between the main direction of the spinal cord and the orientation of the acquisition box were computed at each spine level to assess acquisition geometry and define an angle threshold for which a tractography of good quality is no longer possible. RESULTS There was a significant improvement in tractography quality after performing DC with susceptibility artifact correction using a deterministic approach based on tensor. Before DC, the angle threshold was defined at C6 (15.2°) compared with C7 (21.9°) after corrections, demonstrating the importance of spinal cord angulation for DC. CONCLUSION The impact of DC on tractography quality is greatly impacted by acquisition geometry. To obtain a good-quality tractography, we propose as a future perspective to adapt the acquisition geometry to that of the patient by automatically adjusting the acquisition box.
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Affiliation(s)
- Corentin Dauleac
- Department of Neurosurgery, Hôpital neurologique et neurochirurgical Pierre Wertheimer, Hospices Civils de Lyon, Lyon, France.,Université de Lyon, Université Claude Bernard Lyon I, Lyon, France.,Laboratoire CREATIS, CNRS UMR5220, INSA-Lyon, Université de Lyon I, Inserm U1206, Lyon, France
| | - Elise Bannier
- Université de Rennes, Inria, CNRS, Inserm, IRISA UMR 6074, Empenn, France.,Department of Radiology, CHU de Rennes, Rennes, France
| | - François Cotton
- Université de Lyon, Université Claude Bernard Lyon I, Lyon, France.,Laboratoire CREATIS, CNRS UMR5220, INSA-Lyon, Université de Lyon I, Inserm U1206, Lyon, France.,Department of Radiology, Centre Hospitalier de Lyon Sud, Hospices Civils de Lyon, Lyon, France
| | - Carole Frindel
- Université de Lyon, Université Claude Bernard Lyon I, Lyon, France.,Laboratoire CREATIS, CNRS UMR5220, INSA-Lyon, Université de Lyon I, Inserm U1206, Lyon, France
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Johnson KA, Hagen GM. Artifact-free whole-slide imaging with structured illumination microscopy and Bayesian image reconstruction. Gigascience 2020; 9:giaa035. [PMID: 32285910 PMCID: PMC7155289 DOI: 10.1093/gigascience/giaa035] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2019] [Revised: 12/06/2019] [Accepted: 03/24/2020] [Indexed: 01/19/2023] Open
Abstract
BACKGROUND Structured illumination microscopy (SIM) is a method that can be used to image biological samples and can achieve both optical sectioning and super-resolution effects. Optimization of the imaging set-up and data-processing methods results in high-quality images without artifacts due to mosaicking or due to the use of SIM methods. Reconstruction methods based on Bayesian estimation can be used to produce images with a resolution beyond that dictated by the optical system. FINDINGS Five complete datasets are presented including large panoramic SIM images of human tissues in pathophysiological conditions. Cancers of the prostate, skin, ovary, and breast, as well as tuberculosis of the lung, were imaged using SIM. The samples are available commercially and are standard histological preparations stained with hematoxylin-eosin. CONCLUSION The use of fluorescence microscopy is increasing in histopathology. There is a need for methods that reduce artifacts caused by the use of image-stitching methods or optical sectioning methods such as SIM. Stitched SIM images produce results that may be useful for intraoperative histology. Releasing high-quality, full-slide images and related data will aid researchers in furthering the field of fluorescent histopathology.
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Affiliation(s)
- Karl A Johnson
- UCCS BioFrontiers Center, University of Colorado at Colorado Springs, 1420 Austin Bluffs Parkway, Colorado Springs, CO 80918, USA
| | - Guy M Hagen
- UCCS BioFrontiers Center, University of Colorado at Colorado Springs, 1420 Austin Bluffs Parkway, Colorado Springs, CO 80918, USA
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Seo JH, Yang S, Kang MS, Her NG, Nam DH, Choi JH, Kim MH. Automated stitching of microscope images of fluorescence in cells with minimal overlap. Micron 2019; 126:102718. [PMID: 31473399 DOI: 10.1016/j.micron.2019.102718] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2019] [Revised: 07/25/2019] [Accepted: 07/25/2019] [Indexed: 10/26/2022]
Abstract
The morphology of tumor cells is highly related to their phenotype and activity. To verify the drug response of a brain tumor patient, fluorescence microscope images of drug-treated patient-derived cells in each well are analyzed. Due to the limitation of the field of view (FOV), a large number of small FOVs are acquired to compose one complete microscope well. Here, we propose an automated method for accurately stitching tile-scanned fluorescence microscope images, even with noise and a narrow overlapping region between adjacent fields. The proposed method is based on intensity-based normalized cross-correlation (NCC) and a triangular method-based threshold. The proposed method's quantitative accuracy and the sensitivity of the input was compared to other existing stitching tools, MIST and FijiIS, setting manually stitched images as the ground truth. The test images were 20 samples of 3 × 3 grid images in three versions of the fluorescence channel. The distance between the location of each field and number of cells was determined for different input field overlap ranges (1%, 3%, 5%, and 10%), while the actual value was about 1.15%. The proposed method had a distance error of 1.5 pixels at an input overlap of 1%, showing the lowest minimum error at all channels. Regarding the difference in cell numbers, although the number of overlapping cells was always small because of the narrow overlapping range, the proposed method was able to generate the resultant image with the smallest difference. In addition, to confirm the size limitation of the proposed algorithm, the accuracy of stitching images of grid structures 3 × 3, 5 × 5, 10 × 10-20 × 20 was tested, showing consistent results. In conclusion, quantitative evaluation of the performance of the method proved its improved accuracy compared to other current state-of-art techniques, and it showed robust performance even with noise and a narrow overlapping region between adjacent fields.
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Affiliation(s)
- Ji-Hyun Seo
- Department of Computer Science and Engineering, College of Engineering, Ewha Womans University, Seoul 03760, Republic of Korea
| | - Sejung Yang
- Division of Biomedical Engineering, College of Health Sciences, Yonsei University, Wonju, Gangwon-do 26493, Republic of Korea
| | - Mi-Sun Kang
- Department of Computer Science and Engineering, College of Engineering, Ewha Womans University, Seoul 03760, Republic of Korea
| | - Nam-Gu Her
- Institute for Refractory Cancer Research, Samsung Medical Center, Seoul 06351, Republic of Korea
| | - Do-Hyun Nam
- Institute for Refractory Cancer Research, Samsung Medical Center, Seoul 06351, Republic of Korea; Department of Neurosurgery, Samsung Medical Center, Sungkyunkwan University, Seoul 06351, Republic of Korea
| | - Jang-Hwan Choi
- Division of Mechanical and Biomedical Engineering, College of Engineering, Ewha Womans University, Seoul 03760, Republic of Korea.
| | - Myoung Hee Kim
- Department of Computer Science and Engineering, College of Engineering, Ewha Womans University, Seoul 03760, Republic of Korea.
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Digital, Rapid, Accurate, and Label-Free Enumeration of Viable Microorganisms Enabled by Custom-Built On-Glass-Slide Culturing Device and Microscopic Scanning. SENSORS 2018; 18:s18113700. [PMID: 30384414 PMCID: PMC6263752 DOI: 10.3390/s18113700] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/08/2018] [Revised: 10/11/2018] [Accepted: 10/24/2018] [Indexed: 01/11/2023]
Abstract
Accurately measuring the number of viable microorganisms plays an essential role in microbiological studies. Since the conventional agar method of enumerating visible colonies is time-consuming and not accurate, efforts have been made towards overcoming these limitations by counting the invisible micro-colonies. However, none of studies on micro-colony counting was able to save significant time or provide accurate results. Herein, we developed an on-glass-slide cell culture device that enables rapid formation of micro-colonies on a 0.38 mm-thick gel film without suffering from nutrient and oxygen deprivation during bacteria culturing. Employing a phase contrast imaging setup, we achieved rapid microscopic scanning of micro-colonies within a large sample area on the thin film without the need of fluorescent staining. Using Escherichia coli (E. coli) as a demonstration, our technique was able to shorten the culturing time to within 5 h and automatically enumerate the micro-colonies from the phase contrast images. Moreover, this method delivered more accurate counts than the conventional visible colony counting methods. Due to these advantages, this imaging-based micro-colony enumeration technique provides a new platform for the quantification of viable microorganisms.
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Deng WN, Wang S, Ventrici de Souza J, Kuhl TL, Liu GY. New Algorithm to Enable Construction and Display of 3D Structures from Scanning Probe Microscopy Images Acquired Layer-by-Layer. J Phys Chem A 2018; 122:5756-5763. [PMID: 29889521 DOI: 10.1021/acs.jpca.8b03417] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Scanning probe microscopy (SPM), such as atomic force microscopy (AFM), is widely known for high-resolution imaging of surface structures and nanolithography in two dimensions (2D), providing important physical insights into surface science and material science. This work reports a new algorithm to enable construction and display of layer-by-layer 3D structures from SPM images. The algorithm enables alignment of SPM images acquired during layer-by-layer deposition and removal of redundant features and faithfully constructs the deposited 3D structures. The display uses a "see-through" strategy to enable the structure of each layer to be visible. The results demonstrate high spatial accuracy as well as algorithm versatility; users can set parameters for reconstruction and display as per image quality and research needs. To the best of our knowledge, this method represents the first report to enable SPM technology for 3D imaging construction and display. The detailed algorithm is provided to facilitate usage of the same approach in any SPM software. These new capabilities support wide applications of SPM that require 3D image reconstruction and display, such as 3D nanoprinting and 3D additive and subtractive manufacturing and imaging.
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Affiliation(s)
- William Nanqiao Deng
- Department of Chemical Engineering , University of California , Davis , California 95616 , United States
| | - Shuo Wang
- Department of Chemistry , University of California , Davis , California 95616 , United States
| | - Joao Ventrici de Souza
- Department of Chemistry , University of California , Davis , California 95616 , United States
| | - Tonya L Kuhl
- Department of Chemical Engineering , University of California , Davis , California 95616 , United States
| | - Gang-Yu Liu
- Department of Chemistry , University of California , Davis , California 95616 , United States
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Shah MI, Mishra S, Yadav VK, Chauhan A, Sarkar M, Sharma SK, Rout C. Ziehl-Neelsen sputum smear microscopy image database: a resource to facilitate automated bacilli detection for tuberculosis diagnosis. J Med Imaging (Bellingham) 2017; 4:027503. [PMID: 28680911 DOI: 10.1117/1.jmi.4.2.027503] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2017] [Accepted: 06/14/2017] [Indexed: 11/14/2022] Open
Abstract
Ziehl-Neelsen stained microscopy is a crucial bacteriological test for tuberculosis detection, but its sensitivity is poor. According to the World Health Organization (WHO) recommendation, 300 viewfields should be analyzed to augment sensitivity, but only a few viewfields are examined due to patient load. Therefore, tuberculosis diagnosis through automated capture of the focused image (autofocusing), stitching of viewfields to form mosaics (autostitching), and automatic bacilli segmentation (grading) can significantly improve the sensitivity. However, the lack of unified datasets impedes the development of robust algorithms in these three domains. Therefore, the Ziehl-Neelsen sputum smear microscopy image database (ZNSM iDB) has been developed, and is freely available. This database contains seven categories of diverse datasets acquired from three different bright-field microscopes. Datasets related to autofocusing, autostitching, and manually segmenting bacilli can be used for developing algorithms, whereas the other four datasets are provided to streamline the sensitivity and specificity. All three categories of datasets were validated using different automated algorithms. As images available in this database have distinctive presentations with high noise and artifacts, this referral resource can also be used for the validation of robust detection algorithms. The ZNSM-iDB also assists for the development of methods in automated microscopy.
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Affiliation(s)
- Mohammad Imran Shah
- Jaypee University of Information Technology, Department of Biotechnology and Bioinformatics, Waknaghat, Himachal Pradesh, India
| | - Smriti Mishra
- Jaypee University of Information Technology, Department of Biotechnology and Bioinformatics, Waknaghat, Himachal Pradesh, India
| | - Vinod Kumar Yadav
- Jaypee University of Information Technology, Department of Biotechnology and Bioinformatics, Waknaghat, Himachal Pradesh, India
| | - Arun Chauhan
- Jaypee University of Information Technology, Department of Biotechnology and Bioinformatics, Waknaghat, Himachal Pradesh, India
| | - Malay Sarkar
- Indira Gandhi Medical College, Department of Pulmonary Medicine, Shimla, India
| | | | - Chittaranjan Rout
- Jaypee University of Information Technology, Department of Biotechnology and Bioinformatics, Waknaghat, Himachal Pradesh, India
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Wei L, Zhou S, Dong H, Mao Q, Lin J, Chen R. The plant virus microscope image registration method based on mismatches removing. Micron 2016; 80:90-5. [DOI: 10.1016/j.micron.2015.10.002] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2015] [Revised: 09/24/2015] [Accepted: 10/03/2015] [Indexed: 02/03/2023]
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Khan MB, Lee XY, Nisar H, Ng CA, Yeap KH, Malik AS. Digital image processing and analysis for activated sludge wastewater treatment. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2015; 823:227-48. [PMID: 25381111 DOI: 10.1007/978-3-319-10984-8_13] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Activated sludge system is generally used in wastewater treatment plants for processing domestic influent. Conventionally the activated sludge wastewater treatment is monitored by measuring physico-chemical parameters like total suspended solids (TSSol), sludge volume index (SVI) and chemical oxygen demand (COD) etc. For the measurement, tests are conducted in the laboratory, which take many hours to give the final measurement. Digital image processing and analysis offers a better alternative not only to monitor and characterize the current state of activated sludge but also to predict the future state. The characterization by image processing and analysis is done by correlating the time evolution of parameters extracted by image analysis of floc and filaments with the physico-chemical parameters. This chapter briefly reviews the activated sludge wastewater treatment; and, procedures of image acquisition, preprocessing, segmentation and analysis in the specific context of activated sludge wastewater treatment. In the latter part additional procedures like z-stacking, image stitching are introduced for wastewater image preprocessing, which are not previously used in the context of activated sludge. Different preprocessing and segmentation techniques are proposed, along with the survey of imaging procedures reported in the literature. Finally the image analysis based morphological parameters and correlation of the parameters with regard to monitoring and prediction of activated sludge are discussed. Hence it is observed that image analysis can play a very useful role in the monitoring of activated sludge wastewater treatment plants.
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Affiliation(s)
- Muhammad Burhan Khan
- Faculty of Engineering and Green Technology, Department of Electronic Engineering, Universiti Tunku Abdul Rahman, Kampar, Perak, Malaysia
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Wang Y, Xu R, Luo G, Wu J. Three-dimensional reconstruction of light microscopy image sections: present and future. Front Med 2014; 9:30-45. [DOI: 10.1007/s11684-014-0337-z] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2013] [Accepted: 03/27/2014] [Indexed: 12/31/2022]
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