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Lai CL, Karmakar R, Mukundan A, Natarajan RK, Lu SC, Wang CY, Wang HC. Advancing hyperspectral imaging and machine learning tools toward clinical adoption in tissue diagnostics: A comprehensive review. APL Bioeng 2024; 8. [DOI: https:/doi.org/10.1063/5.0240444] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/02/2025] Open
Abstract
Hyperspectral imaging (HSI) has become an evident transformative apparatus in medical diagnostics. The review aims to appraise the present advancement and challenges in HSI for medical applications. It features a variety of medical applications namely diagnosing diabetic retinopathy, neurodegenerative diseases like Parkinson's and Alzheimer's, which illustrates its effectiveness in early diagnosis, early caries detection in periodontal disease, and dermatology by detecting skin cancer. Regardless of these advances, the challenges exist within every aspect that limits its broader clinical adoption. It has various constraints including difficulties with technology related to the complexity of the HSI system and needing specialist training, which may act as a drawback to its clinical settings. This article pertains to potential challenges expressed in medical applications and probable solutions to overcome these constraints. Successful companies that perform advanced solutions with HSI in terms of medical applications are being emphasized in this study to signal the high level of interest in medical diagnosis for systems to incorporate machine learning ML and artificial intelligence AI to foster precision diagnosis and standardized clinical workflow. This advancement signifies progressive possibilities of HSI in real-time clinical assessments. In conclusion despite HSI has been presented as a significant advanced medical imaging tool, addressing its limitations and probable solutions is for broader clinical adoption.
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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 1 , No. 2, Minsheng Road, Dalin, Chiayi 62247,
- Public School of Medicine, Tzu Chi University 2 , 701 Zhongyang Rd., Sec. 3, Hualien 97004,
| | - Riya Karmakar
- Department of Mechanical Engineering, National Chung Cheng University 3 , 168, University Road, Min Hsiung, Chiayi City 62102,
| | - Arvind Mukundan
- Department of Mechanical Engineering, National Chung Cheng University 3 , 168, University Road, Min Hsiung, Chiayi City 62102,
| | - Ragul Kumar Natarajan
- Department of Biotechnology, Karpagam Academy of Higher Education 4 , Salem - Kochi Hwy, Eachanari, Coimbatore, Tamil Nadu 641021,
| | - Song-Cun Lu
- Department of Mechanical Engineering, National Chung Cheng University 3 , 168, University Road, Min Hsiung, Chiayi City 62102,
| | - Cheng-Yi Wang
- Department of Gastroenterology, Kaohsiung Armed Forces General Hospital 5 , 2, Zhongzheng 1st. Rd., Kaohsiung City 80284,
| | - Hsiang-Chen Wang
- Department of Mechanical Engineering, National Chung Cheng University 3 , 168, University Road, Min Hsiung, Chiayi City 62102,
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Lai CL, Karmakar R, Mukundan A, Natarajan RK, Lu SC, Wang CY, Wang HC. Advancing hyperspectral imaging and machine learning tools toward clinical adoption in tissue diagnostics: A comprehensive review. APL Bioeng 2024; 8:041504. [PMID: 39660034 PMCID: PMC11629177 DOI: 10.1063/5.0240444] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2024] [Accepted: 11/19/2024] [Indexed: 12/12/2024] Open
Abstract
Hyperspectral imaging (HSI) has become an evident transformative apparatus in medical diagnostics. The review aims to appraise the present advancement and challenges in HSI for medical applications. It features a variety of medical applications namely diagnosing diabetic retinopathy, neurodegenerative diseases like Parkinson's and Alzheimer's, which illustrates its effectiveness in early diagnosis, early caries detection in periodontal disease, and dermatology by detecting skin cancer. Regardless of these advances, the challenges exist within every aspect that limits its broader clinical adoption. It has various constraints including difficulties with technology related to the complexity of the HSI system and needing specialist training, which may act as a drawback to its clinical settings. This article pertains to potential challenges expressed in medical applications and probable solutions to overcome these constraints. Successful companies that perform advanced solutions with HSI in terms of medical applications are being emphasized in this study to signal the high level of interest in medical diagnosis for systems to incorporate machine learning ML and artificial intelligence AI to foster precision diagnosis and standardized clinical workflow. This advancement signifies progressive possibilities of HSI in real-time clinical assessments. In conclusion despite HSI has been presented as a significant advanced medical imaging tool, addressing its limitations and probable solutions is for broader clinical adoption.
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Affiliation(s)
| | - Riya Karmakar
- Department of Mechanical Engineering, National Chung Cheng University, 168, University Road, Min Hsiung, Chiayi City 62102, Taiwan
| | - Arvind Mukundan
- Department of Mechanical Engineering, National Chung Cheng University, 168, University Road, Min Hsiung, Chiayi City 62102, Taiwan
| | - Ragul Kumar Natarajan
- Department of Biotechnology, Karpagam Academy of Higher Education, Salem - Kochi Hwy, Eachanari, Coimbatore, Tamil Nadu 641021, India
| | - Song-Cun Lu
- Department of Mechanical Engineering, National Chung Cheng University, 168, University Road, Min Hsiung, Chiayi City 62102, Taiwan
| | - Cheng-Yi Wang
- Department of Gastroenterology, Kaohsiung Armed Forces General Hospital, 2, Zhongzheng 1st. Rd., Kaohsiung City 80284, Taiwan
| | - Hsiang-Chen Wang
- Department of Mechanical Engineering, National Chung Cheng University, 168, University Road, Min Hsiung, Chiayi City 62102, Taiwan
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