A novel visible and near-infrared hyperspectral imaging platform for automated breast-cancer detection

Youssef, Ahmed; Moa, Belaid; El-Sharkawy, Yasser H.

doi:10.1016/j.pdpdt.2024.104048

Photodiagnosis and Photodynamic Therapy

2024

DOI: 10.1016/j.pdpdt.2024.104048

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A novel visible and near-infrared hyperspectral imaging platform for automated breast-cancer detection

Ahmed Youssef,

Belaid Moa,

Yasser H. El-Sharkawy

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Advancing hyperspectral imaging and machine learning tools toward clinical adoption in tissue diagnostics: A comprehensive review

Lai,

Karmakar,

Mukundan

et al. 2024

APL Bioengineering

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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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Advancing hyperspectral imaging and machine learning tools toward clinical adoption in tissue diagnostics: A comprehensive review

Lai,

Karmakar,

Mukundan

et al. 2024

APL Bioengineering

View full text Add to dashboard Cite

show abstract

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A novel visible and near-infrared hyperspectral imaging platform for automated breast-cancer detection

Cited by 1 publication

References 29 publications

Advancing hyperspectral imaging and machine learning tools toward clinical adoption in tissue diagnostics: A comprehensive review

Advancing hyperspectral imaging and machine learning tools toward clinical adoption in tissue diagnostics: A comprehensive review

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