Lai Chun-Liang, Karmakar Riya, Mukundan Arvind, Natarajan Ragul Kumar, Lu Song-Cun, Wang Cheng-Yi, Wang Hsiang-Chen
Department of Mechanical Engineering, National Chung Cheng University, 168, University Road, Min Hsiung, Chiayi City 62102, Taiwan.
Department of Biotechnology, Karpagam Academy of Higher Education, Salem - Kochi Hwy, Eachanari, Coimbatore, Tamil Nadu 641021, India.
APL Bioeng. 2024 Dec 6;8(4):041504. doi: 10.1063/5.0240444. eCollection 2024 Dec.
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.
高光谱成像（HSI）已成为医学诊断中一种显著的变革性工具。本综述旨在评估HSI在医学应用方面的当前进展和挑战。它具有多种医学应用，即诊断糖尿病视网膜病变、帕金森氏症和阿尔茨海默氏症等神经退行性疾病，这说明了其在早期诊断中的有效性、牙周病早期龋齿检测以及通过检测皮肤癌用于皮肤科。尽管有这些进展，但在限制其更广泛临床应用的各个方面仍存在挑战。它有各种限制，包括与HSI系统复杂性相关的技术难题以及需要专业培训，这可能成为其在临床环境中的一个缺点。本文涉及医学应用中所表达的潜在挑战以及克服这些限制的可能解决方案。本研究强调了在医学应用方面成功运用HSI先进解决方案的公司，以表明对将机器学习（ML）和人工智能（AI）纳入系统以促进精准诊断和标准化临床工作流程的医学诊断的高度兴趣。这一进展标志着HSI在实时临床评估中的进步可能性。总之，尽管HSI已被视为一种重要的先进医学成像工具，但解决其局限性和可能的解决方案对于更广泛的临床应用至关重要。
