Towards an integrated imaging for melanoma diagnosis: A review of multispectral, hyperspectral, and thermal technologies with preliminary system development.

IF 7 2区 医学 Q1 BIOLOGY
Computers in biology and medicine Pub Date : 2025-02-01 Epub Date: 2024-12-16 DOI:10.1016/j.compbiomed.2024.109570
Maria Oniga, Alina Sultana, Bogdan Alexandrescu, Olguța Orzan
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引用次数: 0

Abstract

The diagnosis of melanoma traditionally relies on visual inspection or on the use of the dermoscope, which do not have capabilities for early and precise detection. In this review, we aimed to explore other imaging technologies that can provide non-invasive and detailed information on skin lesions, such as multispectral, hyperspectral and thermal imaging. In this regard, the systems were evaluated in terms of hardware, performance and clinical applications. Since there is currently a very big interest in developing artificial intelligence (AI) applications in dermatology, the review also focuses on analysing studies that integrated this technology with newer imaging systems. To obtain clinical validation for such systems, there is an extensive need for publicly available datasets, as the current ones are limited. Expanding and obtaining new datasets is crucial in advancing research for a more accurate melanoma diagnosis. Taking into consideration the benefits that these imaging modalities can provide if they are combined with AI, we propose a prototype that can distinguish between melanoma and its precursor, the nevus, for which the set-up, components, imaging processing pipeline and classification techniques are described. The final system benefits of the advantages provided by near infrared, thermal and visible cameras, that allow a more in-depth characterizations of melanoma for a better understanding of its behaviour, an early detection improvement and diagnostic precision.

迈向黑色素瘤诊断的综合成像:多光谱、高光谱和热成像技术与初步系统开发的综述。
黑素瘤的诊断传统上依赖于视觉检查或皮肤镜的使用,这些方法无法进行早期和精确的检测。在这篇综述中,我们的目的是探索其他成像技术,可以提供非侵入性和详细的信息,如多光谱、高光谱和热成像。在这方面,系统在硬件,性能和临床应用方面进行了评估。由于目前人们对开发人工智能(AI)在皮肤病学中的应用非常感兴趣,因此本文还重点分析了将该技术与较新的成像系统相结合的研究。为了获得这些系统的临床验证,由于目前的数据集有限,因此对公开可用的数据集有广泛的需求。扩大和获得新的数据集对于推进更准确的黑色素瘤诊断研究至关重要。考虑到这些成像模式如果与人工智能相结合可以提供的好处,我们提出了一个可以区分黑色素瘤及其前体痣的原型,并描述了其设置、组件、成像处理管道和分类技术。最后的系统得益于近红外、热成像和可见光相机的优势,可以更深入地描述黑色素瘤的特征,从而更好地了解其行为,提高早期检测和诊断精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Computers in biology and medicine
Computers in biology and medicine 工程技术-工程:生物医学
CiteScore
11.70
自引率
10.40%
发文量
1086
审稿时长
74 days
期刊介绍: Computers in Biology and Medicine is an international forum for sharing groundbreaking advancements in the use of computers in bioscience and medicine. This journal serves as a medium for communicating essential research, instruction, ideas, and information regarding the rapidly evolving field of computer applications in these domains. By encouraging the exchange of knowledge, we aim to facilitate progress and innovation in the utilization of computers in biology and medicine.
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