期刊
CURRENT OPINION IN BIOMEDICAL ENGINEERING
卷 28, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.cobme.2023.100495
关键词
In vivo cancer detection Low-resource settings Optical imaging Deep; learning.
This article reviews the recent development and application of low-cost optical imaging technologies, emphasizing the integration of artificial intelligence to improve in vivo cancer detection accuracy in low-resource settings. The article also discusses the challenges and future prospects of applying optical imaging technologies in clinical practice.
Cancer continues to affect underserved populations disproportionately. Novel optical imaging technologies, which can provide rapid, non-invasive, and accurate cancer detection at the point of care, have great potential to improve global cancer care. This article reviews the recent technical innovations and clinical translation of low-cost optical imaging technologies, highlighting the advances in both hardware and software, especially the integration of artificial intelligence, to improve in vivo cancer detection in low-resource settings. Additionally, this article provides an overview of existing challenges and future perspectives of adapting optical imaging technologies into clinical practice, which can potentially contribute to novel insights and programs that effectively improve cancer detection in low-resource settings.
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