Progress in deep learning based on magnetic resonance imaging for rectal cancer research
Rectal cancer(RC)is a malignancy with a high incidence rate worldwide,posing significant challenges in its management and treatment.MRI is the conventional modality used to assess RC.However,both traditional MRI and functional MRI frequently fall short in providing sufficient information for the development of personalized treatment plans for RC patients due to their inherent limitations.With the rapid advancements in artificial intelligence within the medical field in recent years,deep learning technologies have demonstrated tremendous potential and broad prospects for applications in areas such as RC staging,treatment response evaluation,RC segmentation,and genetic typing.These advancements suggest that deep learning could pave new ways for enhancing the precision and personalization of treatment decisions in RC in the future.This article presents a comprehensive review on the application of MRI-based deep learning techniques in RC,aiming to assist in selecting the optimal treatment strategy for RC patients,thereby improving patient outcomes,and providing new insights and directions for future research endeavors.
国家科技期刊平台
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