论文标题
计算机辅助诊断和治疗肿瘤的深度学习：一项调查
Deep Learning in Computer-Aided Diagnosis and Treatment of Tumors: A Survey
论文作者
论文摘要
近年来，计算机辅助诊断和治疗肿瘤是深度学习的热门话题，该主题构成了一系列的医疗任务，例如检测肿瘤标记，肿瘤休闲的轮廓，亚型和肿瘤的阶段，治疗效应的预测和药物发育。同时，有一些深度学习模型具有精确的定位，并在主流任务方案中产生了出色的表现。因此，遵循从任务意识到的深度学习方法，主要关注医疗任务的改进。然后，总结了肿瘤诊断和治疗的四个阶段的最新进展，该进展命名为视频诊断（IVD），成像诊断（ID），病理诊断（PD）和治疗计划（TP）。根据每个阶段的特定数据类型和医疗任务，我们介绍了深度学习在计算机辅助诊断和治疗肿瘤中的应用，并分析其中的出色作品。这项调查通过讨论研究问题并提出了未来改进的挑战结束。
Computer-Aided Diagnosis and Treatment of Tumors is a hot topic of deep learning in recent years, which constitutes a series of medical tasks, such as detection of tumor markers, the outline of tumor leisures, subtypes and stages of tumors, prediction of therapeutic effect, and drug development. Meanwhile, there are some deep learning models with precise positioning and excellent performance produced in mainstream task scenarios. Thus follow to introduce deep learning methods from task-orient, mainly focus on the improvements for medical tasks. Then to summarize the recent progress in four stages of tumor diagnosis and treatment, which named In-Vitro Diagnosis (IVD), Imaging Diagnosis (ID), Pathological Diagnosis (PD), and Treatment Planning (TP). According to the specific data types and medical tasks of each stage, we present the applications of deep learning in the Computer-Aided Diagnosis and Treatment of Tumors and analyzing the excellent works therein. This survey concludes by discussing research issues and suggesting challenges for future improvement.
