Comparison of Vision Transformers and Convolutional Neural Networks in Medical Image Analysis: A Systematic Review

IF 3.5 3区 医学 Q1 HEALTH CARE SCIENCES & SERVICES
Satoshi Takahashi, Yusuke Sakaguchi, Nobuji Kouno, Ken Takasawa, Kenichi Ishizu, Yu Akagi, Rina Aoyama, Naoki Teraya, Amina Bolatkan, Norio Shinkai, Hidenori Machino, Kazuma Kobayashi, Ken Asada, Masaaki Komatsu, Syuzo Kaneko, Masashi Sugiyama, Ryuji Hamamoto
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Abstract

In the rapidly evolving field of medical image analysis utilizing artificial intelligence (AI), the selection of appropriate computational models is critical for accurate diagnosis and patient care. This literature review provides a comprehensive comparison of vision transformers (ViTs) and convolutional neural networks (CNNs), the two leading techniques in the field of deep learning in medical imaging. We conducted a survey systematically. Particular attention was given to the robustness, computational efficiency, scalability, and accuracy of these models in handling complex medical datasets. The review incorporates findings from 36 studies and indicates a collective trend that transformer-based models, particularly ViTs, exhibit significant potential in diverse medical imaging tasks, showcasing superior performance when contrasted with conventional CNN models. Additionally, it is evident that pre-training is important for transformer applications. We expect this work to help researchers and practitioners select the most appropriate model for specific medical image analysis tasks, accounting for the current state of the art and future trends in the field.

Abstract Image

医学图像分析中视觉变换器与卷积神经网络的比较:系统综述
在利用人工智能(AI)快速发展的医学图像分析领域,选择合适的计算模型对于准确诊断和患者护理至关重要。本文献综述全面比较了视觉变换器(ViT)和卷积神经网络(CNN)这两种医学影像深度学习领域的领先技术。我们进行了系统的调查。我们特别关注了这些模型在处理复杂医学数据集时的鲁棒性、计算效率、可扩展性和准确性。综述纳入了 36 项研究的结果,并指出了一个共同的趋势,即基于变压器的模型,尤其是 ViT,在各种医学成像任务中展现出巨大的潜力,与传统 CNN 模型相比表现出更优越的性能。此外,预训练对于变压器的应用显然非常重要。我们希望这项工作能帮助研究人员和从业人员根据该领域的技术现状和未来趋势,为特定的医学图像分析任务选择最合适的模型。
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来源期刊
Journal of Medical Systems
Journal of Medical Systems 医学-卫生保健
CiteScore
11.60
自引率
1.90%
发文量
83
审稿时长
4.8 months
期刊介绍: Journal of Medical Systems provides a forum for the presentation and discussion of the increasingly extensive applications of new systems techniques and methods in hospital clinic and physician''s office administration; pathology radiology and pharmaceutical delivery systems; medical records storage and retrieval; and ancillary patient-support systems. The journal publishes informative articles essays and studies across the entire scale of medical systems from large hospital programs to novel small-scale medical services. Education is an integral part of this amalgamation of sciences and selected articles are published in this area. Since existing medical systems are constantly being modified to fit particular circumstances and to solve specific problems the journal includes a special section devoted to status reports on current installations.
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