Advances in Medical Image Analysis with Vision Transformers: A Comprehensive Review

By Reza Azad, Amirhossein Kazerouni, Moein Heidari, Ehsan Khodapanah Aghdam, Amir Molaei, Yiwei Jia, Abin Jose, Rijo Roy, Dorit Merhof. Medical Image Anal., 2023

419 citations recorded by the source corpus.

The remarkable performance of the Transformer architecture in natural language processing has recently also triggered broad interest in Computer Vision. Among other merits, Transformers are witnessed as capable of learning long-range dependencies and spatial correlations, which is a clear advantage over convolutional neural networks (CNNs), which have been the de facto standard in Computer Vision problems so far. Thus, Transformers have become an integral part of modern medical image analysis. In this review, we provide an encyclopedic review of the applications of Transformers in medical imaging. Specifically, we present a systematic and thorough review of relevant recent Transformer literature for different medical image analysis tasks, including classification, segmentation, detection, registration, synthesis, and clinical report generation. For each of these applications, we investigate the novelty, strengths and weaknesses of the different proposed strategies and develop taxonomies highlighting key properties and contributions. Further, if applicable, we outline current benchmarks on different datasets. Finally, we summarize key challenges and discuss different future research directions. In addition, we have provided cited papers with their corresponding implementations in https://github.com/mindflow-institue/Awesome-Transformer.

Subfields: Artificial Intelligence, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/8b0357f1bceb9cf7a5629b0ba3acb5660edf90b2

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Ehsan Khodapanah Aghdam
2. Dorit Merhof
3. Reza Azad
4. Yiwei Jia
5. Ehsan Adeli

In Radiology, Nuclear Medicine and Imaging

1. Ehsan Khodapanah Aghdam
2. Dorit Merhof
3. Reza Azad

Citations in the corpus

• Medical Image Segmentation Review: The Success of U-Net (2022, background): “However, an in-depth analysis of the ViT and its functionality can be found in [114].”