MI

Medical Image Analysis

Medical Image Analysis is an official journal of the MICCAI Society that publishes original research in medical and biological image analysis, with emphasis on applications of computer vision, virtual reality, and robotics to biomedical imaging problems. It covers biomedical image datasets across spatial scales, from molecular and cellular imaging to tissue and organ imaging, and includes work on algorithms and strategies for visualization, feature extraction, segmentation, registration, longitudinal studies, image-guided surgery and intervention, computational anatomy, computational physiology, telemedicine, telesurgery, and image-guided medical robots.

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Impact Factor 11.8
Quartile Q1
Open Access Type Hybrid
ISSN 1361-8415
eISSN 1361-8423
Invitation Only No
Cost Range Open Access APC: USD 4,470 (excluding taxes); Subscription: no publication fee charged to authors

Submission Instructions

Medical Image Analysis accepts the following article types. Click on an article type to view submission instructions.

Original Papers

Cover Letter Cover Letter requirements are not specified.
Abstract An abstract is required. Abstract must not exceed 250 words. Abstract must be unstructured and concise enough to stand alone.
Manuscript Manuscript must be divided into clearly defined numbered sections and include a Discussion section. The submission must include 1 to 7 English keywords, 3 to 5 highlights in a separate editable file, a graphical abstract as a separate file, author biographies of up to 100 words each, a competing interests declaration document, and an AI-use disclosure section before the references if generative AI was used in manuscript preparation.
References In-text citations must use author-name-and-year formatting. References must correspond exactly to the citations in the text and be listed alphabetically, then chronologically, with same-year works by the same author distinguished by letters.
Figures & Tables Figures must be uploaded as separate files, while tables must be submitted as editable text. Tables must be editable text with captions and consecutive numbering, and figures must be separately numbered, cited in the text, and accompanied by captions that include a brief title and description.
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Recent Publications

Enhanced multimodal MRI classification of schizophrenia through cross-attention graph neural networks

Jingjing Gao, Jie Wu, Maomin Qian, Zhengning Wang, Yanling Li, Na Luo, Xin Dai, Weiyang Shi, Peng Li, Jun Chen, Yunchun Chen, Huaning Wang, Wenming Liu, Zhigang Li, Yongfeng Yang, Hua Guo, Ping Wan, Luxian Lv, Lin Lu, Jun Yan, Yuqing Song, Huiling Wang, Hongxing Zhang, Yuhui Du, Yuqi Cheng, Jian Xu, Xiufeng Xu, Dai Zhang, Tianzai Jiang

10.1016/j.media.2026.104218
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Co-assistant networks by pathology foundation model and convolutional neural network for gigapixel whole slide image analysis

Zhuoran Liu, Junyi Shen, Lei Cui, Meilian Xu, Xiaofeng Zhu, Xiaoshuang Shi

10.1016/j.media.2026.104202
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Breaking error coupling via divergent–convergent coordination for semi-supervised medical image segmentation

Yuxuan Wan, Zhixuan Chen, Yuquan Xu, Yiyang Xu, Mingfeng Li, Yuefei Wang

10.1016/j.media.2026.104236
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KongNet: A multi-headed deep learning model for detection and classification of nuclei in histopathology images

Jiaqi Lv, Esha Sadia Nasir, Kesi Xu, Mostafa Jahanifar, Brinder Singh Chohan, Behnaz Elhaminia, Shan E. Ahmed Raza

10.1016/j.media.2026.104233
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Causal gradient intervention for debiased and evidence-grounded medical visual question answering

Bing Liu, Ziyuan Yang, Lijun Liu, Jiaman Ding, Wei Peng

10.1016/j.media.2026.104226
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Frequently asked questions

How long does it take to publish?

7 days from submission to first decision; 88 days from submission to decision after review; 253 days from submission to acceptance; 12 days from acceptance to first online publication.

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What are the publication costs?

Hybrid model. Open Access APC: USD 4,470 excluding taxes. Subscription publication has no publication fee charged to authors.

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Research Topics

Medical Image Segmentation Techniques AI in cancer detection Radiomics and Machine Learning in Medical Imaging Advanced MRI Techniques and Applications Medical Imaging Techniques and Applications Advanced Neuroimaging Techniques and Applications Advanced Neural Network Applications Medical Imaging and Analysis Functional Brain Connectivity Studies COVID-19 diagnosis using AI Cell Image Analysis Techniques Diverse Scientific and Economic Studies Human auditory perception and evaluation Retinal Imaging and Analysis Domain Adaptation and Few-Shot Learning Digital Imaging for Blood Diseases Educational Robotics and Engineering MRI in cancer diagnosis Image Retrieval and Classification Techniques 3D Shape Modeling and Analysis Advanced X-ray and CT Imaging Fetal and Pediatric Neurological Disorders Brain Tumor Detection and Classification Cardiac Imaging and Diagnostics Lung Cancer Diagnosis and Treatment