Medical Image Analysis

3.0k papers and 149.0k indexed citations i.

About

The 3.0k papers published in Medical Image Analysis in the last decades have received a total of 149.0k indexed citations. Papers published in Medical Image Analysis usually cover Radiology, Nuclear Medicine and Imaging (1.6k papers), Computer Vision and Pattern Recognition (1.4k papers) and Artificial Intelligence (739 papers) specifically the topics of Medical Image Segmentation Techniques (830 papers), AI in cancer detection (502 papers) and Radiomics and Machine Learning in Medical Imaging (483 papers). The most active scholars publishing in Medical Image Analysis are Mark Jenkinson, Stephen M. Smith, J.-P. Thirion, Bram van Ginneken, Max A. Viergever, Fred L. Bookstein, Geert Litjens, James C. Gee, J. B. Antoine Maintz and Clara I. Sá‎nchez.

In The Last Decade

Fields of papers published in Medical Image Analysis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Medical Image Analysis. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers published in Medical Image Analysis.

Countries where authors publish in Medical Image Analysis

Since Specialization
Citations

This map shows the geographic impact of research published in Medical Image Analysis. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by papers published in Medical Image Analysis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Medical Image Analysis more than expected).

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar’s output or impact.

Explore journals with similar magnitude of impact

Rankless by CCL
2025