Inverse Problems and Imaging

884 papers and 10.0k indexed citations i.

About

The 884 papers published in Inverse Problems and Imaging in the last decades have received a total of 10.0k indexed citations. Papers published in Inverse Problems and Imaging usually cover Mathematical Physics (492 papers), Biomedical Engineering (271 papers) and Computer Vision and Pattern Recognition (221 papers) specifically the topics of Inverse Problems in Mathematical Physics and Imaging (480 papers), Microwave Imaging and Scattering Analysis (187 papers) and Advanced Mathematical Modeling in Engineering (169 papers). The most active scholars publishing in Inverse Problems and Imaging are Tony F. Chan, Victor Isakov, Stanley Osher, Xavier Bresson, Andreas Kirsch, Samuli Siltanen, Sari Lasanen, Xue‐Cheng Tai, Mila Nikolova and Matti Lassas.

In The Last Decade

Fields of papers published in Inverse Problems and Imaging

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Inverse Problems and Imaging. 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 Inverse Problems and Imaging.

Countries where authors publish in Inverse Problems and Imaging

Since Specialization
Citations

This map shows the geographic impact of research published in Inverse Problems and Imaging. 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 Inverse Problems and Imaging with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Inverse Problems and Imaging 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.

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2025