Sulaiman Vesal

1.2k total citations
21 papers, 221 citations indexed

About

Sulaiman Vesal is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Artificial Intelligence. According to data from OpenAlex, Sulaiman Vesal has authored 21 papers receiving a total of 221 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Radiology, Nuclear Medicine and Imaging, 14 papers in Pulmonary and Respiratory Medicine and 7 papers in Artificial Intelligence. Recurrent topics in Sulaiman Vesal's work include Radiomics and Machine Learning in Medical Imaging (12 papers), Prostate Cancer Diagnosis and Treatment (11 papers) and AI in cancer detection (7 papers). Sulaiman Vesal is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (12 papers), Prostate Cancer Diagnosis and Treatment (11 papers) and AI in cancer detection (7 papers). Sulaiman Vesal collaborates with scholars based in United States, Germany and United Kingdom. Sulaiman Vesal's co-authors include Andreas Maier, Nishant Ravikumar, Mirabela Rusu, Richard E. Fan, Geoffrey A. Sonn, Ekta Walia, Indrani Bhattacharya, Ronak Kosti, Yipeng Hu and Pejman Ghanouni and has published in prestigious journals such as PLoS ONE, The Journal of Urology and IEEE Transactions on Medical Imaging.

In The Last Decade

Sulaiman Vesal

17 papers receiving 219 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Sulaiman Vesal United States 9 118 81 74 64 39 21 221
Riqiang Gao United States 11 213 1.8× 97 1.2× 94 1.3× 115 1.8× 57 1.5× 34 340
Qicheng Lao China 11 104 0.9× 85 1.0× 128 1.7× 23 0.4× 25 0.6× 29 250
Ela M. Akay Germany 7 96 0.8× 117 1.4× 30 0.4× 99 1.5× 44 1.1× 11 281
Florin C. Ghesu United States 7 122 1.0× 51 0.6× 83 1.1× 31 0.5× 42 1.1× 13 223
Ruibin Feng United States 5 175 1.5× 109 1.3× 153 2.1× 42 0.7× 28 0.7× 13 297
Luisa F. Sánchez‐Peralta Spain 10 119 1.0× 103 1.3× 105 1.4× 44 0.7× 105 2.7× 24 364
Nils Gessert Germany 9 126 1.1× 59 0.7× 135 1.8× 19 0.3× 102 2.6× 24 336
Joanne Hoffman United States 5 259 2.2× 98 1.2× 126 1.7× 147 2.3× 97 2.5× 7 415
Vivek Vaidya India 5 144 1.2× 60 0.7× 83 1.1× 74 1.2× 19 0.5× 18 219

Countries citing papers authored by Sulaiman Vesal

Since Specialization
Citations

This map shows the geographic impact of Sulaiman Vesal's research. 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 Sulaiman Vesal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sulaiman Vesal more than expected).

Fields of papers citing papers by Sulaiman Vesal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sulaiman Vesal. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Sulaiman Vesal. The network helps show where Sulaiman Vesal may publish in the future.

Co-authorship network of co-authors of Sulaiman Vesal

This figure shows the co-authorship network connecting the top 25 collaborators of Sulaiman Vesal. A scholar is included among the top collaborators of Sulaiman Vesal based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Sulaiman Vesal. Sulaiman Vesal is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Zhou, Steve, Li‐Chun Zhang, Moon Hyung Choi, et al.. (2025). ProMUS ‐ NET : Artificial intelligence detects more prostate cancer than urologists on micro‐ultrasonography. British Journal of Urology. 136(6). 1071–1079.
2.
Li, Cynthia, Indrani Bhattacharya, Sulaiman Vesal, et al.. (2025). ProstAtlasDiff: Prostate cancer detection on MRI using Diffusion Probabilistic Models guided by population spatial cancer atlases. Medical Image Analysis. 101. 103486–103486. 1 indexed citations
3.
Rusu, Mirabela, Sulaiman Vesal, Cynthia Li, et al.. (2025). ProCUSNet: Prostate Cancer Detection on B-mode Transrectal Ultrasound Using Artificial Intelligence for Targeting During Prostate Biopsies. European Urology Oncology. 8(2). 477–485.
4.
Li, Cynthia, Sulaiman Vesal, Indrani Bhattacharya, et al.. (2025). IP21-24 MULTIMODAL MRI-TRUS AI MODEL EXCEEDS RADIOLOGIST PERFORMANCE IN PROSTATE CANCER DETECTION. The Journal of Urology. 213(5S).
5.
Vesal, Sulaiman, Indrani Bhattacharya, Xinran Li, et al.. (2024). A deep learning framework to assess the feasibility of localizing prostate cancer on b-mode transrectal ultrasound images. 26–26. 1 indexed citations
6.
Shao, Wei, Sulaiman Vesal, Simon John Christoph Soerensen, et al.. (2024). RAPHIA: A deep learning pipeline for the registration of MRI and whole-mount histopathology images of the prostate. Computers in Biology and Medicine. 173. 108318–108318. 8 indexed citations
7.
Sang, Shengtian, Xinran Li, Sulaiman Vesal, et al.. (2024). Swin Transformer-based affine registration of MRI and ultrasound images of the prostate. 6–6. 1 indexed citations
8.
Zhou, Steve, Moon Hyung Choi, Sulaiman Vesal, et al.. (2024). Inter-reader Agreement for Prostate Cancer Detection Using Micro-ultrasound: A Multi-institutional Study. European Urology Open Science. 66. 93–100. 6 indexed citations
9.
Bhattacharya, Indrani, Sulaiman Vesal, Moon Hyung Choi, et al.. (2024). MP31-18 ARTIFICIAL INTELLIGENCE-ASSISTED PROSTATE CANCER DETECTION ON B-MODE TRANSRECTAL ULTRASOUND IMAGES. The Journal of Urology. 211(5S).
10.
Priester, Alan, Richard E. Fan, Mirabela Rusu, et al.. (2023). Prediction and Mapping of Intraprostatic Tumor Extent with Artificial Intelligence. European Urology Open Science. 54. 20–27. 8 indexed citations
11.
Vesal, Sulaiman, Indrani Bhattacharya, Shyam Natarajan, et al.. (2022). Domain generalization for prostate segmentation in transrectal ultrasound images: A multi-center study. Medical Image Analysis. 82. 102620–102620. 22 indexed citations
12.
Khandwala, Yash S., Simon John Christoph Soerensen, Pejman Ghanouni, et al.. (2022). The Association of Tissue Change and Treatment Success During High-intensity Focused Ultrasound Focal Therapy for Prostate Cancer. European Urology Focus. 9(4). 584–591. 2 indexed citations
13.
14.
Bhattacharya, Indrani, Yash S. Khandwala, Sulaiman Vesal, et al.. (2022). A review of artificial intelligence in prostate cancer detection on imaging. Therapeutic Advances in Urology. 14. 3623475287–3623475287. 46 indexed citations
15.
Vesal, Sulaiman, et al.. (2021). Adapt Everywhere: Unsupervised Adaptation of Point-Clouds and Entropy Minimization for Multi-Modal Cardiac Image Segmentation. IEEE Transactions on Medical Imaging. 40(7). 1838–1851. 34 indexed citations
16.
Vesal, Sulaiman, et al.. (2020). Spatio-Temporal Multi-Task Learning for Cardiac MRI Left Ventricle Quantification. IEEE Journal of Biomedical and Health Informatics. 25(7). 2698–2709. 11 indexed citations
17.
Ellmann, Stephan, Evelyn Wenkel, Matthias Dietzel, et al.. (2020). Implementation of machine learning into clinical breast MRI: Potential for objective and accurate decision-making in suspicious breast masses. PLoS ONE. 15(1). e0228446–e0228446. 18 indexed citations
18.
Vesal, Sulaiman, Andreas Maier, & Nishant Ravikumar. (2020). Fully Automated 3D Cardiac MRI Localisation and Segmentation Using Deep Neural Networks. Journal of Imaging. 6(7). 65–65. 25 indexed citations
19.
Kaiser, Nico, Andreas Fieselmann, Ludwig Ritschl, et al.. (2019). Mammographic breast density classification using a deep neural network: assessment on the basis of inter-observer variability. 23–23. 5 indexed citations
20.
Vesal, Sulaiman, Nishant Ravikumar, & Andreas Maier. (2019). A 2D dilated residual U-Net for multi-organ segmentation in thoracic CT. arXiv (Cornell University). 7 indexed citations

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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