Leaderboards/MRI in cancer diagnosis

MRI in cancer diagnosis

Last updated July 15, 2026

Rising Stars

Fresh ink, massive impact

Researchers

1
Magda Bosch de Basea Gómez
Teulades i Façanes Multifuncionals (Spain)
2
Aimon Rahman
Johns Hopkins University
3
Kevin J. Chung
University of California, Davis
4
Haiqing Fan
Guiyang Medical University
5
Chentao Cao
Hebei Semiconductor Research Institute
6
Gustav Müller‐Franzes
Universitätsklinikum Aachen
7
Viet Huan Le
Khanh Hoa General Hospital
8
Stefanie G. A. Veenhuizen
Utrecht University
9
Joseph S. R. Alisch
National Institutes of Health
10
Andrée‐Anne Berthiaume
Athira Pharma (United States)

Papers

1
Artificial intelligence-based MRI radiomics and radiogenomics in glioma
Cancer Imaging|2024
87 cit.
2
Publication in IEEE Transactions on Medical Imaging (2024) [80 citations, W4390706293]
IEEE Transactions on Medical Imaging|2024
80 cit.
3
Deep Learning Radiomics for Survival Prediction in Non-Small-Cell Lung Cancer Patients from CT Images
Journal of Medical Systems|2025
19 cit.
4
Medical slice transformer for improved diagnosis and explainability on 3D medical images with DINOv2
Scientific Reports|2025
16 cit.
5
Diffusion probabilistic versus generative adversarial models to reduce contrast agent dose in breast MRI
European Radiology Experimental|2024
9 cit.
6
Intraindividual Comparison of Different Methods for Automated BPE Assessment at Breast MRI: A Call for Standardization
Radiology|2024
7 cit.
7
Re-attendance in supplemental breast MRI screening rounds of the DENSE trial for women with extremely dense breasts
European Radiology|2024
6 cit.
8
Publication in Frontiers in Neuroscience (2024) [4 citations, W4391648463]
Frontiers in Neuroscience|2024
4 cit.
9
Publication in Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition (2024) [1 citation, W4401574535]
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition|2024
1 cit.
10
Publication (2025) [1 citation, W4409262562]
Unknown Journal|2025
1 cit.

Emerging Leaders

Drafting the new consensus

Researchers

1
Albert Gubern‐Mérida
Lightpoint Medical (United Kingdom)
2
Susie Y. Huang
Mass General Brigham
3
Iva Petkovska
Beth Israel Deaconess Medical Center
4
Ko Woon Park
Samsung Medical Center
5
Veeru Kasivisvanathan
University College London Hospitals NHS Foundation Trust
6
Eric M. Gale
Athinoula A. Martinos Center for Biomedical Imaging
7
Hongyu Jing
Jilin University
8
Lingyun Liu
Nanjing University
9
Ahmed E. Othman
Johannes Gutenberg University Mainz
10
Meihao Wang
Wenzhou Medical University

Papers

1
Deep Learning Reconstruction for Accelerated Spine MRI: Prospective Analysis of Interchangeability
Radiology|2022
92 cit.
2
SDnDTI: Self-supervised deep learning-based denoising for diffusion tensor MRI
NeuroImage|2022
75 cit.
3
Comparing biparametric to multiparametric MRI in the diagnosis of clinically significant prostate cancer in biopsy-naive men (PRIME): a prospective, international, multicentre, non-inferiority within-patient, diagnostic yield trial protocol
BMJ Open|2023
67 cit.
4
Comprehensive diffusion MRI dataset for in vivo human brain microstructure mapping using 300 mT/m gradients
Scientific Data|2022
56 cit.
5
Feasibility of an accelerated 2D-multi-contrast knee MRI protocol using deep-learning image reconstruction: a prospective intraindividual comparison with a standard MRI protocol
European Radiology|2022
49 cit.
6
Can financial agglomeration curb carbon emissions reduction from agricultural sector in China? Analyzing the role of industrial structure and digital finance
Journal of Cleaner Production|2024
47 cit.
7
Ultrafast Brain MRI with Deep Learning Reconstruction for Suspected Acute Ischemic Stroke
Radiology|2024
42 cit.
8
Prediction of pathologic complete response on MRI in patients with breast cancer receiving neoadjuvant chemotherapy according to molecular subtypes
European Radiology|2022
36 cit.
9
Combined artificial intelligence and radiologist model for predicting rectal cancer treatment response from magnetic resonance imaging: an external validation study
Abdominal Radiology|2022
33 cit.
10
Combination of Whole-Body Baseline CT Radiomics and Clinical Parameters to Predict Response and Survival in a Stage-IV Melanoma Cohort Undergoing Immunotherapy
Cancers|2022
27 cit.

Current Senior Leaders

Wrote the book, still writing it

Researchers

1
Ron Kikinis
Brigham and Women's Hospital
2
Hugo J.W.L. Aerts
Harvard University
3
Daniel C. Alexander
Hawassa University
4
David J. Hawkes
Wirral University Teaching Hospital NHS Foundation Trust
5
Peter J. Basser
Association of Military Surgeons of the United States
6
Alan C. Evans
Montreal Neurological Institute and Hospital
7
Bruce R. Rosen
Massachusetts General Hospital
8
Peter C.M. van Zijl
Kennedy Krieger Institute
9
Robert R. Edelman
Northwestern University
10
John Ashburner
University College London

Papers

1
3D Slicer as an image computing platform for the Quantitative Imaging Network
Magnetic Resonance Imaging|2012
8.9k cit.
2
A fast diffeomorphic image registration algorithm
NeuroImage|2007
8.3k cit.
3
Unified segmentation
NeuroImage|2005
7.5k cit.
4
Computational Radiomics System to Decode the Radiographic Phenotype
Cancer Research|2017
6.5k cit.
5
MR diffusion tensor spectroscopy and imaging
Biophysical Journal|1994
6k cit.
6
Nonrigid registration using free-form deformations: application to breast MR images
IEEE Transactions on Medical Imaging|1999
5.3k cit.
7
Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach
Nature Communications|2014
5.1k cit.
8
A nonparametric method for automatic correction of intensity nonuniformity in MRI data
IEEE Transactions on Medical Imaging|1998
4.8k cit.
9
How to correct susceptibility distortions in spin-echo echo-planar images: application to diffusion tensor imaging
NeuroImage|2003
3.7k cit.
10
Estimation of the Effective Self-Diffusion Tensor from the NMR Spin Echo
Journal of Magnetic Resonance Series B|1994
3.7k cit.

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