Bradley J. Erickson

17.4k total citations · 5 hit papers
280 papers, 10.4k citations indexed

About

Bradley J. Erickson is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Artificial Intelligence. According to data from OpenAlex, Bradley J. Erickson has authored 280 papers receiving a total of 10.4k indexed citations (citations by other indexed papers that have themselves been cited), including 143 papers in Radiology, Nuclear Medicine and Imaging, 55 papers in Pulmonary and Respiratory Medicine and 48 papers in Artificial Intelligence. Recurrent topics in Bradley J. Erickson's work include Radiomics and Machine Learning in Medical Imaging (69 papers), AI in cancer detection (39 papers) and Medical Imaging Techniques and Applications (29 papers). Bradley J. Erickson is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (69 papers), AI in cancer detection (39 papers) and Medical Imaging Techniques and Applications (29 papers). Bradley J. Erickson collaborates with scholars based in United States, Canada and Austria. Bradley J. Erickson's co-authors include Zeynettin Akkus, Panagiotis Korfiatis, Timothy L. Kline, Kenneth A. Philbrick, Daniel L. Rubin, Assaf Hoogi, Alfiia Galimzianova, Alexander D. Weston, Felipe Kitamura and Jan C. Buckner and has published in prestigious journals such as Circulation, Journal of Clinical Oncology and SHILAP Revista de lepidopterología.

In The Last Decade

Bradley J. Erickson

263 papers receiving 10.2k citations

Hit Papers

5 papers align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Machine Learning for Medical Imaging

2017 1.1k citations Bradley J. Erickson, Panagiotis Korfiatis et al. profile →
Deep Learning for Brain MRI Segmentation: State of the Art and Future Directions

2017 722 citations Bradley J. Erickson et al. Journal of Digital Imaging profile →
Imaging Classification of Autosomal Dominant Polycystic Kidney Disease

2014 407 citations Marie C. Hogan, Peter C. Harris et al. Journal of the American Society of Nephrology profile →
Association between pathological and MRI findings in multiple sclerosis

2012 377 citations Bradley J. Erickson et al. profile →
The Effects of Changes in Utilization and Technological Advancements of Cross-Sectional Imaging on Radiologist Workload

2015 307 citations Bradley J. Erickson et al. profile →

Peers

Countries citing papers authored by Bradley J. Erickson

Since Specialization

Citations

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

Fields of papers citing papers by Bradley J. Erickson

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Bradley J. Erickson. 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 Bradley J. Erickson. The network helps show where Bradley J. Erickson may publish in the future.

Co-authorship network of co-authors of Bradley J. Erickson

This figure shows the co-authorship network connecting the top 25 collaborators of Bradley J. Erickson. A scholar is included among the top collaborators of Bradley J. Erickson 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 Bradley J. Erickson. Bradley J. Erickson is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

#	Work	Indexed citations
1	A comparative analysis of privacy-preserving large language models for automated echocardiography report analysis 2025 ·Journal of the American Medical Informatics Association ·Elham Mahmoudi, (unknown), Chieh‐Ju Chao, Bardia Khosravi, Arundhati Misra, Francisco López-Jiménez, Bradley J. Erickson	2
2	Deep Learning-Based Instance-Level Segmentation of Kidney and Liver Cysts in Computed Tomography Images of Patients Affected by Polycystic Kidney Disease 2025 ·Kidney360 ·Adriana Gregory, Mahmoud A. Khalifa, J G Im, (unknown), (unknown), (unknown), Hana Yang, Aleksandar Đenić, Andrew D. Rule, Fouad T. Chebib, Neera K. Dahl, Marie C. Hogan, Peter C. Harris, Vicente E. Torres, Bradley J. Erickson, Theodora A. Potretzke, Timothy L. Kline	0
3	Role of Model Size and Prompting Strategies in Extracting Labels from Free-Text Radiology Reports with Open-Source Large Language Models 2025 ·Journal of Imaging Informatics in Medicine ·Bardia Khosravi, (unknown), (unknown), (unknown), (unknown), Scot Garg, (unknown), Amir Khosravi, (unknown), Hari Trivedi, Cody C. Wyles, Saptarshi Purkayastha, Bradley J. Erickson, Judy Wawira Gichoya	2
4	Exploring the Impact of 3D Fast Spin Echo and Inversion Recovery Gradient Echo Sequences Magnetic Resonance Imaging Acquisition on Automated Brain Tumor Segmentation 2024 ·SHILAP Revista de lepidopterología ·Mana Moassefi, Shahriar Faghani, (unknown), Gian Marco Conte, Seyed Moein Rassoulinejad-Mousavi, Timothy J. Kaufmann, Bradley J. Erickson	0
5	Study Design Considerations for Generating Real-world Evidence With Digital Biomarkers in Older Adult Populations: Lessons Learned From a Pilot Smartphone Study 2024 ·SSRN Electronic Journal ·(unknown), (unknown), Clinton E. Hagen, Bart M. Demaerschalk, Bradley J. Erickson	1
6	Abdominal Body Composition Reference Ranges and Association With Chronic Conditions in an Age- and Sex-Stratified Representative Sample of a Geographically Defined American Population 2024 ·The Journals of Gerontology Series A ·Alexander D. Weston, Brandon R. Grossardt, Hillary W. Garner, Timothy L. Kline, Alanna M. Chamberlain, Alina M. Allen, Bradley J. Erickson, Walter A. Rocca, Andrew D. Rule, Jennifer L. St. Sauver	5
7	Computed tomography-based radiomics and body composition model for predicting hepatic decompensation 2024 ·Oncotarget ·Yashbir Singh, John E. Eaton, Sudhakar K. Venkatesh, Bradley J. Erickson	0
8	A Systematic Review on the Use of Registration-Based Change Tracking Methods in Longitudinal Radiological Images 2024 ·Journal of Imaging Informatics in Medicine ·J G Im, Mahmoud A. Khalifa, Adriana Gregory, Bradley J. Erickson, Timothy L. Kline	0
9	Comprehensive Segmentation of Gray Matter Structures on T1-Weighted Brain MRI: A Comparative Study of Convolutional Neural Network, Convolutional Neural Network Hybrid-Transformer or -Mamba Architectures 2024 ·American Journal of Neuroradiology ·Yujia Wei, Jaidip Jagtap, Yashbir Singh, (unknown), Jason Cai, Jeffrey L. Gunter, Bradley J. Erickson	4
10	Exploring Remote Monitoring of Poststroke Mood With Digital Sensors by Assessment of Depression Phenotypes and Accelerometer Data in UK Biobank: Cross-Sectional Analysis 2024 ·(unknown), (unknown), Gian Marco Conte, Bart M. Demaerschalk, Bradley J. Erickson	0
11	Topological data analysis in medical imaging: current state of the art 2023 ·Insights into Imaging ·Yashbir Singh, (unknown), Quincy A. Hathaway, Tim Leiner, Jaidip Jagtap, Gunnar Carlsson, Bradley J. Erickson	40
12	The Role of Geometry in Convolutional Neural Networks for Medical Imaging 2023 ·SHILAP Revista de lepidopterología ·Yashbir Singh, (unknown), Quincy A. Hathaway, Ashok Choudhary, Gunnar Carlsson, Bradley J. Erickson, Tim Leiner	10
13	NIMG-57. PERFORMANCE OF DEEP LEARNING IN MGMT PROMOTER METHYLATION STATUS PREDICTION USING BRAIN MRI: RESULTS FROM A LARGE COHORT OF IDH-WILDTYPE GLIOMAS TESTED BY A SINGLE METHYLATION ASSAY 2023 ·Neuro-Oncology ·Gian Marco Conte, Mana Moassefi, Shahriar Faghani, Francesco Sanvito, Paul A. Decker, Sani H. Kizilbash, Jeanette E. Eckel‐Passow, (unknown), Bradley J. Erickson	1
14	Effect of Dataset Size and Medical Image Modality on Convolutional Neural Network Model Performance for Automated Segmentation: A CT and MR Renal Tumor Imaging Study 2023 ·Journal of Digital Imaging ·(unknown), Adriana Gregory, Vidit Sharma, Abhinav Khanna, (unknown), Christine M. Lohse, Theodora A. Potretzke, Panagiotis Korfiatis, Aaron M. Potretzke, Aleksandar Đenić, Andrew D. Rule, Naoki Takahashi, Bradley J. Erickson, Bradley C. Leibovich, Timothy L. Kline	6
15	An Overview of Machine Learning in Orthopedic Surgery: An Educational Paper 2023 ·The Journal of Arthroplasty ·(unknown), (unknown), Diana V. Vera-Garcia, Fred Nugen, Bardia Khosravi, Bradley J. Erickson, Cody C. Wyles, Michael J. Taunton	16
16	Few-shot biomedical image segmentation using diffusion models: Beyond image generation 2023 ·Computer Methods and Programs in Biomedicine ·Bardia Khosravi, Pouria Rouzrokh, (unknown), Shahriar Faghani, (unknown), (unknown), A. Noelle Larson, Benjamin M. Howe, Bradley J. Erickson, Michael J. Taunton, Cody C. Wyles	11
17	Mitigating Bias in Radiology Machine Learning: 1. Data Handling 2022 ·Radiology Artificial Intelligence ·Pouria Rouzrokh, Bardia Khosravi, Shahriar Faghani, Mana Moassefi, Diana V. Vera-Garcia, Yashbir Singh, (unknown), Gian Marco Conte, Bradley J. Erickson	81
18	Getting More Out of Large Databases and EHRs with Natural Language Processing and Artificial Intelligence 2022 ·Journal of Bone and Joint Surgery ·Bardia Khosravi, Pouria Rouzrokh, Bradley J. Erickson	9
19	Deep Learning Artificial Intelligence Model for Assessment of Hip Dislocation Risk Following Primary Total Hip Arthroplasty From Postoperative Radiographs 2021 ·The Journal of Arthroplasty ·Pouria Rouzrokh, Taghi Ramazanian, Cody C. Wyles, Kenneth A. Philbrick, Jason Cai, Michael J. Taunton, Hilal Maradit Kremers, David G. Lewallen, Bradley J. Erickson	48
20	Automatic Measurement of Kidney and Liver Volumes from MR Images of Patients Affected by Autosomal Dominant Polycystic Kidney Disease 2019 ·Journal of the American Society of Nephrology ·Maatje D.A. van Gastel, Marie E. Edwards, Vicente E. Torres, Bradley J. Erickson, Ron T. Gansevoort, Timothy L. Kline	68

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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