Ronald M. Summers

37.8k total citations · 9 hit papers
501 papers, 18.9k citations indexed

About

Ronald M. Summers is a scholar working on Radiology, Nuclear Medicine and Imaging, Oncology and Computer Vision and Pattern Recognition. According to data from OpenAlex, Ronald M. Summers has authored 501 papers receiving a total of 18.9k indexed citations (citations by other indexed papers that have themselves been cited), including 270 papers in Radiology, Nuclear Medicine and Imaging, 149 papers in Oncology and 141 papers in Computer Vision and Pattern Recognition. Recurrent topics in Ronald M. Summers's work include Radiomics and Machine Learning in Medical Imaging (172 papers), Colorectal Cancer Screening and Detection (132 papers) and AI in cancer detection (90 papers). Ronald M. Summers is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (172 papers), Colorectal Cancer Screening and Detection (132 papers) and AI in cancer detection (90 papers). Ronald M. Summers collaborates with scholars based in United States, United Kingdom and Japan. Ronald M. Summers's co-authors include Jianhua Yao, Le Lü, Holger R. Roth, Hoo-Chang Shin, Daniel J. Mollura, Perry J. Pickhardt, Ziyue Xu, Mingchen Gao, Isabella Nogues and Shijun Wang and has published in prestigious journals such as Circulation, Nature Communications and Gastroenterology.

In The Last Decade

Ronald M. Summers

482 papers receiving 18.4k 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.

Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning

2016 4.0k citations Le Lü, Ronald M. Summers et al. IEEE Transactions on Medical Imaging profile →
Preparing Medical Imaging Data for Machine Learning

2020 553 citations Les Folio, Ronald M. Summers et al. Radiology profile →
Deep learning in medical imaging and radiation therapy

2018 527 citations Ronald M. Summers et al. Medical Physics profile →
Machine learning and radiology

2012 467 citations Ronald M. Summers et al. Medical Image Analysis profile →
Data augmentation using generative adversarial networks (CycleGAN) to improve generalizability in CT segmentation tasks

2019 439 citations Perry J. Pickhardt, Ronald M. Summers et al. Scientific Reports profile →
Improving Computer-Aided Detection UsingConvolutional Neural Networks and Random View Aggregation

2015 417 citations Le Lü, Ronald M. Summers et al. IEEE Transactions on Medical Imaging profile →
DeepLesion: automated mining of large-scale lesion annotations and universal lesion detection with deep learning

2018 292 citations Le Lü, Ronald M. Summers et al. profile →
A New 2.5D Representation for Lymph Node Detection using Random Sets of Deep Convolutional Neural Network Observations

2014 285 citations Le Lü, Ronald M. Summers et al. arXiv (Cornell University) profile →
Opportunistic Osteoporosis Screening at Routine Abdominal and Thoracic CT: Normative L1 Trabecular Attenuation Values in More than 20 000 Adults

2019 217 citations Samuel Jang, Peter M. Graffy et al. Radiology profile →

Peers

Countries citing papers authored by Ronald M. Summers

Since Specialization

Citations

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

Fields of papers citing papers by Ronald M. Summers

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ronald M. Summers. 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 Ronald M. Summers. The network helps show where Ronald M. Summers may publish in the future.

Co-authorship network of co-authors of Ronald M. Summers

This figure shows the co-authorship network connecting the top 25 collaborators of Ronald M. Summers. A scholar is included among the top collaborators of Ronald M. Summers 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 Ronald M. Summers. Ronald M. Summers 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	One Year On: Assessing Progress of Multimodal Large Language Model Performance on RSNA 2024 Case of the Day Questions 2025 ·Radiology ·Benjamin Hou, Pritam Mukherjee, (unknown), Kenneth C. Wang, Ronald M. Summers, Zhiyong Lu	1
2	Biological age model using explainable automated CT-based cardiometabolic biomarkers for phenotypic prediction of longevity 2025 ·Nature Communications ·Perry J. Pickhardt, Michael W. Kattan, Matthew H. Lee, B. Dustin Pooler, Ayis Pyrros, (unknown), Ryan Zea, Ronald M. Summers, John W. Garrett	5
3	Segmentation of pelvic structures in T2 MRI via MR-to-CT synthesis 2024 ·Computerized Medical Imaging and Graphics ·Yan Zhuang, (unknown), Pritam Mukherjee, Ronald M. Summers	3
4	Detection of abdominopelvic lymph nodes in multi-parametric MRI 2024 ·Computerized Medical Imaging and Graphics ·(unknown), Thomas C. Shen, Daniel C. Elton, Sungwon Lee, Zhiyong Lu, Ronald M. Summers	2
5	Correlation of HbA1c levels with CT-based body composition biomarkers in diabetes mellitus and metabolic syndrome 2024 ·Scientific Reports ·Joshua Warner, Glen M. Blake, John W. Garrett, Matthew H. Lee, (unknown), Ronald M. Summers, Perry J. Pickhardt	2
6	Interpretable medical image Visual Question Answering via multi-modal relationship graph learning 2024 ·Medical Image Analysis ·(unknown), Lin Gu, Kazuma Kobayashi, (unknown), (unknown), Tatsuya Harada, Ronald M. Summers, Yingying Zhu	12
7	Weakly supervised detection of pheochromocytomas and paragangliomas in CT using noisy data 2024 ·Computerized Medical Imaging and Graphics ·(unknown), (unknown), (unknown), Pritam Mukherjee, Jianfei Liu, Abhishek Jha, Mayank Patel, Karel Pacák, Ronald M. Summers	0
8	Hidden flaws behind expert-level accuracy of multimodal GPT-4 vision in medicine 2024 ·npj Digital Medicine ·Qiao Jin, Fangyuan Chen, Yiliang Zhou, Ziyang Xu, (unknown), Robert F. Chen, Ronald M. Summers, Justin F. Rousseau, (unknown), Marc Landsman, Sally L. Baxter, Subhi J. Al’Aref, Yijia Li, (unknown), (unknown), Michael F. Chiang, Yifan Peng, Zhiyong Lu	47
9	Evaluation of GPT Large Language Model Performance on RSNA 2023 Case of the Day Questions 2024 ·Radiology ·Pritam Mukherjee, Benjamin Hou, (unknown), Yan Zhuang, (unknown), (unknown), (unknown), Ravi Jain, Kenneth C. Wang, (unknown), Ronald M. Summers	8
10	A New Benchmark: Clinical Uncertainty and Severity Aware Labeled Chest X-Ray Images With Multi-Relationship Graph Learning 2024 ·IEEE Transactions on Medical Imaging ·(unknown), (unknown), Lin Gu, (unknown), Kazuma Kobayashi, Tatsuya Harada, Yan Yan, Ronald M. Summers, Yingying Zhu	1
11	Opportunistic Screening: Radiology Scientific Expert Panel 2023 ·Radiology ·Perry J. Pickhardt, Ronald M. Summers, John W. Garrett, Arun Krishnaraj, Sheela Agarwal, Keith J. Dreyer, Gregory N. Nicola	51
12	Expert Knowledge-Aware Image Difference Graph Representation Learning for Difference-Aware Medical Visual Question Answering 2023 ·arXiv (Cornell University) ·(unknown), Lin Gu, (unknown), (unknown), (unknown), Kazuma Kobayashi, Tatsuya Harada, Ronald M. Summers, Yingying Zhu	14
13	Improved CT-based Osteoporosis Assessment with a Fully Automated Deep Learning Tool 2022 ·Radiology Artificial Intelligence ·Perry J. Pickhardt, (unknown), Alberto A. Perez, Peter M. Graffy, Samuel Jang, Ronald M. Summers, John W. Garrett	43
14	Association between Abdominal CT Measurements of Body Composition before Deceased Donor Liver Transplant with Posttransplant Outcomes 2022 ·Radiology ·Omid Shafaat, Yi Liu, Kyle R. Jackson, Jennifer D. Motter, Brian J. Boyarsky, Muhammad Latif, Frank Yuan, (unknown), Elizabeth A. King, Atif Zaheer, Ronald M. Summers, Dorry L. Segev, Mara McAdams‐DeMarco, Clifford R. Weiss	24
15	Abdominal CT Body Composition Thresholds Using Automated AI Tools for Predicting 10-year Adverse Outcomes 2022 ·Radiology ·Matthew H. Lee, Ryan Zea, John W. Garrett, Peter M. Graffy, Ronald M. Summers, Perry J. Pickhardt	26
16	Deep Learning CT-based Quantitative Visualization Tool for Liver Volume Estimation: Defining Normal and Hepatomegaly 2021 ·Radiology ·Alberto A. Perez, (unknown), Meghan G. Lubner, Peter M. Graffy, John W. Garrett, Daniel C. Elton, Ronald M. Summers, Perry J. Pickhardt	25
17	CT Evaluation of Lymph Nodes That Merge or Split during the Course of a Clinical Trial: Limitations of RECIST 1.1 2021 ·Radiology Imaging Cancer ·(unknown), Mohammadhadi Bagheri, Faraz Farhadi, Andrea B. Apolo, Nadia Biassou, Les Folio, Elizabeth C. Jones, Ronald M. Summers	9
18	Abnormal Chest X-Ray Identification With Generative Adversarial One-Class Classifier 2019 ·Yuxing Tang, Youbao Tang, Mei Han, Jing Xiao, Ronald M. Summers	32
19	Unsupervised body part regression using convolutional neural network with self-organization. 2017 ·arXiv (Cornell University) ·Ke Yan, Le Lü, Ronald M. Summers	3
20	Automated segmentation and quantification of liver and spleen from CT images using normalized probabilistic atlases and enhancement estimation 2010 ·Medical Physics ·Marius George Linguraru, Jesse K. Sandberg, Zhixi Li, (unknown), Ronald M. Summers	100

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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