Nathan Lay

2.0k citations

50 papers · 1.2k indexed · h-index 18

Impact in

Health Informatics top 2%
Radiology, Nuclear Medicine and Imaging top 2%
- Radiomics and Machine Learning in Medical Imaging
- MRI in cancer diagnosis

Papers in ⓘ

Pulmonary and Respiratory Medicine 30
- Prostate Cancer Diagnosis and Treatment 23
- Prostate Cancer Treatment and Research 10
- Renal cell carcinoma treatment 7
Radiology, Nuclear Medicine and Imaging 29
- Radiomics and Machine Learning in Medical Imaging 23
- MRI in cancer diagnosis 11

Co-authors: Ronald M. Summers (16 shared papers)Barış Türkbey (33 shared papers)Peter A. Pinto (23 shared papers)Holger R. Roth (9 shared papers)Peter L. Choyke (29 shared papers)Bradford J. Wood (23 shared papers)Le Lü (6 shared papers)Amal Farag (1 shared paper)
Journals: Abdominal Radiology (6 papers)Academic Radiology (4 papers)American Journal of Roentgenology (3 papers)Journal of Magnetic Resonance Imaging (2 papers)The Journal of Urology (2 papers)
Partner nations: United States Singapore United Kingdom

In The Last Decade

Nathan Lay

49 papers receiving 1.2k citations

Peers

Countries citing papers authored by Nathan Lay

Since Specialization

Citations

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

Fields of papers citing papers by Nathan Lay

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nathan Lay. 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 Nathan Lay. The network helps show where Nathan Lay may publish in the future.

Co-authors

The 25 scholars most cited alongside Nathan Lay, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Nathan Lay Line = papers co-authored together Nathan Lay links everyone, so they are left out of the graph.

All Works

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20 of 20 papers shown

Showing the 20 most-cited of 50 papers — load more, or switch the sort, to bring in the rest.

#	Work
1	Spatial aggregation of holistically-nested convolutional neural networks for automated pancreas localization and segmentation Medical Image Analysis ·Holger R. Roth, Le Lü, Nathan Lay, Adam P. Harrison, Amal Farag, Andrew Sohn, Ronald M. Summers	2018	229
2	Validation of the Dominant Sequence Paradigm and Role of Dynamic Contrast-enhanced Imaging in PI-RADS Version 2 Radiology ·Matthew D. Greer, Joanna H. Shih, Nathan Lay, Tristan Barrett, Leonardo Kayat Bittencourt, Samuel Borofsky, Ismail Kabakus, Yan Mee Law, Jamie Marko, Haytham Shebel, Francesca Mertan, Maria J. Merino, Bradford J. Wood, Peter A. Pinto, Ronald M. Summers, Peter L. Choyke, Barış Türkbey	2017	123
3	Interreader Variability of Prostate Imaging Reporting and Data System Version 2 in Detecting and Assessing Prostate Cancer Lesions at Prostate MRI American Journal of Roentgenology ·Matthew D. Greer, Joanna H. Shih, Nathan Lay, Tristan Barrett, Leonardo Kayat Bittencourt, Samuel Borofsky, Ismail Kabakus, Yan Mee Law, Jamie Marko, Haytham Shebel, Maria J. Merino, Bradford J. Wood, Peter A. Pinto, Ronald M. Summers, Peter L. Choyke, Barış Türkbey	2019	92
4	Computer-aided diagnosis prior to conventional interpretation of prostate mpMRI: an international multi-reader study European Radiology ·Matthew D. Greer, Nathan Lay, Joanna H. Shih, Tristan Barrett, Leonardo Kayat Bittencourt, Samuel Borofsky, Ismail Kabakus, Yan Mee Law, Jamie Marko, Haytham Shebel, Francesca Mertan, Maria J. Merino, Bradford J. Wood, Peter A. Pinto, Ronald M. Summers, Peter L. Choyke, Barış Türkbey	2018	73
5	Population-based opportunistic osteoporosis screening: Validation of a fully automated CT tool for assessing longitudinal BMD changes British Journal of Radiology ·Perry J. Pickhardt, Scott Lee, Jiamin Liu, Jianhua Yao, Nathan Lay, Peter M. Graffy, Ronald M. Summers	2018	65
6	Quality of Prostate MRI: Is the PI-RADS Standard Sufficient? Academic Radiology ·Jonathan Sackett, Joanna H. Shih, Sarah E. Reese, Jeffrey Brender, Stephanie A. Harmon, Tristan Barrett, Mehmet Coşkun, Manuel Madariaga, Jamie Marko, Yan Mee Law, Evrim Türkbey, Sherif Mehralivand, Thomas Sanford, Nathan Lay, Peter A. Pinto, Bradford J. Wood, Peter L. Choyke, Barış Türkbey	2020	56
7	Automatic magnetic resonance prostate segmentation by deep learning with holistically nested networks Journal of Medical Imaging ·Ruida Cheng, Holger R. Roth, Nathan Lay, Le Lü, Barış Türkbey, William Gandler, Evan McCreedy, Tom Pohida, Peter A. Pinto, Peter L. Choyke, Matthew McAuliffe, Ronald M. Summers	2017	55
8	Convolutional neural network based deep-learning architecture for prostate cancer detection on multiparametric magnetic resonance images Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE ·Yohannes Tsehay, Nathan Lay, Holger R. Roth, Xiaosong Wang, Jin Tae Kwak, Baris I. Turkbey, Peter A. Pinto, Bradford J. Wood, Ronald M. Summers	2017	53
9	A Cascaded Deep Learning–Based Artificial Intelligence Algorithm for Automated Lesion Detection and Classification on Biparametric Prostate Magnetic Resonance Imaging Academic Radiology ·Sherif Mehralivand, Dong Yang, Stephanie A. Harmon, Daguang Xu, Ziyue Xu, Holger R. Roth, Samira Masoudi, Thomas Sanford, Deepak Kesani, Nathan Lay, Maria J. Merino, Bradford J. Wood, Peter A. Pinto, Peter L. Choyke, Barış Türkbey	2021	48
10	Prostate cancer detection from multi-institution multiparametric MRIs using deep convolutional neural networks Journal of Medical Imaging ·Yohan Sumathipala, Nathan Lay, Barış Türkbey	2018	47
11	Rapid Multi-organ Segmentation Using Context Integration and Discriminative Models Lecture notes in computer science ·Nathan Lay, Neil Birkbeck, Jingdan Zhang, S. Kevin Zhou	2013	43
12	Detection of prostate cancer in multiparametric MRI using random forest with instance weighting Journal of Medical Imaging ·Nathan Lay, Yohannes Tsehay, Matthew D. Greer, Barış Türkbey, Jin Tae Kwak, Peter L. Choyke, Peter A. Pinto, Bradford J. Wood, Ronald M. Summers	2017	42
13	An Improved Sharp Interface Method for Viscoelastic and Viscous Two-Phase Flows Journal of Scientific Computing ·P. A. Stewart, Nathan Lay, Mark Sussman, Mitsuhiro Ohta	2007	41
14	Deep learning-based artificial intelligence for prostate cancer detection at biparametric MRI Abdominal Radiology ·Sherif Mehralivand, Dong Yang, Stephanie A. Harmon, Daguang Xu, Ziyue Xu, Holger R. Roth, Samira Masoudi, Deepak Kesani, Nathan Lay, Maria J. Merino, Bradford J. Wood, Peter A. Pinto, Peter L. Choyke, Barış Türkbey	2022	29
15	Biopsy-guided learning with deep convolutional neural networks for Prostate Cancer detection on multiparametric MRI Yohannes Tsehay, Nathan Lay, Xiaosong Wang, Jin Tae Kwak, Barış Türkbey, Peter L. Choyke, Peter A. Pinto, Bradford J. Wood, Ronald M. Summers	2017	28
16	Deep Learning Based Staging of Bone Lesions From Computed Tomography Scans IEEE Access ·Samira Masoudi, Sherif Mehralivand, Stephanie A. Harmon, Nathan Lay, Liza Lindenberg, Esther Mena, Peter A. Pinto, Deborah E. Citrin, James L. Gulley, Bradford J. Wood, William L. Dahut, Ravi A. Madan, Ulaş Bağcı, Peter L. Choyke, Barış Türkbey	2021	22
17	Fully automated prostate whole gland and central gland segmentation on MRI using holistically nested networks with short connections Journal of Medical Imaging ·Ruida Cheng, Nathan Lay, Holger R. Roth, Barış Türkbey, Dakai Jin, William Gandler, Evan McCreedy, Tom Pohida, Peter A. Pinto, Peter L. Choyke, Matthew McAuliffe, Ronald M. Summers	2019	18
18	Deep learning with orthogonal volumetric HED segmentation and 3D surface reconstruction model of prostate MRI Ruida Cheng, Nathan Lay, Francesca Mertan, Barış Türkbey, Holger R. Roth, Le Lü, William Gandler, Evan McCreedy, Thomas J. Pohida, Peter L. Choyke, Matthew McAuliffe, Ronald M. Summers	2017	17
19	The Low Rate of Adherence to Checklist for Artificial Intelligence in Medical Imaging Criteria Among Published Prostate MRI Artificial Intelligence Algorithms Journal of the American College of Radiology ·Mason J. Belue, Stephanie A. Harmon, Nathan Lay, Asha Daryanani, Tim E. Phelps, Peter L. Choyke, Barış Türkbey	2022	16
20	Artificial Intelligence-based Tumor Segmentation in Mouse Models of Lung Adenocarcinoma Journal of Pathology Informatics ·Alena Arlova, Chengcheng Jin, Abigail Wong-Rolle, Eric Chen, Curtis Lisle, Gavin Brown, Nathan Lay, Peter L. Choyke, Barış Türkbey, Stephanie A. Harmon, Chen Zhao	2022	12

About Nathan Lay

Nathan Lay is a scholar working on Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Biomedical Engineering and Artificial Intelligence, having authored 50 papers that have together received 1.2k indexed citations. Recurring topics across this work include Prostate Cancer Diagnosis and Treatment (23 papers), Radiomics and Machine Learning in Medical Imaging (23 papers), MRI in cancer diagnosis (11 papers), Prostate Cancer Treatment and Research (10 papers), Advanced Neural Network Applications (9 papers), AI in cancer detection (7 papers), Renal cell carcinoma treatment (7 papers) and Medical Image Segmentation Techniques (6 papers). The work is most often cited by research in Health Informatics (66 citations), Radiology, Nuclear Medicine and Imaging (747 citations), Pulmonary and Respiratory Medicine (633 citations), Computer Vision and Pattern Recognition (302 citations) and Artificial Intelligence (262 citations). Nathan Lay has collaborated with scholars based in United States, Singapore and United Kingdom. Frequent co-authors include Ronald M. Summers, Barış Türkbey, Peter A. Pinto, Holger R. Roth, Peter L. Choyke, Bradford J. Wood, Le Lü, Amal Farag, Adam P. Harrison and Andrew Sohn. Their work appears in journals such as Abdominal Radiology, Academic Radiology, American Journal of Roentgenology, Journal of Magnetic Resonance Imaging and The Journal of Urology.

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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