Nathan Lay

According to our database, Nathan Lay authored at least 19 papers between 2010 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Using YOLO v7 to Detect Kidney in Magnetic Resonance Imaging.

Pouria Yazdian Anari, Fiona Obiezu, Nathan Lay, Fatemeh Dehghani Firouzabadi, Aditi Chaurasia, Mahshid Golagha, Shiva Singh, Fatemeh Homayounieh, Aryan Zahergivar, Stephanie A. Harmon, Evrim Turkbey, Rabindra Gautam, Kevin C. Ma, María Merino, Elizabeth C. Jones, Mark W. Ball, W. Marston Linehan, Baris Turkbey, Ashkan A. Malayeri

CoRR, 2024

2021

Deep Learning Based Staging of Bone Lesions From Computed Tomography Scans.

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, Ulas Bagci, Peter L. Choyke, Baris Turkbey

IEEE Access, 2021

No-Reference Image Quality Assessment Of T2-Weighted Magnetic Resonance Images In Prostate Cancer Patients.

Samira Masoudi, Stephanie A. Harmon, Sherif Mehralivand, Nathan Lay, Ulas Bagci, Bradford J. Wood, Peter A. Pinto, Peter L. Choyke, Baris Turkbey

Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021

2018

Spatial aggregation of holistically-nested convolutional neural networks for automated pancreas localization and segmentation.

Holger R. Roth, Le Lu, Nathan Lay, Adam P. Harrison, Amal Farag, Andrew Sohn, Ronald M. Summers

Medical Image Anal., 2018

Random Hinge Forest for Differentiable Learning.

Nathan Lay, Adam P. Harrison, Sharon Schreiber, Gitesh Dawer, Adrian Barbu

CoRR, 2018

A Decomposable Model for the Detection of Prostate Cancer in Multi-parametric MRI.

Nathan Lay, Yohannes Tsehay, Yohan Sumathipala, Ruida Cheng, Sonia Gaur, Clayton Smith, Adrian Barbu, Le Lu, Baris Turkbey, Peter L. Choyke, Peter A. Pinto, Ronald M. Summers

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018

2017

Automatic MR prostate segmentation by deep learning with holistically-nested networks.

Ruida Cheng, Holger R. Roth, Nathan Lay, Le Lu, Baris Turkbey, William Gandler, Evan S. McCreedy, Peter L. Choyke, Ronald M. Summers, Matthew J. McAuliffe

Proceedings of the Medical Imaging 2017: Image Processing, 2017

Convolutional neural network based deep-learning architecture for prostate cancer detection on multiparametric magnetic resonance images.

Yohannes K. Tsehay, Nathan S. Lay, Holger R. Roth, Xiaosong Wang, Jin Tae Kwak, Baris Turkbey, Peter A. Pinto, Bradford J. Wood, Ronald M. Summers

Proceedings of the Medical Imaging 2017: Computer-Aided Diagnosis, 2017

Texture analysis of common renal masses in multiple MR sequences for prediction of pathology.

Uyen N. Hoang, Ashkan A. Malayeri, Nathan S. Lay, Ronald M. Summers, Jianhua Yao

Proceedings of the Medical Imaging 2017: Computer-Aided Diagnosis, 2017

Biopsy-guided learning with deep convolutional neural networks for Prostate Cancer detection on multiparametric MRI.

Yohannes Tsehay, Nathan Lay, Xiaosong Wang, Jin Tae Kwak, Baris Turkbey, Peter L. Choyke, Peter A. Pinto, Bradford J. Wood, Ronald M. Summers

Proceedings of the 14th IEEE International Symposium on Biomedical Imaging, 2017

Deep learning with orthogonal volumetric HED segmentation and 3D surface reconstruction model of prostate MRI.

Ruida Cheng, Nathan Lay, Francesca Mertan, Baris Turkbey, Holger R. Roth, Le Lu, William Gandler, Evan S. McCreedy, Thomas Pohida, Peter L. Choyke, Matthew J. McAuliffe, Ronald M. Summers

Proceedings of the 14th IEEE International Symposium on Biomedical Imaging, 2017

2016

Accurate 3D bone segmentation in challenging CT images: Bottom-up parsing and contextualized optimization.

Le Lu, Dijia Wu, Nathan Lay, David Liu, Isabella Nogues, Ronald M. Summers

Proceedings of the 2016 IEEE Winter Conference on Applications of Computer Vision, 2016

Automatic Lymph Node Cluster Segmentation Using Holistically-Nested Neural Networks and Structured Optimization in CT Images.

Isabella Nogues, Le Lu, Xiaosong Wang, Holger Roth, Gedas Bertasius, Nathan Lay, Jianbo Shi, Yohannes Tsehay, Ronald M. Summers

Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016, 2016

Colitis detection on abdominal CT scans by rich feature hierarchies.

Jiamin Liu, Nathan Lay, Zhuoshi Wei, Le Lu, Lauren Kim, Evrim Turkbey, Ronald M. Summers

Proceedings of the Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, California, United States, 27 February, 2016

Detection of benign prostatic hyperplasia nodules in T2W MR images using fuzzy decision forest.

Nathan Lay, Sabrina Freeman, Baris Turkbey, Ronald M. Summers

Proceedings of the Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, California, United States, 27 February, 2016

2013

Rapid Multi-organ Segmentation Using Context Integration and Discriminative Models.

Nathan Lay, Neil Birkbeck, Jingdan Zhang, Shaohua Kevin Zhou

Proceedings of the Information Processing in Medical Imaging, 2013

2012

An introduction to artificial prediction markets for classification.

Adrian Barbu, Nathan Lay

J. Mach. Learn. Res., 2012

2010

A systematic study of efficient sampling methods to quantify uncertainty in crack propagation and the Burgers equation.

Edwin Jimenez, Nathan Lay, M. Yousuff Hussaini

Monte Carlo Methods Appl., 2010

Supervised Aggregation of Classifiers using Artificial Prediction Markets.

Nathan Lay, Adrian Barbu

Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010