Robert D. Boutin

According to our database, Robert D. Boutin authored at least 11 papers between 2018 and 2024.

Collaborative distances:

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

2024

Detecting Underdiagnosed Medical Conditions with Deep Learning-Based Opportunistic CT Imaging.

Asad Aali, Andrew Johnston, Louis Blankemeier, Dave Van Veen, Laura T. Derry, David Svec, Jason Hom, Robert D. Boutin, Akshay S. Chaudhari

CoRR, 2024

Merlin: A Vision Language Foundation Model for 3D Computed Tomography.

Louis Blankemeier, Joseph Paul Cohen, Ashwin Kumar, Dave Van Veen, Syed Jamal Safdar Gardezi, Magdalini Paschali, Zhihong Chen, Jean-Benoit Delbrouck, Eduardo Pontes Reis, Cesar Truyts, Christian Bluethgen, Malte Engmann Kjeldskov Jensen, Sophie Ostmeier, Maya Varma, Jeya Maria Jose Valanarasu, Zhongnan Fang, Zepeng Huo, Zaid Nabulsi, Diego Ardila, Wei-Hung Weng, Edson Amaro Júnior, Neera Ahuja, Jason Alan Fries, Nigam H. Shah, Andrew Johnston, Robert D. Boutin, Andrew Wentland, Curtis P. Langlotz, Jason Hom, Sergios Gatidis, Akshay S. Chaudhari

CoRR, 2024

2023

Comp2Comp: Open-Source Body Composition Assessment on Computed Tomography.

Louis Blankemeier, Arjun D. Desai, Juan Manuel Zambrano Chaves, Andrew Wentland, Sally Yao, Eduardo Pontes Reis, Malte E. K. Jensen, Bhanushree Bahl, Khushboo Arora, Bhavik N. Patel, Leon Lenchik, Marc H. Willis, Robert D. Boutin, Akshay S. Chaudhari

CoRR, 2023

2022

Artificial Intelligence System for Automatic Quantitative Analysis and Radiology Reporting of Leg Length Radiographs.

Nathan Larson, Chantal Nguyen, Bao H. Do, Aryan Kaul, Anna Larson, Shannon Wang, Erin Wang, Eric Bultman, Kate Stevens, Jason Pai, Audrey Ha, Robert Boutin, Michael Fredericson, Long Do, Charles X. Fang

J. Digit. Imaging, 2022

Scale-Agnostic Super-Resolution in MRI using Feature-Based Coordinate Networks.

Dave Van Veen, Rogier van der Sluijs, Batu Ozturkler, Arjun D. Desai, Christian Bluethgen, Robert D. Boutin, Marc H. Willis, Gordon Wetzstein, David B. Lindell, Shreyas Vasanawala, John M. Pauly, Akshay S. Chaudhari

CoRR, 2022

Data-Limited Tissue Segmentation using Inpainting-Based Self-Supervised Learning.

Jeffrey Dominic, Nandita Bhaskhar, Arjun D. Desai, Andrew M. Schmidt, Elka B. Rubin, Beliz Gunel, Garry E. Gold, Brian A. Hargreaves, Leon Lenchik, Robert Boutin, Akshay S. Chaudhari

CoRR, 2022

Opportunistic Incidence Prediction of Multiple Chronic Diseases from Abdominal CT Imaging Using Multi-task Learning.

Louis Blankemeier, Isabel Gallegos, Juan Manuel Zambrano Chaves, David J. Maron, Alexander T. Sandhu, Fátima Rodriguez, Daniel L. Rubin, Bhavik N. Patel, Marc H. Willis, Robert D. Boutin, Akshay S. Chaudhari

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

2021

SKM-TEA: A Dataset for Accelerated MRI Reconstruction with Dense Image Labels for Quantitative Clinical Evaluation.

Arjun D. Desai, Andrew M. Schmidt, Elka B. Rubin, Christopher M. Sandino, Marianne S. Black, Valentina Mazzoli, Kathryn J. Stevens, Robert Boutin, Christopher Ré, Garry Gold, Brian A. Hargreaves, Akshay Chaudhari

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

Genetic Algorithm based L4 Identification and Psoas Segmentation.

Namitha V. Benjamin, Robert D. Boutin, Abhijit J. Chaudhari, Kwan-Liu Ma

Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies, 2021

2020

Abdominal muscle segmentation from CT using a convolutional neural network.

Ka'Toria Edwards, Avneesh Chhabra, James D. Dormer, Phillip Jones, Robert D. Boutin, Leon Lenchik, Baowei Fei

Proceedings of the Medical Imaging 2020: Biomedical Applications in Molecular, 2020

2018

WRIST: A WRist Image Segmentation Toolkit for carpal bone delineation from MRI.

Brent Foster, Anand A. Joshi, Marissa Borgese, Yasser Abdelhafez, Robert D. Boutin, Abhijit J. Chaudhari

Comput. Medical Imaging Graph., 2018