Luke Macyszyn

According to our database, Luke Macyszyn authored at least 14 papers between 2016 and 2023.

Collaborative distances:

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

2023

Segmentation and identification of fatty infiltration of the erector spinae using deep learning.

Anshul Ratnaparkhi, Bilwaj Gaonkar, Azim Laiwalla, Elliot Berdy, Matiar Jafari, Abhinav Suri, David Zarrin, Kirstin Cook, Bayard Wilson, Luke Macyszyn, Joel Beckett

Proceedings of the Medical Imaging 2023: Image Processing, 2023

2022

A deep network ensemble for segmentation of cervical spinal cord and neural foramina.

David Zarrin, Anshul Ratnaparkhi, Bayard Wilson, Kirstin Cook, Ien Li, Azim Laiwalla, Mark Attiah, Joel Beckett, Bilwaj Gaonkar, Luke Macyszyn

Proceedings of the Medical Imaging 2022: Computer-Aided Diagnosis, 2022

Ensembling mitigates scanner effects in deep learning medical image segmentation with deep-U-Nets.

Anshul Ratnaparkhi, Bilwaj Gaonkar, David Zarrin, Ien Li, Kirstin Cook, Azim Laiwalla, Bayard Wilson, Mark Attiah, Christine S. Ahn, Diane Villaroman, Bryan Yoo, Banafsheh Salehi, Joel Beckett, Luke Macyszyn

Proceedings of the Medical Imaging 2022: Computer-Aided Diagnosis, 2022

2021

Eigenrank by committee: Von-Neumann entropy based data subset selection and failure prediction for deep learning based medical image segmentation.

Bilwaj Gaonkar, Joel Beckett, Mark Attiah, Christine S. Ahn, Matthew Edwards, Bayard Wilson, Azim Laiwalla, Banafsheh Salehi, Bryan Yoo, Alex A. T. Bui, Luke Macyszyn

Medical Image Anal., 2021

Multi-resolution deep network ensembles for cervical intervertebral disc segmentation are biased by trainer.

Ien Li, Kirstin Cook, Michael Le, Bilwaj Gaonkar, Luke Macyszyn

Proceedings of the Medical Imaging 2021: Computer-Aided Diagnosis, 2021

2019

EigenRank by Committee: A Data Subset Selection and Failure Prediction paradigm for Robust Deep Learning based Medical Image Segmentation.

Bilwaj Gaonkar, Alex A. T. Bui, Luke Macyszyn

CoRR, 2019

2018

Extreme Augmentation : Can deep learning based medical image segmentation be trained using a single manually delineated scan?

Bilwaj Gaonkar, Alex A. T. Bui, Matthew Brown, Luke Macyszyn

CoRR, 2018

Orchestral fully convolutional networks for small lesion segmentation in brain MRI.

Botian Xu, Yaqiong Chai, Cristina M. Galarza, Chau Q. Vu, Benita Tamrazi, Bilwaj Gaonkar, Luke Macyszyn, Thomas D. Coates Jr., Natasha Leporé, John C. Wood

Proceedings of the 15th IEEE International Symposium on Biomedical Imaging, 2018

A deep learning approach to spine segmentation using a feed-forward chain of pixel-wise convolutional networks.

William Whitehead, Steven Moran, Bilwaj Gaonkar, Luke Macyszyn, Subramanian S. Iyer

Proceedings of the 15th IEEE International Symposium on Biomedical Imaging, 2018

Cell Counting and Segmentation of Immunohistochemical Images in the Spinal Cord: Comparing Deep Learning and Traditional Approaches.

Bau Pham, Bilwaj Gaonkar, William Whitehead, Steven Moran, Qing Dai, Luke Macyszyn, V. Reggie Edgerton

Proceedings of the 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2018

2017

Bayesian automated cortical segmentation for neonatal MRI.

Zane Chou, Natacha Paquette, Bhavana Ganesh, Yalin Wang, Rafael Ceschin, Marvin D. Nelson, Luke Macyszyn, Bilwaj Gaonkar, Ashok Panigrahy, Natasha Leporé

Proceedings of the 13th International Symposium on Medical Information Processing and Analysis, 2017

Automatic vertebral bodies detection of x-ray images using invariant multiscale template matching.

Mona Sharifi Sarabi, Diane Villaroman, Joel Beckett, Mark Attiah, Logan Marcus, Christine S. Ahn, Diana Babayan, Bilwaj Gaonkar, Luke Macyszyn, Cauligi S. Raghavendra

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

Automatic segmentation of lumbar vertebrae in CT images.

Amruta Kulkarni, Akshita Raina, Mona Sharifi Sarabi, Christine S. Ahn, Diana Babayan, Bilwaj Gaonkar, Luke Macyszyn, Cauligi S. Raghavendra

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

2016

Deep learning in the small sample size setting: cascaded feed forward neural networks for medical image segmentation.

Bilwaj Gaonkar, David Hovda, Neil Martin, Luke Macyszyn

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