Luke Macyszyn

Publication Activity (10 Years)

Years Active: 2016-2023
Publications (10 Years): 14

Top Topics

Subset Selection

Top Venues

Medical Imaging: Computer-Aided Diagnosis

Medical Image Anal.

Publications

Anshul Ratnaparkhi, Bilwaj Gaonkar, Azim Laiwalla, Elliot Berdy, Matiar Jafari, Abhinav Suri, David Zarrin, Kirstin Cook, Bayard Wilson, Luke Macyszyn, Joel Beckett
Segmentation and identification of fatty infiltration of the erector spinae using deep learning. Medical Imaging: Image Processing (2023)
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
Ensembling mitigates scanner effects in deep learning medical image segmentation with deep-U-Nets. Medical Imaging: Computer-Aided Diagnosis (2022)
David Zarrin, Anshul Ratnaparkhi, Bayard Wilson, Kirstin Cook, Ien Li, Azim Laiwalla, Mark Attiah, Joel Beckett, Bilwaj Gaonkar, Luke Macyszyn
A deep network ensemble for segmentation of cervical spinal cord and neural foramina. Medical Imaging: Computer-Aided Diagnosis (2022)
Ien Li, Kirstin Cook, Michael Le, Bilwaj Gaonkar, Luke Macyszyn
Multi-resolution deep network ensembles for cervical intervertebral disc segmentation are biased by trainer. Medical Imaging: Computer-Aided Diagnosis (2021)
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
Eigenrank by committee: Von-Neumann entropy based data subset selection and failure prediction for deep learning based medical image segmentation. Medical Image Anal. 67 (2021)
Bilwaj Gaonkar, Alex A. T. Bui, Luke Macyszyn
EigenRank by Committee: A Data Subset Selection and Failure Prediction paradigm for Robust Deep Learning based Medical Image Segmentation. CoRR (2019)
Bau Pham, Bilwaj Gaonkar, William Whitehead, Steven Moran, Qing Dai, Luke Macyszyn, V. Reggie Edgerton
Cell Counting and Segmentation of Immunohistochemical Images in the Spinal Cord: Comparing Deep Learning and Traditional Approaches. EMBC (2018)
William Whitehead, Steven Moran, Bilwaj Gaonkar, Luke Macyszyn, Subramanian Iyer
A deep learning approach to spine segmentation using a feed-forward chain of pixel-wise convolutional networks. ISBI (2018)
Bilwaj Gaonkar, Alex A. T. Bui, Matthew Brown, Luke Macyszyn
Extreme Augmentation : Can deep learning based medical image segmentation be trained using a single manually delineated scan? CoRR (2018)
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
Orchestral fully convolutional networks for small lesion segmentation in brain MRI. ISBI (2018)
Amruta Kulkarni, Akshita Raina, Mona Sharifi Sarabi, Christine S. Ahn, Diana Babayan, Bilwaj Gaonkar, Luke Macyszyn, Cauligi S. Raghavendra
Automatic segmentation of lumbar vertebrae in CT images. Medical Imaging: Computer-Aided Diagnosis (2017)
Zane Chou, Natacha Paquette, Bhavana Ganesh, Yalin Wang, Rafael Ceschin, Marvin D. Nelson, Luke Macyszyn, Bilwaj Gaonkar, Ashok Panigrahy, Natasha Leporé
Bayesian automated cortical segmentation for neonatal MRI. SIPAIM (2017)
Mona Sharifi Sarabi, Diane Villaroman, Joel Beckett, Mark Attiah, Logan Marcus, Christine S. Ahn, Diana Babayan, Bilwaj Gaonkar, Luke Macyszyn, Cauligi S. Raghavendra
Automatic vertebral bodies detection of x-ray images using invariant multiscale template matching. Medical Imaging: Computer-Aided Diagnosis (2017)
Bilwaj Gaonkar, David Hovda, Neil Martin, Luke Macyszyn
Deep learning in the small sample size setting: cascaded feed forward neural networks for medical image segmentation. Medical Imaging: Computer-Aided Diagnosis (2016)