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2020 – today
- 2023
[c11]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- 2022
- [c10]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 - [c9]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 - 2021
- [j1]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: 101834 (2021) - [c8]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
2010 – 2019
- 2019
- [i2]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 abs/1908.06337 (2019) - 2018
- [c7]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: 842-845 - [c6]William Whitehead, Steven Moran, Bilwaj Gaonkar, Luke Macyszyn, Subramanian S. Iyer:
A deep learning approach to spine segmentation using a feed-forward chain of pixel-wise convolutional networks. ISBI 2018: 868-871 - [c5]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: 889-892 - [i1]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 abs/1810.01621 (2018) - 2017
- [c4]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: 1013447 - [c3]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: 1013448 - [c2]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: 105720R - 2016
- [c1]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: 97852I
Coauthor Index
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