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2020 – today
- 2023
[c23]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
- [c22]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 - [c21]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
- [j5]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) - [c20]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
- [c19]Saman Sargolzaei, Yan Cai, Stephanie M. Wolahan, Bilwaj Gaonkar, Arman Sargolzaei, Christopher C. Giza, Neil G. Harris:
A Comparative Study of Automatic Approaches for Preclinical MRI-based Brain Segmentation in the Developing Rat. EMBC 2018: 652-655 - [c18]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 - [c17]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 - [c16]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
- [c15]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 - [c14]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 - [c13]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
- [j4]Kristin A. Linn, Bilwaj Gaonkar, Theodore D. Satterthwaite, Jimit Doshi, Christos Davatzikos, Russell T. Shinohara:
Control-group feature normalization for multivariate pattern analysis of structural MRI data using the support vector machine. NeuroImage 132: 157-166 (2016) - [j3]Aoyan Dong, Nicolas Honnorat, Bilwaj Gaonkar, Christos Davatzikos:
CHIMERA: Clustering of Heterogeneous Disease Effects via Distribution Matching of Imaging Patterns. IEEE Trans. Medical Imaging 35(2): 612-621 (2016) - [c12]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 - 2015
- [j2]Bilwaj Gaonkar, Russell T. Shinohara, Christos Davatzikos:
Interpreting support vector machine models for multivariate group wise analysis in neuroimaging. Medical Image Anal. 24(1): 190-204 (2015) - [c11]Ning Yu, Jia Wu, Susan P. Weinstein, Bilwaj Gaonkar, Brad M. Keller, Ahmed Bilal Ashraf, YunQing Jiang, Christos Davatzikos, Emily F. Conant, Despina Kontos:
A superpixel-based framework for automatic tumor segmentation on breast DCE-MRI. Medical Imaging: Computer-Aided Diagnosis 2015: 94140O - [c10]Spyridon Bakas, Ke Zeng, Aristeidis Sotiras, Saima Rathore, Hamed Akbari, Bilwaj Gaonkar, Martin Rozycki, Sarthak Pati, Christos Davatzikos:
GLISTRboost: Combining Multimodal MRI Segmentation, Registration, and Biophysical Tumor Growth Modeling with Gradient Boosting Machines for Glioma Segmentation. Brainles@MICCAI 2015: 144-155 - 2014
- [c9]Bilwaj Gaonkar, Shu Liao, Gerardo Hermosillo, Yiqiang Zhan:
Adaptive geodesic transform for segmentation of vertebrae on CT images. Medical Imaging: Computer-Aided Diagnosis 2014: 903516 - 2013
- [j1]Bilwaj Gaonkar, Christos Davatzikos:
Analytic estimation of statistical significance maps for support vector machine based multi-variate image analysis and classification. NeuroImage 78: 270-283 (2013) - [c8]Erdem Varol, Bilwaj Gaonkar, Christos Davatzikos:
Classifying medical images using morphological appearance manifolds. ISBI 2013: 744-747 - [c7]Bilwaj Gaonkar, Aristeidis Sotiras, Christos Davatzikos:
Deriving Statistical Significance Maps for Support Vector Regression Using Medical Imaging Data. PRNI 2013: 13-16 - 2012
- [c6]Erdem Varol, Bilwaj Gaonkar, Güray Erus, Robert Schultz, Christos Davatzikos:
Feature ranking based nested support vector machine ensemble for medical image classification. ISBI 2012: 146-149 - [c5]Bilwaj Gaonkar, Christos Davatzikos:
Deriving Statistical Significance Maps for SVM Based Image Classification and Group Comparisons. MICCAI (1) 2012: 723-730 - [c4]Roman Filipovych, Bilwaj Gaonkar, Christos Davatzikos:
A Composite Multivariate Polygenic and Neuroimaging Score for Prediction of Conversion to Alzheimer's Disease. PRNI 2012: 105-108 - 2011
- [c3]Bilwaj Gaonkar, Güray Erus, Kilian M. Pohl, Manoj Tanwar, Stefan Margiewicz, R. Nick Bryan, Christos Davatzikos:
Automated segmentation of cortical necrosis using awavelet based abnormality detection system. ISBI 2011: 1391-1395 - [c2]Bilwaj Gaonkar, Kilian M. Pohl, Christos Davatzikos:
Pattern Based Morphometry. MICCAI (2) 2011: 459-466 - 2010
- [c1]Bilwaj Gaonkar, Güray Erus, R. Nick Bryan, Christos Davatzikos:
Automated segmentation of brain lesions by combining intensity and spatial information. ISBI 2010: 93-96
Coauthor Index
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