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Gagandeep Singh
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Publications
- 2023
- [i14]Zilinghan Li, Pranshu Chaturvedi, Shilan He, Han Chen, Gagandeep Singh, Volodymyr V. Kindratenko, E. A. Huerta, Kibaek Kim, Ravi K. Madduri:
FedCompass: Efficient Cross-Silo Federated Learning on Heterogeneous Client Devices using a Computing Power Aware Scheduler. CoRR abs/2309.14675 (2023) - 2022
- [j16]Marwa Ismail, Prateek Prasanna, Kaustav Bera, Volodymyr Statsevych, Virginia B. Hill, Gagandeep Singh, Sasan Partovi, Niha G. Beig, Sean D. McGarry, Peter S. LaViolette, Manmeet Ahluwalia, Anant Madabhushi, Pallavi Tiwari:
Radiomic Deformation and Textural Heterogeneity (R-DepTH) Descriptor to Characterize Tumor Field Effect: Application to Survival Prediction in Glioblastoma. IEEE Trans. Medical Imaging 41(7): 1764-1777 (2022) - [c24]Saumya Gupta, Xiaoling Hu, James Kaan, Michael Jin, Mutshipay Mpoy, Katherine Chung, Gagandeep Singh, Mary M. Saltz, Tahsin M. Kurç, Joel H. Saltz, Apostolos Tassiopoulos, Prateek Prasanna, Chao Chen:
Learning Topological Interactions for Multi-Class Medical Image Segmentation. ECCV (29) 2022: 701-718 - [i12]Lei Zhou, Joseph Bae, Huidong Liu, Gagandeep Singh, Jeremy Green, Amit Gupta, Dimitris Samaras, Prateek Prasanna:
Lung Swapping Autoencoder: Learning a Disentangled Structure-texture Representation of Chest Radiographs. CoRR abs/2201.07344 (2022) - [i11]Saumya Gupta, Xiaoling Hu, James Kaan, Michael Jin, Mutshipay Mpoy, Katherine Chung, Gagandeep Singh, Mary M. Saltz, Tahsin M. Kurç, Joel H. Saltz, Apostolos Tassiopoulos, Prateek Prasanna, Chao Chen:
Learning Topological Interactions for Multi-Class Medical Image Segmentation. CoRR abs/2207.09654 (2022) - 2021
- [c18]Connor Cowan, Joseph Bae, Gagandeep Singh, Rohit Khullar, Shrey Shah, Nikhil Madan, Prateek Prasanna:
Evolution of chest radiograph radiomics and association with respiratory and inflammatory parameters in COVID-19 patients undergoing prone ventilation: preliminary findings. Medical Imaging: Computer-Aided Diagnosis 2021 - [c17]Lei Zhou, Joseph Bae, Huidong Liu, Gagandeep Singh, Jeremy Green, Dimitris Samaras, Prateek Prasanna:
Chest Radiograph Disentanglement for COVID-19 Outcome Prediction. MICCAI (7) 2021: 345-355 - [c16]Sudhir Suman, Gagandeep Singh, Nicole Sakla, Rishabh Gattu, Jeremy Green, Tej Phatak, Dimitris Samaras, Prateek Prasanna:
Attention Based CNN-LSTM Network for Pulmonary Embolism Prediction on Chest Computed Tomography Pulmonary Angiograms. MICCAI (7) 2021: 356-366 - [c15]Aishik Konwer, Joseph Bae, Gagandeep Singh, Rishabh Gattu, Syed Ali, Jeremy Green, Tej Phatak, Prateek Prasanna:
Attention-Based Multi-scale Gated Recurrent Encoder with Novel Correlation Loss for COVID-19 Progression Prediction. MICCAI (5) 2021: 824-833 - [c14]Aishik Konwer, Joseph Bae, Gagandeep Singh, Rishabh Gattu, Syed Ali, Jeremy Green, Tej Phatak, Amit Gupta, Chao Chen, Joel H. Saltz, Prateek Prasanna:
Predicting COVID-19 Lung Infiltrate Progression on Chest Radiographs Using Spatio-temporal LSTM based Encoder-Decoder Network. MIDL 2021: 384-398 - [i8]Marwa Ismail, Prateek Prasanna, Kaustav Bera, Volodymyr Statsevych, Virginia B. Hill, Gagandeep Singh, Sasan Partovi, Niha G. Beig, Sean D. McGarry, Peter S. LaViolette, Manmeet Ahluwalia, Anant Madabhushi, Pallavi Tiwari:
Radiomic Deformation and Textural Heterogeneity (R-DepTH) Descriptor to characterize Tumor Field Effect: Application to Survival Prediction in Glioblastoma. CoRR abs/2103.07423 (2021) - [i6]Sudhir Suman, Gagandeep Singh, Nicole Sakla, Rishabh Gattu, Jeremy Green, Tej Phatak, Dimitris Samaras, Prateek Prasanna:
Attention based CNN-LSTM Network for Pulmonary Embolism Prediction on Chest Computed Tomography Pulmonary Angiograms. CoRR abs/2107.06276 (2021) - [i5]Aishik Konwer, Joseph Bae, Gagandeep Singh, Rishabh Gattu, Syed Ali, Jeremy Green, Tej Phatak, Prateek Prasanna:
Attention-based Multi-scale Gated Recurrent Encoder with Novel Correlation Loss for COVID-19 Progression Prediction. CoRR abs/2107.08330 (2021) - 2020
- [j14]Marwa Ismail, Virginia B. Hill, Volodymyr Statsevych, Evan Mason, Ramon Correa, Prateek Prasanna, Gagandeep Singh, Kaustav Bera, Rajat Thawani, Manmeet Ahluwalia, Anant Madabhushi, Pallavi Tiwari:
Can Tumor Location on Pre-treatment MRI Predict Likelihood of Pseudo-Progression vs. Tumor Recurrence in Glioblastoma? - A Feasibility Study. Frontiers Comput. Neurosci. 14: 563439 (2020) - [i3]Marwa Ismail, Virginia B. Hill, Volodymyr Statsevych, Evan Mason, Ramon Correa, Prateek Prasanna, Gagandeep Singh, Kaustav Bera, Rajat Thawani, Anant Madabhushi, Manmeet Ahluwalia, Pallavi Tiwari:
Can tumor location on pre-treatment MRI predict likelihood of pseudo-progression versus tumor recurrence in Glioblastoma? A feasibility study. CoRR abs/2006.09483 (2020) - [i2]Joseph Bae, Saarthak Kapse, Gagandeep Singh, Tej Phatak, Jeremy Green, Nikhil Madan, Prateek Prasanna:
Predicting Mechanical Ventilation Requirement and Mortality in COVID-19 using Radiomics and Deep Learning on Chest Radiographs: A Multi-Institutional Study. CoRR abs/2007.08028 (2020) - 2017
- [c8]Prateek Prasanna, Jhimli Mitra, Niha G. Beig, Sasan Partovi, Gagandeep Singh, Marco Pinho, Anant Madabhushi, Pallavi Tiwari:
Radiographic-Deformation and Textural Heterogeneity (r-DepTH): An Integrated Descriptor for Brain Tumor Prognosis. MICCAI (2) 2017: 459-467
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