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2020 – today
- 2024
[j8]Jennifer Salguero
, Prateek Prasanna, Germán Corredor, Angel Cruz-Roa, David Becerra, Eduardo Romero:
Data distillation in computational pathology by choosing few representants of the original variance: A use case in ovarian cancer. Expert Syst. Appl. 245: 123028 (2024)- [j7]Saarthak Kapse, Srijan Das, Jingwei Zhang, Rajarsi R. Gupta, Joel H. Saltz, Dimitris Samaras, Prateek Prasanna:
Attention De-sparsification Matters: Inducing diversity in digital pathology representation learning. Medical Image Anal. 93: 103070 (2024) - [c56]Alexandros Graikos, Srikar Yellapragada, Minh-Quan Le, Saarthak Kapse, Prateek Prasanna, Joel H. Saltz, Dimitris Samaras:
Learned Representation-Guided Diffusion Models for Large-Image Generation. CVPR 2024: 8532-8542 - [c55]Saarthak Kapse, Pushpak Pati, Srijan Das, Jingwei Zhang, Chao Chen, Maria Vakalopoulou, Joel H. Saltz, Dimitris Samaras, Rajarsi R. Gupta, Prateek Prasanna:
SI-MIL: Taming Deep MIL for Self-Interpretability in Gigapixel Histopathology. CVPR 2024: 11226-11237 - [c54]Paras Goel, Saarthak Kapse, Pushpak Pati, Prateek Prasanna:
Coca-Mil: Attention-Based Handcrafted-Deep Feature Fusion in Computational Pathology. ISBI 2024: 1-5 - [c53]Meiliong Xu, Nate Anderson, Richard M. Levenson, Prateek Prasanna, Chao Chen:
A Topological Comparison of the Fluorescence Imitating Brightfield Imaging and H&E Imaging. TGI3@MICCAI 2024: 122-133 - [c52]Wentao Huang, Xiaoling Hu, Shahira Abousamra, Prateek Prasanna, Chao Chen:
Hard Negative Sample Mining for Whole Slide Image Classification. MICCAI (4) 2024: 144-154 - [c51]Aishik Konwer, Prateek Prasanna:
MetaStain: Stain-Generalizable Meta-learning for Cell Segmentation and Classification with Limited Exemplars. MICCAI (4) 2024: 307-317 - [c50]Joseph Bae, Saarthak Kapse, Lei Zhou, Kartik Mani, Prateek Prasanna:
HoG-Net: Hierarchical Multi-organ Graph Network for Head and Neck Cancer Recurrence Prediction from CT Images. MICCAI (5) 2024: 317-327 - [c49]Mahmudul Hasan, Xiaoling Hu, Shahira Abousamra, Prateek Prasanna, Joel H. Saltz, Chao Chen:
Semi-supervised Contrastive VAE for Disentanglement of Digital Pathology Images. MICCAI (4) 2024: 459-469 - [c48]Srikar Yellapragada, Alexandros Graikos, Prateek Prasanna, Tahsin M. Kurç, Joel H. Saltz, Dimitris Samaras:
PathLDM: Text conditioned Latent Diffusion Model for Histopathology. WACV 2024: 5170-5179 - [i32]Xuan Xu, Saarthak Kapse, Prateek Prasanna:
Histo-Diffusion: A Diffusion Super-Resolution Method for Digital Pathology with Comprehensive Quality Assessment. CoRR abs/2408.15218 (2024) - [i31]Moinak Bhattacharya, Gagandeep Singh, Shubham Jain, Prateek Prasanna:
RadGazeGen: Radiomics and Gaze-guided Medical Image Generation using Diffusion Models. CoRR abs/2410.00307 (2024) - 2023
- [c47]Yunfan Li, Himanshu Gupta, Prateek Prasanna, I. V. Ramakrishnan, Haibin Ling:
Surgical Phase Recognition in Laparoscopic Cholecystectomy. CENTERIS/ProjMAN/HCist 2023: 2006-2012 - [c46]Aishik Konwer, Xiaoling Hu, Joseph Bae, Xuan Xu, Chao Chen, Prateek Prasanna:
Enhancing Modality-Agnostic Representations via Meta-learning for Brain Tumor Segmentation. ICCV 2023: 21358-21368 - [c45]Yunfan Li, Himanshu Gupta, Haibin Ling, I. V. Ramakrishnan, Prateek Prasanna, Georgios Georgakis, Aaron Sasson:
Automated Assessment of Critical View of Safety in Laparoscopic Cholecystectomy. ICHI 2023: 330-337 - [c44]Jiachen Yao, Yikai Zhang, Songzhu Zheng, Mayank Goswami, Prateek Prasanna, Chao Chen:
Learning to Segment from Noisy Annotations: A Spatial Correction Approach. ICLR 2023 - [c43]Lei Zhou, Huidong Liu, Joseph Bae, Junjun He, Dimitris Samaras, Prateek Prasanna:
Token Sparsification for Faster Medical Image Segmentation. IPMI 2023: 743-754 - [c42]Jingwei Zhang, Saarthak Kapse, Ke Ma, Prateek Prasanna, Maria Vakalopoulou, Joel H. Saltz, Dimitris Samaras:
Precise Location Matching Improves Dense Contrastive Learning in Digital Pathology. IPMI 2023: 783-794 - [c41]Saarthak Kapse, Srijan Das, Prateek Prasanna:
CD-Net: Histopathology Representation Learning Using Context-Detail Transformer Network. ISBI 2023: 1-5 - [c40]Lei Zhou, Huidong Liu, Joseph Bae, Junjun He, Dimitris Samaras, Prateek Prasanna:
Self Pre-Training with Masked Autoencoders for Medical Image Classification and Segmentation. ISBI 2023: 1-6 - [c39]Moinak Bhattacharya, Prateek Prasanna:
Audio-visual feature fusion for improved thoracic disease classification. Medical Imaging: Computer-Aided Diagnosis 2023 - [c38]Xuan Xu, Saarthak Kapse, Rajarsi Gupta, Prateek Prasanna:
ViT-DAE: Transformer-Driven Diffusion Autoencoder for Histopathology Image Analysis. DGM4MICCAI 2023: 66-76 - [c37]Jingwei Zhang, Ke Ma, Saarthak Kapse, Joel H. Saltz, Maria Vakalopoulou, Prateek Prasanna, Dimitris Samaras:
SAM-Path: A Segment Anything Model for Semantic Segmentation in Digital Pathology. ISIC/Care-AI/MedAGI/DeCaF@MICCAI 2023: 161-170 - [c36]Jingwei Zhang, Saarthak Kapse, Ke Ma, Prateek Prasanna, Joel H. Saltz, Maria Vakalopoulou, Dimitris Samaras:
Prompt-MIL: Boosting Multi-instance Learning Schemes via Task-Specific Prompt Tuning. MICCAI (8) 2023: 624-634 - [c35]Aishik Konwer, Chao Chen, Prateek Prasanna:
MagNET: Modality-Agnostic Network for Brain Tumor Segmentation and Characterization with Missing Modalities. MLMI@MICCAI (1) 2023: 361-371 - [c34]Saumya Gupta, Yikai Zhang, Xiaoling Hu, Prateek Prasanna, Chao Chen:
Topology-Aware Uncertainty for Image Segmentation. NeurIPS 2023 - [i30]Aishik Konwer, Xiaoling Hu, Xuan Xu, Joseph Bae, Chao Chen, Prateek Prasanna:
Enhancing Modality-Agnostic Representations via Meta-Learning for Brain Tumor Segmentation. CoRR abs/2302.04308 (2023) - [i29]Lei Zhou, Huidong Liu, Joseph Bae, Junjun He, Dimitris Samaras, Prateek Prasanna:
Token Sparsification for Faster Medical Image Segmentation. CoRR abs/2303.06522 (2023) - [i28]Jingwei Zhang, Saarthak Kapse, Ke Ma, Prateek Prasanna, Joel H. Saltz, Maria Vakalopoulou, Dimitris Samaras:
Prompt-MIL: Boosting Multi-Instance Learning Schemes via Task-specific Prompt Tuning. CoRR abs/2303.12214 (2023) - [i27]Xuan Xu, Saarthak Kapse, Rajarsi Gupta, Prateek Prasanna:
ViT-DAE: Transformer-driven Diffusion Autoencoder for Histopathology Image Analysis. CoRR abs/2304.01053 (2023) - [i26]Saumya Gupta, Yikai Zhang, Xiaoling Hu, Prateek Prasanna, Chao Chen:
Topology-Aware Uncertainty for Image Segmentation. CoRR abs/2306.05671 (2023) - [i25]Jingwei Zhang, Ke Ma, Saarthak Kapse, Joel H. Saltz, Maria Vakalopoulou, Prateek Prasanna, Dimitris Samaras:
SAM-Path: A Segment Anything Model for Semantic Segmentation in Digital Pathology. CoRR abs/2307.09570 (2023) - [i24]Jiachen Yao, Yikai Zhang, Songzhu Zheng, Mayank Goswami, Prateek Prasanna, Chao Chen:
Learning to Segment from Noisy Annotations: A Spatial Correction Approach. CoRR abs/2308.02498 (2023) - [i23]Srikar Yellapragada, Alexandros Graikos, Prateek Prasanna, Tahsin M. Kurç, Joel H. Saltz, Dimitris Samaras:
PathLDM: Text conditioned Latent Diffusion Model for Histopathology. CoRR abs/2309.00748 (2023) - [i22]Saarthak Kapse, Srijan Das, Jingwei Zhang, Rajarsi R. Gupta, Joel H. Saltz, Dimitris Samaras, Prateek Prasanna:
Attention De-sparsification Matters: Inducing Diversity in Digital Pathology Representation Learning. CoRR abs/2309.06439 (2023) - [i21]Yunfan Li, Himanshu Gupta, Haibin Ling, I. V. Ramakrishnan, Prateek Prasanna, Georgios Georgakis, Aaron Sasson:
Automated Assessment of Critical View of Safety in Laparoscopic Cholecystectomy. CoRR abs/2309.07330 (2023) - [i20]Alexandros Graikos, Srikar Yellapragada, Minh-Quan Le, Saarthak Kapse, Prateek Prasanna, Joel H. Saltz, Dimitris Samaras:
Learned representation-guided diffusion models for large-image generation. CoRR abs/2312.07330 (2023) - [i19]Saarthak Kapse, Pushpak Pati, Srijan Das, Jingwei Zhang, Chao Chen, Maria Vakalopoulou, Joel H. Saltz, Dimitris Samaras, Rajarsi R. Gupta, Prateek Prasanna:
SI-MIL: Taming Deep MIL for Self-Interpretability in Gigapixel Histopathology. CoRR abs/2312.15010 (2023) - 2022
- [j6]Jacob T. Antunes, Marwa Ismail, Imran Hossain, Zhoumengdi Wang, Prateek Prasanna, Anant Madabhushi, Pallavi Tiwari, Satish E. Viswanath:
RADIomic Spatial TexturAl Descriptor (RADISTAT): Quantifying Spatial Organization of Imaging Heterogeneity Associated With Tumor Response to Treatment. IEEE J. Biomed. Health Informatics 26(6): 2627-2636 (2022) - [j5]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) - [c33]Aishik Konwer, Xuan Xu, Joseph Bae, Chao Chen, Prateek Prasanna:
Temporal Context Matters: Enhancing Single Image Prediction with Disease Progression Representations. CVPR 2022: 18802-18813 - [c32]Moinak Bhattacharya, Shubham Jain, Prateek Prasanna:
RadioTransformer: A Cascaded Global-Focal Transformer for Visual Attention-Guided Disease Classification. ECCV (21) 2022: 679-698 - [c31]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 - [c30]Ibrahim Hammoud, Prateek Prasanna, I. V. Ramakrishnan, Adam Singer, Mark Henry, Henry C. Thode:
EventScore: An Automated Real-time Early Warning Score for Clinical Events. ICHI 2022: 192-200 - [c29]Saarthak Kapse, Luke Torre-Healy, Richard A. Moffitt, Rajarsi Gupta, Prateek Prasanna:
Subtype-Specific Spatial Descriptors of Tumor-Immune Microenvironment are Prognostic of Survival in Lung Adenocarcinoma. ISBI 2022: 1-5 - [c28]Xuan Xu, Prateek Prasanna:
Brain Cancer Survival Prediction on Treatment-Naïve MRI using Deep Anchor Attention Learning with Vision Transformer. ISBI 2022: 1-5 - [c27]Aishik Konwer, Prateek Prasanna:
Clinical outcome prediction in COVID-19 using self-supervised vision transformer representations. Medical Imaging: Computer-Aided Diagnosis 2022 - [c26]Moinak Bhattacharya, Shubham Jain, Prateek Prasanna:
GazeRadar: A Gaze and Radiomics-Guided Disease Localization Framework. MICCAI (3) 2022: 686-696 - [i18]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) - [i17]Xuan Xu, Prateek Prasanna:
Brain Cancer Survival Prediction on Treatment-na ive MRI using Deep Anchor Attention Learning with Vision Transformer. CoRR abs/2202.01857 (2022) - [i16]Moinak Bhattacharya, Shubham Jain, Prateek Prasanna:
RadioTransformer: A Cascaded Global-Focal Transformer for Visual Attention-guided Disease Classification. CoRR abs/2202.11781 (2022) - [i15]Aishik Konwer, Xuan Xu, Joseph Bae, Chao Chen, Prateek Prasanna:
Temporal Context Matters: Enhancing Single Image Prediction with Disease Progression Representations. CoRR abs/2203.01933 (2022) - [i14]Lei Zhou, Huidong Liu, Joseph Bae, Junjun He, Dimitris Samaras, Prateek Prasanna:
Self Pre-training with Masked Autoencoders for Medical Image Analysis. CoRR abs/2203.05573 (2022) - [i13]Saarthak Kapse, Srijan Das, Prateek Prasanna:
CD-Net: Histopathology Representation Learning using Pyramidal Context-Detail Network. CoRR abs/2203.15078 (2022) - [i12]Yunfan Li, Vinayak Shenoy, Prateek Prasanna, I. V. Ramakrishnan, Haibin Ling, Himanshu Gupta:
Surgical Phase Recognition in Laparoscopic Cholecystectomy. CoRR abs/2206.07198 (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) - [i10]Nathaniel Braman, Prateek Prasanna, Kaustav Bera, Mehdi Alilou, Mohammadhadi Khorrami, Patrick Leo, Maryam Etesami, Manasa Vulchi, Paulette Turk, Amit Gupta, Prantesh Jain, Pingfu Fu, Nathan Pennell, Vamsidhar Velcheti, Jame Abraham, Donna Plecha, Anant Madabhushi:
Novel Radiomic Measurements of Tumor- Associated Vasculature Morphology on Clinical Imaging as a Biomarker of Treatment Response in Multiple Cancers. CoRR abs/2210.02273 (2022) - [i9]Jingwei Zhang, Saarthak Kapse, Ke Ma, Prateek Prasanna, Maria Vakalopoulou, Joel H. Saltz, Dimitris Samaras:
Precise Location Matching Improves Dense Contrastive Learning in Digital Pathology. CoRR abs/2212.12105 (2022) - 2021
- [j4]Cheng Lu, Can Fahrettin Koyuncu, Germán Corredor, Prateek Prasanna, Patrick Leo, Xiangxue Wang, Andrew Janowczyk, Kaustav Bera, James Lewis, Vamsidhar Velcheti, Anant Madabhushi:
Feature-driven local cell graph (FLocK): New computational pathology-based descriptors for prognosis of lung cancer and HPV status of oropharyngeal cancers. Medical Image Anal. 68: 101903 (2021) - [j3]Azam Moosavi, Natalia Figueiredo, Prateek Prasanna, Sunil K. Srivastava, Sumit Sharma, Anant Madabhushi, Justis P. Ehlers:
Imaging Features of Vessels and Leakage Patterns Predict Extended Interval Aflibercept Dosing Using Ultra-Widefield Angiography in Retinal Vascular Disease: Findings From the PERMEATE Study. IEEE Trans. Biomed. Eng. 68(6): 1777-1786 (2021) - [c25]Xuan Xu, Dimitris Samaras, Prateek Prasanna:
Radiologically Defined Tumor-habitat Adjacency as a Prognostic Biomarker in Glioblastoma. EMBC 2021: 3998-4001 - [c24]Fan Wang, Saarthak Kapse, Steven Liu, Prateek Prasanna, Chao Chen:
TopoTxR: A Topological Biomarker for Predicting Treatment Response in Breast Cancer. IPMI 2021: 386-397 - [c23]Divek Patel, Connor Cowan, Prateek Prasanna:
Predicting Mutation Status and Recurrence Free Survival in Non-Small Cell Lung Cancer: A Hierarchical ct Radiomics - Deep Learning Approach. ISBI 2021: 882-885 - [c22]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 - [c21]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 - [c20]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 - [c19]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 - [c18]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]Ibrahim Hammoud, Prateek Prasanna, I. V. Ramakrishnan, Adam Singer, Mark Henry, Henry C. Thode:
EventScore: An Automated Real-time Early Warning Score for Clinical Events. CoRR abs/2102.05958 (2021) - [i7]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]Fan Wang, Saarthak Kapse, Steven Liu, Prateek Prasanna, Chao Chen:
TopoTxR: A Topological Biomarker for Predicting Treatment Response in Breast Cancer. CoRR abs/2105.06049 (2021) - [i5]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) - [i4]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
- [j2]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) - [c17]David Paredes, Prateek Prasanna, Christina Preece, Rajarsi Gupta, Farzad Fereidouni, Dimitris Samaras, Tahsin M. Kurç, Richard M. Levenson, Patricia Thompson-Carino, Joel H. Saltz, Chao Chen:
Automated Assessment of the Curliness of Collagen Fiber in Breast Cancer. ECCV Workshops (1) 2020: 267-279 - [c16]Amogh Hiremath, Rakesh Shiradkar, Nathaniel Braman, Prateek Prasanna, Ardeshir R. Rastinehad, Andrei S. Purysko, Anant Madabhushi:
A combination of intra- and peri-tumoral deep features from prostate bi-parametric MRI can distinguish clinically significant and insignificant prostate cancer. Medical Imaging: Computer-Aided Diagnosis 2020 - [c15]Marwa Ismail, Ramon Correa, Kaustav Bera, Ruchika Verma, Anas Saeed Bamashmos, Niha G. Beig, Jacob Antunes, Prateek Prasanna, Volodymyr Statsevych, Manmeet Ahluwalia, Pallavi Tiwari:
Spatial-And-Context Aware (SpACe) "Virtual Biopsy" Radiogenomic Maps to Target Tumor Mutational Status on Structural MRI. MICCAI (2) 2020: 305-314 - [c14]Ruiwen Ding, Prateek Prasanna, Germán Corredor, Cheng Lu, Priya Velu, Khoi Le, Patrick Leo, Niha G. Beig, Vamsidhar Velcheti, David L. Rimm, Kurt A. Schalper, Anant Madabhushi:
Compactness measures of tumor infiltrating lymphocytes in lung adenocarcinoma are associated with overall patient survival and immune scores. Medical Imaging: Digital Pathology 2020: 1132003 - [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]Marwa Ismail, Ramon Correa, Kaustav Bera, Ruchika Verma, Anas Saeed Bamashmos, Niha G. Beig, Jacob Antunes, Prateek Prasanna, Volodymyr Statsevych, Manmeet Ahluwalia, Pallavi Tiwari:
Spatial-And-Context aware (SpACe) "virtual biopsy" radiogenomic maps to target tumor mutational status on structural MRI. CoRR abs/2006.09878 (2020) - [i1]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)
2010 – 2019
- 2019
- [c13]Prateek Prasanna, Justis Ehlers, Vishal Bobba, Natalia Figueredo, Cheng Lu, Sumit Sharma, Sunil Srivastava, Anant Madabhushi:
Spatial arrangement of leakage patterns in diabetic macular edema is associated with tolerance of aflibercept treatment interval length: preliminary findings. Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging 2019: 1095311 - [c12]Prateek Prasanna, Justis Ehlers, Nathaniel Braman, Natalia Figueredo, Vishal Bobba, Sumit Sharma, Sunil Srivastava, Anant Madabhushi:
Morphology of vascular network in eyes with diabetic macular edema varies based on tolerance of aflibercept treatment interval length: preliminary findings. Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging 2019: 1095312 - [c11]Mohammadhadi Khorrami, Mehdi Alilou, Prateek Prasanna, Pradnya Patil, Pirya Velu, Kaustav Bera, Pingfu Fu, Vamsidhar Velcheti, Anant Madabhushi:
A combination of intra- and peritumoral features on baseline CT scans is associated with overall survival in non-small cell lung cancer patients treated with immune checkpoint inhibitors: a multi-agent multi-site study. Medical Imaging: Computer-Aided Diagnosis 2019: 109500R - [c10]Niha G. Beig, Prateek Prasanna, Virginia B. Hill, Ruchika Verma, Vinay Varadan, Anant Madabhushi, Pallavi Tiwari:
Radiogenomic characterization of response to chemo-radiation therapy in glioblastoma is associated with PI3K/AKT/mTOR and apoptosis signaling pathways. Medical Imaging: Computer-Aided Diagnosis 2019: 109501B - [c9]Sukanya Iyer, Marwa Ismail, Benita Tamrazi, Ashley Margol, Ruchika Verma, Ramon Correa, Prateek Prasanna, Niha G. Beig, Kaustav Bera, Volodymyr Statsevych, Alexander R. Judkins, Anant Madabhushi, Pallavi Tiwari:
Deformation heterogeneity radiomics to predict molecular subtypes of pediatric Medulloblastoma on routine MRI. Medical Imaging: Computer-Aided Diagnosis 2019: 109501E - 2018
- [c8]Cheng Lu, Xiangxue Wang, Prateek Prasanna, Germán Corredor, Geoffrey Sedor, Kaustav Bera, Vamsidhar Velcheti, Anant Madabhushi:
Feature Driven Local Cell Graph (FeDeG): Predicting Overall Survival in Early Stage Lung Cancer. MICCAI (2) 2018: 407-416 - [c7]Nathaniel Braman, Prateek Prasanna, Mehdi Alilou, Niha G. Beig, Anant Madabhushi:
Vascular Network Organization via Hough Transform (VaNgOGH): A Novel Radiomic Biomarker for Diagnosis and Treatment Response. MICCAI (2) 2018: 803-811 - 2017
- [c6]Niha G. Beig, Jay Patel, Prateek Prasanna, Sasan Partovi, Vinay Varadan, Anant Madabhushi, Pallavi Tiwari:
Radiogenomic analysis of hypoxia pathway reveals computerized MRI descriptors predictive of overall survival in glioblastoma. Medical Imaging: Computer-Aided Diagnosis 2017: 101341U - [c5]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 - [c4]Jacob Antunes, Prateek Prasanna, Anant Madabhushi, Pallavi Tiwari, Satish Viswanath:
RADIomic Spatial TexturAl descripTor (RADISTAT): Characterizing Intra-tumoral Heterogeneity for Response and Outcome Prediction. MICCAI (2) 2017: 468-476 - 2016
- [j1]Prateek Prasanna, Kristin J. Dana, Nenad Gucunski, Basily B. Basily, Hung Manh La, Ronny Salim Lim, Hooman Parvardeh:
Automated Crack Detection on Concrete Bridges. IEEE Trans Autom. Sci. Eng. 13(2): 591-599 (2016) - 2014
- [c3]Pallavi Tiwari, Prateek Prasanna, Lisa Rogers, Leo Wolansky, Chaitra Badve, Andrew Sloan, Mark Cohen, Anant Madabhushi:
Texture descriptors to distinguish radiation necrosis from recurrent brain tumors on multi-parametric MRI. Medical Imaging: Computer-Aided Diagnosis 2014: 90352B - [c2]Prateek Prasanna, Pallavi Tiwari, Anant Madabhushi:
Co-occurrence of Local Anisotropic Gradient Orientations (CoLlAGe): Distinguishing Tumor Confounders and Molecular Subtypes on MRI. MICCAI (3) 2014: 73-80 - 2013
- [c1]Prateek Prasanna, Shubham Jain, Neelakshi Bhagat, Anant Madabhushi:
Decision support system for detection of diabetic retinopathy using smartphones. PervasiveHealth 2013: 176-179
Coauthor Index
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Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-11-06 20:29 CET by the dblp team
all metadata released as open data under CC0 1.0 license
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since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
