Decision support system for detection of diabetic retinopathy using smartphones. - Prateek Prasanna; Shubham Jain; Neelakshi Bhagat; Anant Madabhushi (PervasiveHealth, 2013)

Texture descriptors to distinguish radiation necrosis from recurrent brain tumors on multi-parametric MRI. - Pallavi Tiwari; Prateek Prasanna; Lisa Rogers; Leo Wolansky; Chaitra Badve; Andrew Sloan; Mark Cohen; Anant Madabhushi (Computer-Aided Diagnosis, 2014)

Co-occurrence of Local Anisotropic Gradient Orientations (CoLlAGe): Distinguishing Tumor Confounders and Molecular Subtypes on MRI. - Prateek Prasanna; Pallavi Tiwari; Anant Madabhushi (MICCAI (3), 2014)

Automated Crack Detection on Concrete Bridges. - Prateek Prasanna; Kristin J. Dana; Nenad Gucunski; Basily B. Basily; Hung Manh La; Ronny Salim Lim; Hooman Parvardeh (IEEE Trans Autom. Sci. Eng., 2016)

Radiogenomic analysis of hypoxia pathway reveals computerized MRI descriptors predictive of overall survival in glioblastoma. - Niha G. Beig; Jay Patel; Prateek Prasanna; Sasan Partovi; Vinay Varadan; Anant Madabhushi; Pallavi Tiwari (Computer-Aided Diagnosis, 2017)

RADIomic Spatial TexturAl descripTor (RADISTAT): Characterizing Intra-tumoral Heterogeneity for Response and Outcome Prediction. - Jacob Antunes; Prateek Prasanna; Anant Madabhushi; Pallavi Tiwari; Satish Viswanath (MICCAI (2), 2017)

Radiographic-Deformation and Textural Heterogeneity (r-DepTH): An Integrated Descriptor for Brain Tumor Prognosis. - Prateek Prasanna; Jhimli Mitra; Niha G. Beig; Sasan Partovi; Gagandeep Singh; Marco Pinho; Anant Madabhushi; Pallavi Tiwari (MICCAI (2), 2017)

Vascular Network Organization via Hough Transform (VaNgOGH): A Novel Radiomic Biomarker for Diagnosis and Treatment Response. - Nathaniel Braman; Prateek Prasanna; Mehdi Alilou; Niha G. Beig; Anant Madabhushi (MICCAI (2), 2018)

Feature Driven Local Cell Graph (FeDeG): Predicting Overall Survival in Early Stage Lung Cancer. - Cheng Lu 001; Xiangxue Wang; Prateek Prasanna; Germán Corredor; Geoffrey Sedor; Kaustav Bera; Vamsidhar Velcheti; Anant Madabhushi (MICCAI (2), 2018)

Morphology of vascular network in eyes with diabetic macular edema varies based on tolerance of aflibercept treatment interval length: preliminary findings. - Prateek Prasanna; Justis Ehlers; Nathaniel Braman; Natalia Figueredo; Vishal Bobba; Sumit Sharma 005; Sunil Srivastava; Anant Madabhushi (Biomedical Applications in Molecular, Structural, and Functional Imaging, 2019)

Spatial arrangement of leakage patterns in diabetic macular edema is associated with tolerance of aflibercept treatment interval length: preliminary findings. - Prateek Prasanna; Justis Ehlers; Vishal Bobba; Natalia Figueredo; Cheng Lu 001; Sumit Sharma 005; Sunil Srivastava; Anant Madabhushi (Biomedical Applications in Molecular, Structural, and Functional Imaging, 2019)

Radiogenomic characterization of response to chemo-radiation therapy in glioblastoma is associated with PI3K/AKT/mTOR and apoptosis signaling pathways. - Niha G. Beig; Prateek Prasanna; Virginia B. Hill; Ruchika Verma; Vinay Varadan; Anant Madabhushi; Pallavi Tiwari (Computer-Aided Diagnosis, 2019)

Deformation heterogeneity radiomics to predict molecular subtypes of pediatric Medulloblastoma on routine MRI. - 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; et al. (Computer-Aided Diagnosis, 2019)

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. - Mohammadhadi Khorrami; Mehdi Alilou; Prateek Prasanna; Pradnya Patil; Pirya Velu; Kaustav Bera; Pingfu Fu; Vamsidhar Velcheti; Anant Madabhushi (Computer-Aided Diagnosis, 2019)

Automated Assessment of the Curliness of Collagen Fiber in Breast Cancer. - David Paredes; Prateek Prasanna; Christina Preece; Rajarsi Gupta 001; Farzad Fereidouni; Dimitris Samaras; Tahsin M. Kurç; Richard M. Levenson 001; Patricia Thompson-Carino; Joel H. Saltz; Chao Chen 012 (ECCV Workshops (1), 2020)

A combination of intra- and peri-tumoral deep features from prostate bi-parametric MRI can distinguish clinically significant and insignificant prostate cancer. - Amogh Hiremath; Rakesh Shiradkar; Nathaniel Braman; Prateek Prasanna; Ardeshir R. Rastinehad; Andrei S. Purysko; Anant Madabhushi (Computer-Aided Diagnosis, 2020)

Spatial-And-Context Aware (SpACe) "Virtual Biopsy" Radiogenomic Maps to Target Tumor Mutational Status on Structural MRI. - Marwa Ismail; Ramon Correa; Kaustav Bera; Ruchika Verma; Anas Saeed Bamashmos; Niha G. Beig; Jacob Antunes; Prateek Prasanna; Volodymyr Statsevych; Manmeet Ahluwalia; Pallavi Tiwari (MICCAI (2), 2020)

Compactness measures of tumor infiltrating lymphocytes in lung adenocarcinoma are associated with overall patient survival and immune scores. - Ruiwen Ding; Prateek Prasanna; Germán Corredor; Cheng Lu 001; Priya Velu; Khoi Le; Patrick Leo; Niha G. Beig; Vamsidhar Velcheti; David L. Rimm; Kurt A. Schalper; Anant Madabhushi (Digital Pathology, 2020)

Can tumor location on pre-treatment MRI predict likelihood of pseudo-progression versus tumor recurrence in Glioblastoma? A feasibility study. - 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 (CoRR, 2020)

Predicting Mechanical Ventilation Requirement and Mortality in COVID-19 using Radiomics and Deep Learning on Chest Radiographs: A Multi-Institutional Study. - Joseph Bae; Saarthak Kapse; Gagandeep Singh; Tej Phatak; Jeremy Green; Nikhil Madan; Prateek Prasanna (CoRR, 2020)

Can Tumor Location on Pre-treatment MRI Predict Likelihood of Pseudo-Progression vs. Tumor Recurrence in Glioblastoma? - A Feasibility Study. - 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 (Frontiers Comput. Neurosci., 2020)

Radiologically Defined Tumor-habitat Adjacency as a Prognostic Biomarker in Glioblastoma. - Xuan Xu; Dimitris Samaras; Prateek Prasanna (EMBC, 2021)

TopoTxR: A Topological Biomarker for Predicting Treatment Response in Breast Cancer. - Fan Wang 010; Saarthak Kapse; Steven Liu; Prateek Prasanna; Chao Chen 012 (IPMI, 2021)

Predicting Mutation Status and Recurrence Free Survival in Non-Small Cell Lung Cancer: A Hierarchical ct Radiomics - Deep Learning Approach. - Divek Patel; Connor Cowan; Prateek Prasanna (ISBI, 2021)

Evolution of chest radiograph radiomics and association with respiratory and inflammatory parameters in COVID-19 patients undergoing prone ventilation: preliminary findings. - Connor Cowan; Joseph Bae; Gagandeep Singh; Rohit Khullar; Shrey Shah; Nikhil Madan; Prateek Prasanna (Computer-Aided Diagnosis, 2021)

Attention-Based Multi-scale Gated Recurrent Encoder with Novel Correlation Loss for COVID-19 Progression Prediction. - Aishik Konwer; Joseph Bae; Gagandeep Singh; Rishabh Gattu; Syed Ali; Jeremy Green; Tej Phatak; Prateek Prasanna (MICCAI (5), 2021)

Attention Based CNN-LSTM Network for Pulmonary Embolism Prediction on Chest Computed Tomography Pulmonary Angiograms. - Sudhir Suman; Gagandeep Singh; Nicole Sakla; Rishabh Gattu; Jeremy Green; Tej Phatak; Dimitris Samaras; Prateek Prasanna (MICCAI (7), 2021)

Chest Radiograph Disentanglement for COVID-19 Outcome Prediction. - Lei Zhou; Joseph Bae; Huidong Liu; Gagandeep Singh; Jeremy Green; Dimitris Samaras; Prateek Prasanna (MICCAI (7), 2021)

Predicting COVID-19 Lung Infiltrate Progression on Chest Radiographs Using Spatio-temporal LSTM based Encoder-Decoder Network. - Aishik Konwer; Joseph Bae; Gagandeep Singh; Rishabh Gattu; Syed Ali; Jeremy Green; Tej Phatak; Amit Gupta; Chao Chen 012; Joel H. Saltz; Prateek Prasanna (MIDL, 2021)

Feature-driven local cell graph (FLocK): New computational pathology-based descriptors for prognosis of lung cancer and HPV status of oropharyngeal cancers. - Cheng Lu 001; Can Koyuncu 001; Germán Corredor; Prateek Prasanna; Patrick Leo; Xiangxue Wang; Andrew Janowczyk; Kaustav Bera; James S. Lewis Jr.; Vamsidhar Velcheti; Anant Madabhushi (Medical Image Anal., 2021)

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. - Azam Moosavi; Natalia Figueiredo; Prateek Prasanna; Sunil K. Srivastava; Sumit Sharma 005; Anant Madabhushi; Justis P. Ehlers (IEEE Trans. Biomed. Eng., 2021)

Temporal Context Matters: Enhancing Single Image Prediction with Disease Progression Representations. - Aishik Konwer; Xuan Xu; Joseph Bae; Chao Chen 012; Prateek Prasanna (CVPR, 2022)

RadioTransformer: A Cascaded Global-Focal Transformer for Visual Attention-Guided Disease Classification. - Moinak Bhattacharya; Shubham Jain; Prateek Prasanna (ECCV (21), 2022)

Learning Topological Interactions for Multi-Class Medical Image Segmentation. - Saumya Gupta; Xiaoling Hu 002; James Kaan; Michael Jin; Mutshipay Mpoy; Katherine Chung; Gagandeep Singh; Mary M. Saltz; Tahsin M. Kurç; Joel H. Saltz; Apostolos Tassiopoulos; Prateek Prasanna; et al. (ECCV (29), 2022)

EventScore: An Automated Real-time Early Warning Score for Clinical Events. - Ibrahim Hammoud; Prateek Prasanna; I. V. Ramakrishnan; Adam Singer; Mark Henry; Henry C. Thode (ICHI, 2022)

Subtype-Specific Spatial Descriptors of Tumor-Immune Microenvironment are Prognostic of Survival in Lung Adenocarcinoma. - Saarthak Kapse; Luke Torre-Healy; Richard A. Moffitt; Rajarsi Gupta 001; Prateek Prasanna (ISBI, 2022)

Brain Cancer Survival Prediction on Treatment-Naïve MRI using Deep Anchor Attention Learning with Vision Transformer. - Xuan Xu; Prateek Prasanna (ISBI, 2022)

Clinical outcome prediction in COVID-19 using self-supervised vision transformer representations. - Aishik Konwer; Prateek Prasanna (Computer-Aided Diagnosis, 2022)

GazeRadar: A Gaze and Radiomics-Guided Disease Localization Framework. - Moinak Bhattacharya; Shubham Jain; Prateek Prasanna (MICCAI (3), 2022)

Shape-based tumor microenvironment analysis to differentiate non-small cell lung cancer subtypes: a radio-pathomic study. - Saarthak Kapse; Rajarsi Gupta 001; Prateek Prasanna (Digital and Computational Pathology, 2022)

Selecting training samples for ovarian cancer classification via a semi-supervised clustering approach. - Jennifer Salguero López; Prateek Prasanna; Germán Corredor; Angel Cruz-Roa; David Becerra; Eduardo Romero 001 (Digital and Computational Pathology, 2022)

Muti-stage attention-based network for brain tumor subtype classification. - Sudhir Suman; Prateek Prasanna (Digital and Computational Pathology, 2022)

Lung Swapping Autoencoder: Learning a Disentangled Structure-texture Representation of Chest Radiographs. - Lei Zhou; Joseph Bae; Huidong Liu; Gagandeep Singh; Jeremy Green; Amit Gupta; Dimitris Samaras; Prateek Prasanna (CoRR, 2022)

Brain Cancer Survival Prediction on Treatment-na ive MRI using Deep Anchor Attention Learning with Vision Transformer. - Xuan Xu; Prateek Prasanna (CoRR, 2022)

Self Pre-training with Masked Autoencoders for Medical Image Analysis. - Lei Zhou; Huidong Liu; Joseph Bae; Junjun He; Dimitris Samaras; Prateek Prasanna (CoRR, 2022)

CD-Net: Histopathology Representation Learning using Pyramidal Context-Detail Network. - Saarthak Kapse; Srijan Das; Prateek Prasanna (CoRR, 2022)

Surgical Phase Recognition in Laparoscopic Cholecystectomy. - Yunfan Li 006; Vinayak Shenoy; Prateek Prasanna; I. V. Ramakrishnan; Haibin Ling; Himanshu Gupta (CoRR, 2022)

Novel Radiomic Measurements of Tumor- Associated Vasculature Morphology on Clinical Imaging as a Biomarker of Treatment Response in Multiple Cancers. - Nathaniel Braman; Prateek Prasanna; Kaustav Bera; Mehdi Alilou; Mohammadhadi Khorrami; Patrick Leo; Maryam Etesami; Manasa Vulchi; Paulette Turk; Amit Gupta; Prantesh Jain; Pingfu Fu; et al. (CoRR, 2022)

RADIomic Spatial TexturAl Descriptor (RADISTAT): Quantifying Spatial Organization of Imaging Heterogeneity Associated With Tumor Response to Treatment. - Jacob T. Antunes; Marwa Ismail; Imran Hossain; Zhoumengdi Wang; Prateek Prasanna; Anant Madabhushi; Pallavi Tiwari; Satish E. Viswanath (IEEE J. Biomed. Health Informatics, 2022)

Radiomic Deformation and Textural Heterogeneity (R-DepTH) Descriptor to Characterize Tumor Field Effect: Application to Survival Prediction in Glioblastoma. - 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; et al. (IEEE Trans. Medical Imaging, 2022)

Surgical Phase Recognition in Laparoscopic Cholecystectomy. - Yunfan Li 006; Himanshu Gupta; Prateek Prasanna; I. V. Ramakrishnan; Haibin Ling (CENTERIS/ProjMAN/HCist, 2023)

Enhancing Modality-Agnostic Representations via Meta-learning for Brain Tumor Segmentation. - Aishik Konwer; Xiaoling Hu 002; Joseph Bae; Xuan Xu; Chao Chen 012; Prateek Prasanna (ICCV, 2023)

Automated Assessment of Critical View of Safety in Laparoscopic Cholecystectomy. - Yunfan Li 006; Himanshu Gupta; Haibin Ling; I. V. Ramakrishnan; Prateek Prasanna; Georgios Georgakis; Aaron Sasson (ICHI, 2023)

Learning to Segment from Noisy Annotations: A Spatial Correction Approach. - Jiachen Yao; Yikai Zhang 003; Songzhu Zheng; Mayank Goswami 001; Prateek Prasanna; Chao Chen 012 (ICLR, 2023)

Precise Location Matching Improves Dense Contrastive Learning in Digital Pathology. - Jingwei Zhang; Saarthak Kapse; Ke Ma 005; Prateek Prasanna; Maria Vakalopoulou; Joel H. Saltz; Dimitris Samaras (IPMI, 2023)

Token Sparsification for Faster Medical Image Segmentation. - Lei Zhou; Huidong Liu; Joseph Bae; Junjun He; Dimitris Samaras; Prateek Prasanna (IPMI, 2023)

CD-Net: Histopathology Representation Learning Using Context-Detail Transformer Network. - Saarthak Kapse; Srijan Das; Prateek Prasanna (ISBI, 2023)

Self Pre-Training with Masked Autoencoders for Medical Image Classification and Segmentation. - Lei Zhou; Huidong Liu; Joseph Bae; Junjun He; Dimitris Samaras; Prateek Prasanna (ISBI, 2023)

Audio-visual feature fusion for improved thoracic disease classification. - Moinak Bhattacharya; Prateek Prasanna (Computer-Aided Diagnosis, 2023)

ViT-DAE: Transformer-Driven Diffusion Autoencoder for Histopathology Image Analysis. - Xuan Xu; Saarthak Kapse; Rajarsi Gupta 001; Prateek Prasanna (DGM4MICCAI, 2023)

Prompt-MIL: Boosting Multi-instance Learning Schemes via Task-Specific Prompt Tuning. - Jingwei Zhang; Saarthak Kapse; Ke Ma 005; Prateek Prasanna; Joel H. Saltz; Maria Vakalopoulou; Dimitris Samaras (MICCAI (8), 2023)

SAM-Path: A Segment Anything Model for Semantic Segmentation in Digital Pathology. - Jingwei Zhang; Ke Ma 005; Saarthak Kapse; Joel H. Saltz; Maria Vakalopoulou; Prateek Prasanna; Dimitris Samaras (ISIC/Care-AI/MedAGI/DeCaF@MICCAI, 2023)

Role of stain normalization in computational pathology: use case in metastatic tissue classification. - Paras Goel; Saarthak Kapse; Prateek Prasanna (Digital and Computational Pathology, 2023)

MagNET: Modality-Agnostic Network for Brain Tumor Segmentation and Characterization with Missing Modalities. - Aishik Konwer; Chao Chen 012; Prateek Prasanna (MLMI@MICCAI (1), 2023)

Topology-Aware Uncertainty for Image Segmentation. - Saumya Gupta; Yikai Zhang 003; Xiaoling Hu 002; Prateek Prasanna; Chao Chen 012 (NeurIPS, 2023)

New Spatial Phenotypes from Imaging Uncover Survival Differences for Breast Cancer Patients. - Mahmudul Hasan 006; Ariadna Kim Silva; Shahira Abousamra; Shao-Jun Tang; Prateek Prasanna; Joel H. Saltz; Kevin Gardner; Chao Chen 012; Alisa Yurovsky (BCB, 2024)

Learned Representation-Guided Diffusion Models for Large-Image Generation. - Alexandros Graikos; Srikar Yellapragada; Minh-Quan Le; Saarthak Kapse; Prateek Prasanna; Joel H. Saltz; Dimitris Samaras (CVPR, 2024)

SI-MIL: Taming Deep MIL for Self-Interpretability in Gigapixel Histopathology. - Saarthak Kapse; Pushpak Pati; Srijan Das; Jingwei Zhang; Chao Chen 012; Maria Vakalopoulou; Joel H. Saltz; Dimitris Samaras; Rajarsi R. Gupta; Prateek Prasanna (CVPR, 2024)

Critical View of Safety Assessment in Laparoscopic Cholecystectomy via Segment Anything Model. - Yunfan Li 006; Haibin Ling; I. V. Ramakrishnan; Prateek Prasanna; Aaron Sasson; Himanshu Gupta (EMBC, 2024)

Coca-Mil: Attention-Based Handcrafted-Deep Feature Fusion in Computational Pathology. - Paras Goel; Saarthak Kapse; Pushpak Pati; Prateek Prasanna (ISBI, 2024)

HoG-Net: Hierarchical Multi-organ Graph Network for Head and Neck Cancer Recurrence Prediction from CT Images. - Joseph Bae; Saarthak Kapse; Lei Zhou; Kartik Mani; Prateek Prasanna (MICCAI (5), 2024)

Semi-supervised Contrastive VAE for Disentanglement of Digital Pathology Images. - Mahmudul Hasan 006; Xiaoling Hu 002; Shahira Abousamra; Prateek Prasanna; Joel H. Saltz; Chao Chen 012 (MICCAI (4), 2024)

Hard Negative Sample Mining for Whole Slide Image Classification. - Wentao Huang; Xiaoling Hu 002; Shahira Abousamra; Prateek Prasanna; Chao Chen 012 (MICCAI (4), 2024)

MetaStain: Stain-Generalizable Meta-learning for Cell Segmentation and Classification with Limited Exemplars. - Aishik Konwer; Prateek Prasanna (MICCAI (4), 2024)

A Topological Comparison of the Fluorescence Imitating Brightfield Imaging and H&E Imaging. - Meiliong Xu; Nate Anderson; Richard M. Levenson 001; Prateek Prasanna; Chao Chen 012 (TGI3@MICCAI, 2024)

GazeDiff: A radiologist visual attention guided diffusion model for zero-shot disease classification. - Moinak Bhattacharya; Prateek Prasanna (MIDL, 2024)

PathLDM: Text conditioned Latent Diffusion Model for Histopathology. - Srikar Yellapragada; Alexandros Graikos; Prateek Prasanna; Tahsin M. Kurç; Joel H. Saltz; Dimitris Samaras (WACV, 2024)

Histo-Diffusion: A Diffusion Super-Resolution Method for Digital Pathology with Comprehensive Quality Assessment. - Xuan Xu; Saarthak Kapse; Prateek Prasanna (CoRR, 2024)

RadGazeGen: Radiomics and Gaze-guided Medical Image Generation using Diffusion Models. - Moinak Bhattacharya; Gagandeep Singh; Shubham Jain; Prateek Prasanna (CoRR, 2024)

RankByGene: Gene-Guided Histopathology Representation Learning Through Cross-Modal Ranking Consistency. - Wentao Huang; Meilong Xu; Xiaoling Hu 002; Shahira Abousamra; Aniruddha Ganguly; Saarthak Kapse; Alisa Yurovsky; Prateek Prasanna; Tahsin M. Kurç; Joel H. Saltz; Michael L. Miller; Chao Chen 012 (CoRR, 2024)

Gen-SIS: Generative Self-augmentation Improves Self-supervised Learning. - Varun Belagali; Srikar Yellapragada; Alexandros Graikos; Saarthak Kapse; Zilinghan Li; Tarak Nath Nandi; Ravi K. Madduri; Prateek Prasanna; Joel H. Saltz; Dimitris Samaras (CoRR, 2024)

Data distillation in computational pathology by choosing few representants of the original variance: A use case in ovarian cancer. - Jennifer Salguero; Prateek Prasanna; Germán Corredor; Angel Cruz-Roa; David Becerra; Eduardo Romero 001 (Expert Syst. Appl., 2024)

Attention De-sparsification Matters: Inducing diversity in digital pathology representation learning. - Saarthak Kapse; Srijan Das; Jingwei Zhang; Rajarsi R. Gupta; Joel H. Saltz; Dimitris Samaras; Prateek Prasanna (Medical Image Anal., 2024)

Enhancing SAM with Efficient Prompting and Preference Optimization for Semi-supervised Medical Image Segmentation. - Aishik Konwer; Zhijian Yang; Erhan Bas; Cao Xiao; Prateek Prasanna; Parminder Bhatia; Taha A. Kass-Hout (CVPR, 2025)

TopoCellGen: Generating Histopathology Cell Topology with a Diffusion Model. - Meilong Xu; Saumya Gupta; Xiaoling Hu 002; Chen Li 045; Shahira Abousamra; Dimitris Samaras; Prateek Prasanna; Chao Chen 012 (CVPR, 2025)

ZoomLDM: Latent Diffusion Model for Multi-scale Image Generation. - Srikar Yellapragada; Alexandros Graikos; Kostas Triaridis; Prateek Prasanna; Rajarsi Gupta 001; Joel H. Saltz; Dimitris Samaras (CVPR, 2025)

TopoTxR: A topology-guided deep convolutional network for breast parenchyma learning on DCE-MRIs. - Fan Wang 010; Zhilin Zou; Nicole Sakla; Luke Partyka; Nil Rawal; Gagandeep Singh; Wei Zhao; Haibin Ling; Chuan Huang; Prateek Prasanna; Chao Chen 012 (Medical Image Anal., 2025)

Pathology Image Compression with Pre-trained Autoencoders. - Srikar Yellapragada; Alexandros Graikos; Kostas Triaridis; Zilinghan Li; Tarak Nath Nandi; Ravi K. Madduri; Prateek Prasanna; Joel H. Saltz; Dimitris Samaras (CoRR, 2025)

GECKO: Gigapixel Vision-Concept Contrastive Pretraining in Histopathology. - Saarthak Kapse; Pushpak Pati; Srikar Yellapragada; Srijan Das; Rajarsi R. Gupta; Joel H. Saltz; Dimitris Samaras; Prateek Prasanna (CoRR, 2025)

BrainMRDiff: A Diffusion Model for Anatomically Consistent Brain MRI Synthesis. - Moinak Bhattacharya; Saumya Gupta; Annie Singh; Chao Chen 012; Gagandeep Singh; Prateek Prasanna (CoRR, 2025)

ImmunoDiff: A Diffusion Model for Immunotherapy Response Prediction in Lung Cancer. - Moinak Bhattacharya; Judy Huang; Amna F. Sher; Gagandeep Singh; Chao Chen 012; Prateek Prasanna (CoRR, 2025)

PixCell: A generative foundation model for digital histopathology images. - Srikar Yellapragada; Alexandros Graikos; Zilinghan Li; Kostas Triaridis; Varun Belagali; Saarthak Kapse; Tarak Nath Nandi; Ravi K. Madduri; Prateek Prasanna; Tahsin M. Kurç; Rajarsi R. Gupta; Joel H. Saltz; et al. (CoRR, 2025)

GazeLT: Visual attention-guided long-tailed disease classification in chest radiographs. - Moinak Bhattacharya; Gagandeep Singh; Shubham Jain; Prateek Prasanna (CoRR, 2025)