Prateek Prasanna
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
33
Venues
6
Active years
2014–2026
Best venue rank
A*
Where they publish
Papers
33 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | WACV | PEaRL: Pathway-Enhanced Representation Learning for Gene and Pathway Expression Prediction from Histology. | Sejuti Majumder, Saarthak Kapse, Moinak Bhattacharya, Xuan Xu, Alisa Yurovsky, Prateek Prasanna |
| 2025 | CVPR | 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 |
| 2025 | CVPR | TopoCellGen: Generating Histopathology Cell Topology with a Diffusion Model. | Meilong Xu, Saumya Gupta, Xiaoling Hu, Chen Li, Shahira Abousamra, Dimitris Samaras, Prateek Prasanna, Chao Chen |
| 2025 | CVPR | ZoomLDM: Latent Diffusion Model for Multi-scale Image Generation. | Srikar Yellapragada, Alexandros Graikos, Kostas Triaridis, Prateek Prasanna, Rajarsi Gupta, Joel H. Saltz, Dimitris Samaras |
| 2025 | ICCV | 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 |
| 2025 | MICCAI | 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 |
| 2024 | CVPR | 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 |
| 2024 | CVPR | SI-MIL: Taming Deep MIL for Self-Interpretability in Gigapixel Histopathology. | Saarthak Kapse, Pushpak Pati, Srijan Das, Jingwei Zhang, Chao Chen, Maria Vakalopoulou, Joel H. Saltz, Dimitris Samaras, Rajarsi R. Gupta, Prateek Prasanna |
| 2024 | MICCAI | 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 |
| 2024 | MICCAI | Semi-supervised Contrastive VAE for Disentanglement of Digital Pathology Images. | Mahmudul Hasan, Xiaoling Hu, Shahira Abousamra, Prateek Prasanna, Joel H. Saltz, Chao Chen |
| 2024 | MICCAI | Hard Negative Sample Mining for Whole Slide Image Classification. | Wentao Huang, Xiaoling Hu, Shahira Abousamra, Prateek Prasanna, Chao Chen |
| 2024 | MICCAI | MetaStain: Stain-Generalizable Meta-learning for Cell Segmentation and Classification with Limited Exemplars. | Aishik Konwer, Prateek Prasanna |
| 2024 | MICCAI | A Topological Comparison of the Fluorescence Imitating Brightfield Imaging and H&E Imaging. | Meiliong Xu, Nate Anderson, Richard M. Levenson, Prateek Prasanna, Chao Chen |
| 2024 | WACV | PathLDM: Text conditioned Latent Diffusion Model for Histopathology. | Srikar Yellapragada, Alexandros Graikos, Prateek Prasanna, Tahsin M. Kur, Joel H. Saltz, Dimitris Samaras |
| 2023 | ICCV | Enhancing Modality-Agnostic Representations via Meta-learning for Brain Tumor Segmentation. | Aishik Konwer, Xiaoling Hu, Joseph Bae, Xuan Xu, Chao Chen, Prateek Prasanna |
| 2023 | ICLR | Learning to Segment from Noisy Annotations: A Spatial Correction Approach. | Jiachen Yao, Yikai Zhang, Songzhu Zheng, Mayank Goswami, Prateek Prasanna, Chao Chen |
| 2023 | MICCAI | ViT-DAE: Transformer-Driven Diffusion Autoencoder for Histopathology Image Analysis. | Xuan Xu, Saarthak Kapse, Rajarsi Gupta, Prateek Prasanna |
| 2023 | MICCAI | Prompt-MIL: Boosting Multi-instance Learning Schemes via Task-Specific Prompt Tuning. | Jingwei Zhang, Saarthak Kapse, Ke Ma, Prateek Prasanna, Joel H. Saltz, Maria Vakalopoulou, Dimitris Samaras |
| 2023 | MICCAI | SAM-Path: A Segment Anything Model for Semantic Segmentation in Digital Pathology. | Jingwei Zhang, Ke Ma, Saarthak Kapse, Joel H. Saltz, Maria Vakalopoulou, Prateek Prasanna, Dimitris Samaras |
| 2022 | CVPR | Temporal Context Matters: Enhancing Single Image Prediction with Disease Progression Representations. | Aishik Konwer, Xuan Xu, Joseph Bae, Chao Chen, Prateek Prasanna |
| 2022 | ECCV | RadioTransformer: A Cascaded Global-Focal Transformer for Visual Attention-Guided Disease Classification. | Moinak Bhattacharya, Shubham Jain, Prateek Prasanna |
| 2022 | ECCV | Learning Topological Interactions for Multi-Class Medical Image Segmentation. | Saumya Gupta, Xiaoling Hu, James Kaan, Michael Jin, Mutshipay Mpoy, Katherine Chung, Gagandeep Singh, Mary M. Saltz, Tahsin M. Kur, Joel H. Saltz, Apostolos Tassiopoulos, Prateek Prasanna, Chao Chen |
| 2022 | MICCAI | GazeRadar: A Gaze and Radiomics-Guided Disease Localization Framework. | Moinak Bhattacharya, Shubham Jain, Prateek Prasanna |
| 2021 | MICCAI | 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 |
| 2021 | MICCAI | 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 |
| 2021 | MICCAI | Chest Radiograph Disentanglement for COVID-19 Outcome Prediction. | Lei Zhou, Joseph Bae, Huidong Liu, Gagandeep Singh, Jeremy Green, Dimitris Samaras, Prateek Prasanna |
| 2020 | ECCV | Automated Assessment of the Curliness of Collagen Fiber in Breast Cancer. | David Paredes, Prateek Prasanna, Christina Preece, Rajarsi Gupta, Farzad Fereidouni, Dimitris Samaras, Tahsin M. Kur, Richard M. Levenson, Patricia Thompson-Carino, Joel H. Saltz, Chao Chen |
| 2020 | MICCAI | 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 |
| 2018 | MICCAI | 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 |
| 2018 | MICCAI | Feature Driven Local Cell Graph (FeDeG): Predicting Overall Survival in Early Stage Lung Cancer. | Cheng Lu, Xiangxue Wang, Prateek Prasanna, Germn Corredor, Geoffrey Sedor, Kaustav Bera, Vamsidhar Velcheti, Anant Madabhushi |
| 2017 | MICCAI | RADIomic Spatial TexturAl descripTor (RADISTAT): Characterizing Intra-tumoral Heterogeneity for Response and Outcome Prediction. | Jacob Antunes, Prateek Prasanna, Anant Madabhushi, Pallavi Tiwari, Satish Viswanath |
| 2017 | MICCAI | 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 |
| 2014 | MICCAI | Co-occurrence of Local Anisotropic Gradient Orientations (CoLlAGe): Distinguishing Tumor Confounders and Molecular Subtypes on MRI. | Prateek Prasanna, Pallavi Tiwari, Anant Madabhushi |