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2020 – today
- 2024
[j1]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)- [c11]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 - [c10]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 - [c9]Paras Goel, Saarthak Kapse, Pushpak Pati, Prateek Prasanna:
Coca-Mil: Attention-Based Handcrafted-Deep Feature Fusion in Computational Pathology. ISBI 2024: 1-5 - [c8]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 - [i11]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) - 2023
- [c7]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 - [c6]Saarthak Kapse, Srijan Das, Prateek Prasanna:
CD-Net: Histopathology Representation Learning Using Context-Detail Transformer Network. ISBI 2023: 1-5 - [c5]Xuan Xu, Saarthak Kapse, Rajarsi Gupta, Prateek Prasanna:
ViT-DAE: Transformer-Driven Diffusion Autoencoder for Histopathology Image Analysis. DGM4MICCAI 2023: 66-76 - [c4]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 - [c3]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 - [i10]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) - [i9]Xuan Xu, Saarthak Kapse, Rajarsi Gupta, Prateek Prasanna:
ViT-DAE: Transformer-driven Diffusion Autoencoder for Histopathology Image Analysis. CoRR abs/2304.01053 (2023) - [i8]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) - [i7]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) - [i6]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) - [i5]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
- [c2]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 - [i4]Saarthak Kapse, Srijan Das, Prateek Prasanna:
CD-Net: Histopathology Representation Learning using Pyramidal Context-Detail Network. CoRR abs/2203.15078 (2022) - [i3]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
- [c1]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 - [i2]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) - 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)
Coauthor Index
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