Saarthak Kapse

Orcid: 0000-0002-5426-4111

According to our database1, Saarthak Kapse authored at least 19 papers between 2020 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

2020
2021
2022
2023
2024
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Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
Attention De-sparsification Matters: Inducing diversity in digital pathology representation learning.
Medical Image Anal., 2024

Gen-SIS: Generative Self-augmentation Improves Self-supervised Learning.
CoRR, 2024

RankByGene: Gene-Guided Histopathology Representation Learning Through Cross-Modal Ranking Consistency.
CoRR, 2024

Histo-Diffusion: A Diffusion Super-Resolution Method for Digital Pathology with Comprehensive Quality Assessment.
CoRR, 2024

HoG-Net: Hierarchical Multi-organ Graph Network for Head and Neck Cancer Recurrence Prediction from CT Images.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024

Coca-Mil: Attention-Based Handcrafted-Deep Feature Fusion in Computational Pathology.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

SI-MIL: Taming Deep MIL for Self-Interpretability in Gigapixel Histopathology.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Learned Representation-Guided Diffusion Models for Large-Image Generation.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023
Role of stain normalization in computational pathology: use case in metastatic tissue classification.
Proceedings of the Medical Imaging 2023: Digital and Computational Pathology, 2023

SAM-Path: A Segment Anything Model for Semantic Segmentation in Digital Pathology.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023 Workshops, 2023

Prompt-MIL: Boosting Multi-instance Learning Schemes via Task-Specific Prompt Tuning.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

ViT-DAE: Transformer-Driven Diffusion Autoencoder for Histopathology Image Analysis.
Proceedings of the Deep Generative Models - Third MICCAI Workshop, 2023

CD-Net: Histopathology Representation Learning Using Context-Detail Transformer Network.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

Precise Location Matching Improves Dense Contrastive Learning in Digital Pathology.
Proceedings of the Information Processing in Medical Imaging, 2023

2022
CD-Net: Histopathology Representation Learning using Pyramidal Context-Detail Network.
CoRR, 2022

Shape-based tumor microenvironment analysis to differentiate non-small cell lung cancer subtypes: a radio-pathomic study.
Proceedings of the Medical Imaging 2022: Digital and Computational Pathology, 2022

Subtype-Specific Spatial Descriptors of Tumor-Immune Microenvironment are Prognostic of Survival in Lung Adenocarcinoma.
Proceedings of the 19th IEEE International Symposium on Biomedical Imaging, 2022

2021
TopoTxR: A Topological Biomarker for Predicting Treatment Response in Breast Cancer.
Proceedings of the Information Processing in Medical Imaging, 2021

2020
Predicting Mechanical Ventilation Requirement and Mortality in COVID-19 using Radiomics and Deep Learning on Chest Radiographs: A Multi-Institutional Study.
CoRR, 2020


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