Rajarsi Gupta

Orcid: 0000-0002-1577-8718

Affiliations:
  • Stony Brook University, Department of Biomedical Informatics, NY, USA
  • Stony Brook University Medical Center, Department of Pathology, NY, USA


According to our database1, Rajarsi Gupta authored at least 33 papers between 2017 and 2024.

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

Timeline

Legend:

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PhD thesis 
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Bibliography

2024
Decoding the visual attention of pathologists to reveal their level of expertise.
CoRR, 2024

2023
ChampKit: A framework for rapid evaluation of deep neural networks for patch-based histopathology classification.
Comput. Methods Programs Biomed., September, 2023

SI-MIL: Taming Deep MIL for Self-Interpretability in Gigapixel Histopathology.
CoRR, 2023

Attention De-sparsification Matters: Inducing Diversity in Digital Pathology Representation Learning.
CoRR, 2023

Open and reusable deep learning for pathology with WSInfer and QuPath.
CoRR, 2023

Halcyon - A Pathology Imaging and Feature analysis and Management System.
CoRR, 2023

Unsupervised Stain Decomposition via Inversion Regulation for Multiplex Immunohistochemistry Images.
Proceedings of the Medical Imaging with Deep Learning, 2023

Few Shot Hematopoietic Cell Classification.
Proceedings of the Medical Imaging with Deep Learning, 2023

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

Topology-Guided Multi-Class Cell Context Generation for Digital Pathology.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
AI and Pathology: Steering Treatment and Predicting Outcomes.
CoRR, 2022

Evaluating histopathology transfer learning with ChampKit.
CoRR, 2022

Federated Learning for the Classification of Tumor Infiltrating Lymphocytes.
CoRR, 2022

Gigapixel Whole-Slide Images Classification Using Locally Supervised Learning.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

Predicting the Visual Attention of Pathologists Evaluating Whole Slide Images of Cancer.
Proceedings of the Medical Optical Imaging and Virtual Microscopy Image Analysis, 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

Visual Attention Analysis Of Pathologists Examining Whole Slide Images Of Prostate Cancer.
Proceedings of the 19th IEEE International Symposium on Biomedical Imaging, 2022

2021
Multi-Class Cell Detection Using Spatial Context Representation.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

A Joint Spatial and Magnification Based Attention Framework for Large Scale Histopathology Classification.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021

2020
Dataset of Segmented Nuclei in Hematoxylin and Eosin Stained Histopathology Images of 10 Cancer Types.
CoRR, 2020

Weakly-Supervised Deep Stain Decomposition for Multiplex IHC Images.
Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020

Automated Assessment of the Curliness of Collagen Fiber in Breast Cancer.
Proceedings of the Computer Vision - ECCV 2020 Workshops, 2020

2019
Sparse autoencoder for unsupervised nucleus detection and representation in histopathology images.
Pattern Recognit., 2019

Learning from Thresholds: Fully Automated Classification of Tumor Infiltrating Lymphocytes for Multiple Cancer Types.
CoRR, 2019

Utilizing Automated Breast Cancer Detection to Identify Spatial Distributions of Tumor Infiltrating Lymphocytes in Invasive Breast Cancer.
CoRR, 2019

Label Super Resolution with Inter-Instance Loss.
CoRR, 2019

Pancreatic Cancer Detection in Whole Slide Images Using Noisy Label Annotations.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019

Robust Histopathology Image Analysis: To Label or to Synthesize?
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Delivering Scalable Deep Learning to Research with Bridges-AI.
Proceedings of the High Performance Computing - 6th Latin American Conference, 2019

From Whole Slide Tissues to Knowledge: Mapping Sub-cellular Morphology of Cancer.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2019

2018
Disease phenotyping using deep learning: A diabetes case study.
CoRR, 2018

Methods for Segmentation and Classification of Digital Microscopy Tissue Images.
CoRR, 2018

2017
Unsupervised Histopathology Image Synthesis.
CoRR, 2017


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