Prateek Prasanna
21 papers · 2021–2026 · 8 conferences · across top CS/AI conferences
Achievements
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Conferences
CVPR (6)
MICCAI (5)
ECCV (2)
ICCV (2)
MIDL (2)
WACV (2)
ICLR (1)
NIPS (1)
Top co-authors
Keywords
medical imaging
(5)
self-supervised learning
(3)
contrastive learning
(2)
multiple instance learning
(2)
diffusion model
(2)
disease progression
(2)
histopathology image
(2)
whole slide image
(2)
latent diffusion model
(2)
digital pathology
(2)
image generation
(1)
image synthesis
(1)
text-to-image generation
(1)
medical image segmentation
(1)
multimodal learning
(1)
temporal modeling
(1)
adversarial learning
(1)
data augmentation
(1)
vision transformer
(1)
clinical outcome prediction
(1)
Papers
PEaRL: Pathway-Enhanced Representation Learning for Gene and Pathway Expression Prediction from Histology
WACV 2026
GECKO: Gigapixel Vision-Concept Contrastive Pretraining in Histopathology
ICCV 2025
TopoCellGen: Generating Histopathology Cell Topology with a Diffusion Model
CVPR 2025
Enhancing SAM with Efficient Prompting and Preference Optimization for Semi-supervised Medical Image Segmentation
CVPR 2025
ZoomLDM: Latent Diffusion Model for Multi-scale Image Generation
CVPR 2025
Pathology Image Compression with Pre-trained Autoencoders
MICCAI 2025
GazeDiff: A radiologist visual attention guided diffusion model for zero-shot disease classification
MIDL 2024
Hard Negative Sample Mining for Whole Slide Image Classification
MICCAI 2024
HoG-Net: Hierarchical Multi-Organ Graph Network for Head and Neck Cancer Recurrence Prediction from CT Images
MICCAI 2024
MetaStain: Stain-generalizable Meta-learning for Cell Segmentation and Classification with Limited Exemplars
MICCAI 2024
Semi-Supervised Contrastive VAE for Disentanglement of Digital Pathology Images
MICCAI 2024
SI-MIL: Taming Deep MIL for Self-Interpretability in Gigapixel Histopathology
CVPR 2024
Learned Representation-Guided Diffusion Models for Large-Image Generation
CVPR 2024
PathLDM: Text Conditioned Latent Diffusion Model for Histopathology
WACV 2024
Topology-Aware Uncertainty for Image Segmentation
NIPS 2023
Enhancing Modality-Agnostic Representations via Meta-Learning for Brain Tumor Segmentation
ICCV 2023
Learning to Segment from Noisy Annotations: A Spatial Correction Approach
ICLR 2023
RadioTransformer: A Cascaded Global-Focal Transformer for Visual Attention-Guided Disease Classification
ECCV 2022
Learning Topological Interactions for Multi-Class Medical Image Segmentation
ECCV 2022
Temporal Context Matters: Enhancing Single Image Prediction With Disease Progression Representations
CVPR 2022
Predicting COVID-19 Lung Infiltrate Progression on Chest Radiographs Using Spatio-temporal LSTM based Encoder-Decoder Network
MIDL 2021