activity
20232025
most citedF2FLDM: Latent Diffusion Models with Histopathology Pre-Trained Embeddings for Unpaired Frozen Section to FFPE Translation

2 citations · 5 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CV2025

DuoFormer: Leveraging Hierarchical Representations by Local and Global Attention Vision Transformer

Xiaoya Tang, Bodong Zhang, Man Minh Ho +2

Despite the widespread adoption of transformers in medical applications, the exploration of multi-scale learning through transformers remains limited, while hierarchical representa…

cs.CV2024

SRA: A Novel Method to Improve Feature Embedding in Self-supervised Learning for Histopathological Images

Hamid Manoochehri, Bodong Zhang, Beatrice S. Knudsen +1

Self-supervised learning has become a cornerstone in various areas, particularly histopathological image analysis. Image augmentation plays a crucial role in self-supervised learni…

eess.IV2024

VIMs: Virtual Immunohistochemistry Multiplex staining via Text-to-Stain Diffusion Trained on Uniplex Stains

Shikha Dubey, Yosep Chong, Beatrice Knudsen +1

This paper introduces a Virtual Immunohistochemistry Multiplex staining (VIMs) model designed to generate multiple immunohistochemistry (IHC) stains from a single hematoxylin and e…

cs.CV2024

DuoFormer: Leveraging Hierarchical Visual Representations by Local and Global Attention

Xiaoya Tang, Bodong Zhang, Beatrice S. Knudsen +1

We here propose a novel hierarchical transformer model that adeptly integrates the feature extraction capabilities of Convolutional Neural Networks (CNNs) with the advanced represe…

eess.IV20241 cited

DISC: Latent Diffusion Models with Self-Distillation from Separated Conditions for Prostate Cancer Grading

Man M. Ho, Elham Ghelichkhan, Yosep Chong +3

Latent Diffusion Models (LDMs) can generate high-fidelity images from noise, offering a promising approach for augmenting histopathology images for training cancer grading models.…

eess.IV20242 cited

F2FLDM: Latent Diffusion Models with Histopathology Pre-Trained Embeddings for Unpaired Frozen Section to FFPE Translation

Man M. Ho, Shikha Dubey, Yosep Chong +2

The Frozen Section (FS) technique is a rapid and efficient method, taking only 15-30 minutes to prepare slides for pathologists' evaluation during surgery, enabling immediate decis…