35 citations · 49 across the 8 of their papers we have counts for
5 papers · 1 filter
Structural Cycle GAN for Virtual Immunohistochemistry Staining of Gland Markers in the Colon
Shikha Dubey, Tushar Kataria, Beatrice Knudsen +1
With the advent of digital scanners and deep learning, diagnostic operations may move from a microscope to a desktop. Hematoxylin and Eosin (H&E) staining is one of the most freque…
To pretrain or not to pretrain? A case study of domain-specific pretraining for semantic segmentation in histopathology
Tushar Kataria, Beatrice Knudsen, Shireen Elhabian
Annotating medical imaging datasets is costly, so fine-tuning (or transfer learning) is the most effective method for digital pathology vision applications such as disease classifi…
Unsupervised Domain Adaptation for Medical Image Segmentation via Feature-space Density Matching
Tushar Kataria, Beatrice Knudsen, Shireen Elhabian
Semantic segmentation is a critical step in automated image interpretation and analysis where pixels are classified into one or more predefined semantically meaningful classes. Dee…
Stain Based Contrastive Co-training for Histopathological Image Analysis
Bodong Zhang, Beatrice Knudsen, Deepika Sirohi +2
We propose a novel semi-supervised learning approach for classification of histopathology images. We employ strong supervision with patch-level annotations combined with a novel co…
An attention-based multi-resolution model for prostate whole slide imageclassification and localization
Jiayun Li, Wenyuan Li, Arkadiusz Gertych +3
Histology review is often used as the `gold standard' for disease diagnosis. Computer aided diagnosis tools can potentially help improve current pathology workflows by reducing exa…