Creating an atlas of normal tissue for pruning WSI patching through anomaly detection
Patching whole slide images (WSIs) is an important task in computational pathology. While
most of them are designed to classify or detect the presence of pathological lesions in a WSI …
most of them are designed to classify or detect the presence of pathological lesions in a WSI …
Tpmil: Trainable prototype enhanced multiple instance learning for whole slide image classification
Digital pathology based on whole slide images (WSIs) plays a key role in cancer diagnosis
and clinical practice. Due to the high resolution of the WSI and the unavailability of patch …
and clinical practice. Due to the high resolution of the WSI and the unavailability of patch …
Siamese Content-based Search Engine for a More Transparent Skin and Breast Cancer Diagnosis through Histological Imaging
Z Tabatabaei, A Colomer, JAO Moll… - arXiv preprint arXiv …, 2024 - arxiv.org
Computer Aid Diagnosis (CAD) has developed digital pathology with Deep Learning (DL)-
based tools to assist pathologists in decision-making. Content-Based Histopathological …
based tools to assist pathologists in decision-making. Content-Based Histopathological …
[HTML][HTML] Model-Agnostic Binary Patch Grouping for Bone Marrow Whole Slide Image Representation
Histopathology is the reference standard for pathology diagnosis, and has evolved with the
digitization of glass slides [ie, whole slide images (WSIs)]. While trained histopathologists …
digitization of glass slides [ie, whole slide images (WSIs)]. While trained histopathologists …
Domain-General Vs. Domain-Specific Pre-Trained Models Binary Patch Grouping for Improved WSI Representation
Histopathology is considered the reference standard for making a diagnosis in pathology.
The advent of whole slide images (WSIs), digitized glass slides, has transformed this field …
The advent of whole slide images (WSIs), digitized glass slides, has transformed this field …