18 citations · 42 across the 18 of their papers we have counts for
18 papers
SPLICE -- Streamlining Digital Pathology Image Processing
Areej Alsaafin, Peyman Nejat, Abubakr Shafique +4
Digital pathology and the integration of artificial intelligence (AI) models have revolutionized histopathology, opening new opportunities. With the increasing availability of Whol…
Foundation Models and Information Retrieval in Digital Pathology
H. R. Tizhoosh
The paper reviews the state-of-the-art of foundation models, LLMs, generative AI, information retrieval and CBIR in digital pathology
Training Artificial Neural Networks by Coordinate Search Algorithm
Ehsan Rokhsatyazdi, Shahryar Rahnamayan, Sevil Zanjani Miyandoab +2
Training Artificial Neural Networks poses a challenging and critical problem in machine learning. Despite the effectiveness of gradient-based learning methods, such as Stochastic G…
On Image Search in Histopathology
H. R. Tizhoosh, Liron Pantanowitz
Pathology images of histopathology can be acquired from camera-mounted microscopes or whole slide scanners. Utilizing similarity calculations to match patients based on these image…
Selection of Distinct Morphologies to Divide & Conquer Gigapixel Pathology Images
Abubakr Shafique, Saghir Alfasly, Areej Alsaafin +3
Whole slide images (WSIs) are massive digital pathology files illustrating intricate tissue structures. Selecting a small, representative subset of patches from each WSI is essenti…
Creating an Atlas of Normal Tissue for Pruning WSI Patching Through Anomaly Detection
Peyman Nejat, Areej Alsaafin, Ghazal Alabtah +7
Patching gigapixel whole slide images (WSIs) is an important task in computational pathology. Some methods have been proposed to select a subset of patches as WSI representation fo…