6 citations · 6 across the 5 of their papers we have counts for
5 papers
Zero-Shot Whole Slide Image Retrieval in Histopathology Using Embeddings of Foundation Models
Saghir Alfasly, Ghazal Alabtah, Sobhan Hemati +2
We have tested recently published foundation models for histopathology for image retrieval. We report macro average of F1 score for top-1 retrieval, majority of top-3 retrievals, a…
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…
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…
When is a Foundation Model a Foundation Model
Saghir Alfasly, Peyman Nejat, Sobhan Hemati +13
Recently, several studies have reported on the fine-tuning of foundation models for image-text modeling in the field of medicine, utilizing images from online data sources such as…
OSRE: Object-to-Spot Rotation Estimation for Bike Parking Assessment
Saghir Alfasly, Zaid Al-huda, Saifullah Bello +3
Current deep models provide remarkable object detection in terms of object classification and localization. However, estimating object rotation with respect to other visual objects…