25 citations · 59 across the 15 of their papers we have counts for
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Evaluating Pre-trained Convolutional Neural Networks and Foundation Models as Feature Extractors for Content-based Medical Image Retrieval
Amirreza Mahbod, Nematollah Saeidi, Sepideh Hatamikia +1
Medical image retrieval refers to the task of finding similar images for given query images in a database, with applications such as diagnosis support. While traditional medical im…
WCEbleedGen: A wireless capsule endoscopy dataset and its benchmarking for automatic bleeding classification, detection, and segmentation
Palak Handa, Manas Dhir, Amirreza Mahbod +4
Computer-based analysis of Wireless Capsule Endoscopy (WCE) is crucial. However, a medically annotated WCE dataset for training and evaluation of automatic classification, detectio…
Capsule Vision 2024 Challenge: Multi-Class Abnormality Classification for Video Capsule Endoscopy
Palak Handa, Amirreza Mahbod, Florian Schwarzhans +11
We present the Capsule Vision 2024 Challenge: Multi-Class Abnormality Classification for Video Capsule Endoscopy. It was virtually organized by the Research Center for Medical Imag…
Intensity Normalization Techniques and Their Effect on the Robustness and Predictive Power of Breast MRI Radiomics
Florian Schwarzhans, Geevarghese George, Lorena Escudero Sanchez +4
Radiomics analysis has emerged as a promising approach for extracting quantitative features from medical images to aid in cancer diagnosis and treatment. However, radiomics researc…
Leveraging Medical Foundation Model Features in Graph Neural Network-Based Retrieval of Breast Histopathology Images
Nematollah Saeidi, Hossein Karshenas, Bijan Shoushtarian +3
Breast cancer is the most common cancer type in women worldwide. Early detection and appropriate treatment can significantly reduce its impact. While histopathology examinations pl…