From the 1 of 4 linked papers with an AI index.
4 papers
Parameter-efficient Prompt Tuning of Vision Foundation Model With Adaptive Focal Loss for Interpretable MCI Screening
Javad Khoramdel, Farhad Hoseyni, Amirhossein Nikoofard
The paper introduces a lightweight method that adapts a frozen vision model using learnable prompt tokens and an adaptive focal loss to detect mild cognitive impairment from drawin…
CT Scans As Video: Efficient Intracranial Hemorrhage Detection Using Multi-Object Tracking
Amirreza Parvahan, Mohammad Hoseyni, Javad Khoramdel +1
Automated analysis of volumetric medical imaging on edge devices is severely constrained by the high memory and computational demands of 3D Convolutional Neural Networks (CNNs). Th…
Hemorica: A Comprehensive CT Scan Dataset for Automated Brain Hemorrhage Classification, Segmentation, and Detection
Kasra Davoodi, Mohammad Hoseyni, Javad Khoramdel +5
Timely diagnosis of Intracranial hemorrhage (ICH) on Computed Tomography (CT) scans remains a clinical priority, yet the development of robust Artificial Intelligence (AI) solution…
Benchmarking Class Activation Map Methods for Explainable Brain Hemorrhage Classification on Hemorica Dataset
Z. Rafati, M. Hoseyni, J. Khoramdel +1
Explainable Artificial Intelligence (XAI) has become an essential component of medical imaging research, aiming to increase transparency and clinical trust in deep learning models.…