34 citations · 42 across the 14 of their papers we have counts for
6 papers · 1 filter
Reliability of deep learning models for anatomical landmark detection: The role of inter-rater variability
Soorena Salari, Hassan Rivaz, Yiming Xiao
Automated detection of anatomical landmarks plays a crucial role in many diagnostic and surgical applications. Progresses in deep learning (DL) methods have resulted in significant…
CABLD: Contrast-Agnostic Brain Landmark Detection with Consistency-Based Regularization
Soorena Salari, Arash Harirpoush, Hassan Rivaz +1
Anatomical landmark detection in medical images is essential for various clinical and research applications, including disease diagnosis and surgical planning. However, manual land…
BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models
Taha Koleilat, Hojat Asgariandehkordi, Hassan Rivaz +1
Recent advancements in vision-language models (VLMs), such as CLIP, have demonstrated substantial success in self-supervised representation learning for vision tasks. However, effe…
MedCLIP-SAMv2: Towards Universal Text-Driven Medical Image Segmentation
Taha Koleilat, Hojat Asgariandehkordi, Hassan Rivaz +1
Segmentation of anatomical structures and pathological regions in medical images is essential for modern clinical diagnosis, disease research, and treatment planning. While signifi…
MedCLIP-SAM: Bridging Text and Image Towards Universal Medical Image Segmentation
Taha Koleilat, Hojat Asgariandehkordi, Hassan Rivaz +1
Medical image segmentation of anatomical structures and pathology is crucial in modern clinical diagnosis, disease study, and treatment planning. To date, great progress has been m…
Joint enhancement of automatic chest X-ray diagnosis and radiological gaze prediction with multi-stage cooperative learning
Zirui Qiu, Hassan Rivaz, Yiming Xiao
Purpose: As visual inspection is an inherent process during radiological screening, the associated eye gaze data can provide valuable insights into relevant clinical decisions. As…