12 citations · 24 across the 8 of their papers we have counts for
8 papers
Weakly Supervised Intracranial Aneurysm Detection and Segmentation in MR angiography via Multi-task UNet with Vesselness Prior
Erin Rainville, Amirhossein Rasoulian, Hassan Rivaz +1
Intracranial aneurysms (IAs) are abnormal dilations of cerebral blood vessels that, if ruptured, can lead to life-threatening consequences. However, their small size and soft contr…
Weakly Supervised Intracranial Hemorrhage Segmentation with YOLO and an Uncertainty Rectified Segment Anything Model
Pascal Spiegler, Amirhossein Rasoulian, Yiming Xiao
Intracranial hemorrhage (ICH) is a life-threatening condition that requires rapid and accurate diagnosis to improve treatment outcomes and patient survival rates. Recent advancemen…
Architecture Analysis and Benchmarking of 3D U-shaped Deep Learning Models for Thoracic Anatomical Segmentation
Arash Harirpoush, Amirhossein Rasoulian, Marta Kersten-Oertel +1
Recent rising interests in patient-specific thoracic surgical planning and simulation require efficient and robust creation of digital anatomical models from automatic medical imag…
Dense Error Map Estimation for MRI-Ultrasound Registration in Brain Tumor Surgery Using Swin UNETR
Soorena Salari, Amirhossein Rasoulian, Hassan Rivaz +1
Early surgical treatment of brain tumors is crucial in reducing patient mortality rates. However, brain tissue deformation (called brain shift) occurs during the surgery, rendering…
Weakly supervised segmentation of intracranial aneurysms using a novel 3D focal modulation UNet
Amirhossein Rasoulian, Arash Harirpoush, Soorena Salari +1
Accurate identification and quantification of unruptured intracranial aneurysms (UIAs) is crucial for the risk assessment and treatment of this cerebrovascular disorder. Current 2D…
Towards multi-modal anatomical landmark detection for ultrasound-guided brain tumor resection with contrastive learning
Soorena Salari, Amirhossein Rasoulian, Hassan Rivaz +1
Homologous anatomical landmarks between medical scans are instrumental in quantitative assessment of image registration quality in various clinical applications, such as MRI-ultras…
FocalErrorNet: Uncertainty-aware focal modulation network for inter-modal registration error estimation in ultrasound-guided neurosurgery
Soorena Salari, Amirhossein Rasoulian, Hassan Rivaz +1
In brain tumor resection, accurate removal of cancerous tissues while preserving eloquent regions is crucial to the safety and outcomes of the treatment. However, intra-operative t…
Weakly Supervised Intracranial Hemorrhage Segmentation using Head-Wise Gradient-Infused Self-Attention Maps from a Swin Transformer in Categorical Learning
Amirhossein Rasoulian, Soorena Salari, Yiming Xiao
Intracranial hemorrhage (ICH) is a life-threatening medical emergency that requires timely and accurate diagnosis for effective treatment and improved patient survival rates. While…