2 citations · 4 across the 4 of their papers we have counts for
5 papers
Automated Distinction of Intimal and Medial Intracranial Arterial Calcification from CT Head
Benjamin Jin, Maria del C. Valdés Hernández, Richard Bortsov +3
Intracranial arterial calcifications (IACs) are a common finding on clinical non-contrast enhanced head CT scans and are associated with neurovascular disease. Calcifications can o…
Calibrated Self-supervised Vision Transformers Improve Intracranial Arterial Calcification Segmentation from Clinical CT Head Scans
Benjamin Jin, Grant Mair, Joanna M. Wardlaw +1
Vision Transformers (ViTs) have gained significant popularity in the natural image domain but have been less successful in 3D medical image segmentation. Nevertheless, 3D ViTs are…
Pre-processing and quality control of large clinical CT head datasets for intracranial arterial calcification segmentation
Benjamin Jin, Maria del C. Valdés Hernández, Alessandro Fontanella +6
As a potential non-invasive biomarker for ischaemic stroke, intracranial arterial calcification (IAC) could be used for stroke risk assessment on CT head scans routinely acquired f…
Development of a Deep Learning Method to Identify Acute Ischemic Stroke Lesions on Brain CT
Alessandro Fontanella, Wenwen Li, Grant Mair +6
Computed Tomography (CT) is commonly used to image acute ischemic stroke (AIS) patients, but its interpretation by radiologists is time-consuming and subject to inter-observer vari…
Challenges of building medical image datasets for development of deep learning software in stroke
Alessandro Fontanella, Wenwen Li, Grant Mair +7
Despite the large amount of brain CT data generated in clinical practice, the availability of CT datasets for deep learning (DL) research is currently limited. Furthermore, the dat…