4 papers
Scaling up fine-grained intracranial vessel annotations in computed tomography angiography
Chu-Hsuan Lin, Alberto Mario Ceballos-Arroyo, Jisoo Kim +4
In this work, we present SemanticVessel, a dataset for fine-grained brain vessel segmentation in computed tomography angiography scans. Based on the detailed contrast provided by d…
Robust automatic brain vessel segmentation in 3D CTA scans using dynamic 4D-CTA data
Alberto Mario Ceballos-Arroyo, Shrikanth M. Yadav, Chu-Hsuan Lin +4
In this study, we develop a novel methodology for annotating the brain vasculature using dynamic 4D-CTA head scans. By using multiple time points from dynamic CTA acquisitions, we…
Automated anatomy-based post-processing reduces false positives and improved interpretability of deep learning intracranial aneurysm detection
Jisoo Kim, Chu-Hsuan Lin, Alberto Ceballos-Arroyo +6
Introduction: Deep learning (DL) models can help detect intracranial aneurysms on CTA, but high false positive (FP) rates remain a barrier to clinical translation, despite improvem…
Dynamic-Computed Tomography Angiography for Cerebral Vessel Templates and Segmentation
Shrikanth Yadav, Jisoo Kim, Geoffrey Young +1
Background: Computed Tomography Angiography (CTA) is crucial for cerebrovascular disease diagnosis. Dynamic CTA is a type of imaging that captures temporal information about the We…