Visual Quantification of the Circle of Willis: An Automated Identification and Standardized Representation. (18th July 2016)

• Record Type: Journal Article
• Authors: Miao, H.; Mistelbauer, G.; Našel, C.; Gröller, M. E.
• Is Part Of: Computer graphics forum. Volume 36:Number 6(2017)
• Page Start: 393
• Page End: 404
• Publication Date: 2016-07-18
• Subjects: Circle of Willis -- medical imaging -- visualization -- information visualization -- visualization -- image segmentation -- image and video processing -- I.4.0 [Image Processing and Computer Vision]: General—Image processing software -- J.3 [Computer Applications]: Life and Medical Sciences‐Health; Computer graphics -- Periodicals; 006.605
• DOI: 10.1111/cgf.12988
• Languages: English
• ISSNs: 0167-7055

Abstract

Abstract : This paper presents a method for the visual quantification of cerebral arteries, known as the Circle of Willis (CoW). It is an arterial structure with the responsibility of supplying the brain with blood, however, dysfunctions can lead to strokes. The diagnosis of such a time‐critical/urgent event depends on the expertise of radiologists and the applied software tools. They use basic display methods of the volumetric data without any support of advanced image processing and visualization techniques. The goal of this paper is to present an automated method for the standardized description of cerebral arteries in stroke patients in order to provide an overview of the CoW's configuration. This novel representation provides visual indications of problematic areas as well as straightforward comparisons between multiple patients. Abstract: This paper presents a method for the visual quantification of cerebral arteries, known as the Circle of Willis (CoW). It is an arterial structure with the responsibility of supplying the brain with blood, however, dysfunctions can lead to strokes. The diagnosis of such a time‐critical/urgent event depends on the expertise of radiologists and the applied software tools. They use basic display methods of the volumetric data without any support of advanced image processing and visualization techniques. The goal of this paper is to present an automated method for the standardized description of cerebral arteries in stroke patients in order to provide an overview of the CoW's configuration. This novel representation provides visual indications of problematic areas as well as straightforward comparisons between multiple patients. Additionally, we offer a pipeline for extracting the CoW from Time‐of‐Flight Magnetic Resonance Angiography (TOF‐MRA) data sets together with an enumeration technique for labelling the arterial segments by detecting the main supplying arteries of the CoW. We evaluated the feasibility of our visual quantification approach in a study of 63 TOF‐MRA data sets and compared our findings to those of three radiologists. The obtained results demonstrate that our proposed techniques are effective in detecting the arteries and visually capturing the overall configuration of the CoW.