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Sandra Simon Halliburton

dblp:06/65 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2000
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1Graphics, computer vision, multimedia, augmented reality and games · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Medical and health informatics · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Medical and health informatics › medical imaging
medical image analysis
0.012000
Multi-Modality Model-Based Registration in the Cardiac Domain · CVPR 2000
Medical and health informatics › medical imaging › medical image analysis
multi-modal image registration
0.012000
Multi-Modality Model-Based Registration in the Cardiac Domain · CVPR 2000
Medical and health informatics › medical imaging
cardiac imaging
0.012000
Multi-Modality Model-Based Registration in the Cardiac Domain · CVPR 2000

Methods — techniques the papers use, named apart from their topics

model-based registration · 0.0contour segmentation · 0.0
YearPublicationVenuePosition
2000 Multi-Modality Model-Based Registration in the Cardiac Domain
abstract
Recent advances in CT technology have made possible the acquisition of high resolution images of the heart in which important anatomical features such as the coronary vessels are visible. The state of the art in MR Imaging techniques, on the other hand, typically provides lower resolution but can facilitate the differentiation of viable (healthy) cardiac tissue from infarcted (injured) tissue. The registration of CT and MR images of the same heart permit the association of anatomy with function. As an example, given an infarcted region, the coronary vessels responsible for irrigating that region may be isolated and targeted for treatment (e.g., coronary bypass). We demonstrate a software package, PROTEUS, which is capable of registering CT and MR images. Since the manifestation of cardiac tissue in the two modalities differs so greatly we rely on features to perform the matching. Specifically, we employ a model-based approach that relies on segmented contours delineating the inner and outer borders of the left ventricle (LV). Given these contours, our technique is completely automatic.
Thomas O'Donnell, Shmuel Aharon, Alok Gupta, Gareth Funka-Lea, Sandra Simon Halliburton
CVPR5