Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/76409
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Type: Conference paper
Title: Semantic-based indexing of fetal anatomies from 3-D ultrasound data using global/semi-local context and sequential sampling
Author: Carneiro, G.
Amat, F.
Georgescu, B.
Good, S.
Comaniciu, D.
Citation: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2008: CVPR 2008
Publisher: IEEE Computer Society
Publisher Place: Online
Issue Date: 2008
ISBN: 9781424422432
Conference Name: IEEE Conference on Computer Vision and Pattern Recognition (21st : 2008 : Anchorage, AK)
Statement of
Responsibility: 
Gustavo Carneiro, Fernando Amat, Bogdan Georgescu, Sara Good, Dorin Comaniciu
Abstract: The use of 3-D ultrasound data has several advantages over 2-D ultrasound for fetal biometric measurements, such as considerable decrease in the examination time, possibility of post-exam data processing by experts and the ability to produce 2-D views of the fetal anatomies in orientations that cannot be seen in common 2-D ultrasound exams. However, the search for standardized planes and the precise localization of fetal anatomies in ultrasound volumes are hard and time consuming processes even for expert physicians and sonographers. The relative low resolution in ultrasound volumes, small size of fetus anatomies and inter-volume position, orientation and size variability make this localization problem even more challenging. In order to make the plane search and fetal anatomy localization problems completely automatic, we introduce a novel principled probabilistic model that combines discriminative and generative classifiers with contextual information and sequential sampling. We implement a system based on this model, where the user queries consist of semantic keywords that represent anatomical structures of interest. After queried, the system automatically displays standardized planes and produces biometric measurements of the fetal anatomies. Experimental results on a held-out test set show that the automatic measurements are within the inter-user variability of expert users. It resolves for position, orientation and size of three different anatomies in less than 10 seconds in a dual-core computer running at 1.7 GHz.
Description: Extent: 8p.
Rights: ©2008 IEEE
RMID: 0020114350
DOI: 10.1109/CVPR.2008.4587358
Appears in Collections:Computer Science publications

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