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Proceedings Paper

Shape model and Hermite features for the segmentation of the cerebellum in fetal ultrasound
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Paper Abstract

In this paper we propose a semi-automatic method to segment the fetal cerebellum in ultrasound images. The method is based on an active shape model which includes profiles of Hermite features. In order to fit the shape model we used a PCA of Hermite features. This model was tested on ultrasound images of the fetal brain taken from 20 pregnant women with gestational weeks varying from 18 to 24. Segmentation results compared to manual annotation show a mean Hausdorff distance of 6.85 mm using a conventional active shape model trained with gray profiles, and a mean Hausdorff distance of 5.67 mm using Hermite profiles. We conclude that the Hermite profile model is more robust in segmenting fetal cerebellum in ultrasound images.

Paper Details

Date Published: 21 December 2018
PDF: 10 pages
Proc. SPIE 10975, 14th International Symposium on Medical Information Processing and Analysis, 1097514 (21 December 2018); doi: 10.1117/12.2511411
Show Author Affiliations
Misael Reyes López, Univ. Nacional Autónoma de México (Mexico)
Fernando Arámbula Cosío, Univ. Nacional Autónoma de México (Mexico)
Boris Escalante-Ramírez, Univ. Nacional Autónoma de México (Mexico)
Jimena Olveres, Univ. Nacional Autónoma de México (Mexico)


Published in SPIE Proceedings Vol. 10975:
14th International Symposium on Medical Information Processing and Analysis
Eduardo Romero; Natasha Lepore; Jorge Brieva, Editor(s)

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