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

Misael Reyes López; Fernando Arámbula Cosío; Boris Escalante-Ramírez; Jimena Olveres

doi:10.1117/12.2511411

21 December 2018 Shape model and Hermite features for the segmentation of the cerebellum in fetal ultrasound

Misael Reyes López, Fernando Arámbula Cosío, Boris Escalante-Ramírez, Jimena Olveres

Proceedings Volume 10975, 14th International Symposium on Medical Information Processing and Analysis; 1097514 (2018) https://doi.org/10.1117/12.2511411
Event: 14th International Symposium on Medical Information Processing and Analysis, 2018, Mazatlán, Mexico

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.

Citation Download Citation

Misael Reyes López, Fernando Arámbula Cosío, Boris Escalante-Ramírez, and Jimena Olveres "Shape model and Hermite features for the segmentation of the cerebellum in fetal ultrasound", Proc. SPIE 10975, 14th International Symposium on Medical Information Processing and Analysis, 1097514 (21 December 2018); https://doi.org/10.1117/12.2511411

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