Paper
29 April 2016 Shape extraction in fetal ultrasound images using a Hermite-based filtering approach and a point distribution model
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Abstract
In this work we present a segmentation framework applied to fetal cardiac images. One of the main problems of the segmentation in ultrasound images is the speckle pattern that makes difficult to model images features such as edges and homogeneous regions. Our approach is based on two main processes. The first one aims at enhancing the ultrasound image using a noise reduction scheme. The Hermite transform is used for this purpose. In the second process a Point Distribution Model (PDM), previously trained, is used for the segmentation of the desired object. The filtering process is then employed before the segmentation stage with the aim of improving the results. The obtained result in the filtering process is used as a way to make more robust the segmentation stage. We evaluate the proposed method in the segmentation of the left ventricle of fetal ultrasound data. Different metrics are used to validate and compare the performance with other methods applied to fetal echocardiographic images.
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Lorena Vargas-Quintero, Boris Escalante-Ramírez, Lisbeth Camargo Marín, Mario Guzmán Huerta, Fernando Arámbula Cosio, and Héctor Borboa "Shape extraction in fetal ultrasound images using a Hermite-based filtering approach and a point distribution model", Proc. SPIE 9896, Optics, Photonics and Digital Technologies for Imaging Applications IV, 98961G (29 April 2016); https://doi.org/10.1117/12.2227950
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Cited by 1 scholarly publication.
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KEYWORDS
Image segmentation

Image segmentation

Image filtering

Image filtering

Fetus

Ultrasonography

Speckle

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