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Model-based segmentation of aortic ultrasound images (CROSBI ID 575285)

Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija

Kalinić, Hrvoje ; Lončarić, Sven ; Čikeš, Maja ; Miličić, Davor ; Bijnens, Bart Model-based segmentation of aortic ultrasound images // Proceedings of the Seventh Int'l Symposium on Image and Signal Processing and Analysis / Lončarić, Sven ; Ramponi, Gianni ; Seršić, Damir (ur.). Zagreb: Sveučilište u Zagrebu, 2011. str. 739-743

Podaci o odgovornosti

Kalinić, Hrvoje ; Lončarić, Sven ; Čikeš, Maja ; Miličić, Davor ; Bijnens, Bart

engleski

Model-based segmentation of aortic ultrasound images

Morphological features of the aortic outflow ultrasound images are used in clinical practice for diagnosis of cardiovascular diseases. While feature extraction can be done manually, it is very time consuming. Segmentation is an important step in image interpretation, analysis, and quantification of the objects within a scene. In this work, we propose a novel method for the automatic segmentation of aortic outflow profiles based on a segmentation technique that incorporates a prior knowledge about the object shape in the form of the shape boundary model. The proposed model-based method utilizes a series of image analysis steps including image registration and a modification of the RANSAC algorithm to deal with noise and other artifacts in the image acquisition process. The experimental validation is done on a set of 67 patients and is compared to manual segmentation by an expert cardiologist. The proposed method has shown high correlation with results obtained by the expert cardiologist.

ultrasound; aortic images; model-based segmentation; harmonic decomposition

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Podaci o prilogu

739-743.

2011.

objavljeno

Podaci o matičnoj publikaciji

Proceedings of the Seventh Int'l Symposium on Image and Signal Processing and Analysis

Lončarić, Sven ; Ramponi, Gianni ; Seršić, Damir

Zagreb: Sveučilište u Zagrebu

Podaci o skupu

ISPA 2011

predavanje

04.09.2011-06.09.2011

Dubrovnik, Hrvatska

Povezanost rada

Elektrotehnika, Računarstvo, Kliničke medicinske znanosti