Pregled bibliografske jedinice broj: 525133
Model-based segmentation of aortic ultrasound images
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 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 525133 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Model-based segmentation of aortic ultrasound images
Autori
Kalinić, Hrvoje ; Lončarić, Sven ; Čikeš, Maja ; Miličić, Davor ; Bijnens, Bart
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Proceedings of the Seventh Int'l Symposium on Image and Signal Processing and Analysis
/ Lončarić, Sven ; Ramponi, Gianni ; Seršić, Damir - Zagreb : Sveučilište u Zagrebu, 2011, 739-743
Skup
ISPA 2011
Mjesto i datum
Dubrovnik, Hrvatska, 04.09.2011. - 06.09.2011
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
ultrasound; aortic images; model-based segmentation; harmonic decomposition
Sažetak
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.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika, Računarstvo, Kliničke medicinske znanosti
POVEZANOST RADA
Projekti:
036-0362214-1989 - Inteligentne metode obrade i analize slika (Lončarić, Sven, MZO ) ( CroRIS)
108-1081875-1993 - Otpornost na antitrombocitne lijekove u ishemijskoj bolesti srca i mozga (Miličić, Davor, MZOS ) ( CroRIS)
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb,
Medicinski fakultet, Zagreb,
Sveučilište u Zagrebu