Segmentation of uterine fibroid ultrasound images using a dynamic statistical shape model in HIFU therapy.
Comput Med Imaging Graph
; 46 Pt 3: 302-14, 2015 Dec.
Article
in En
| MEDLINE
| ID: mdl-26459767
ABSTRACT
Segmenting the lesion areas from ultrasound (US) images is an important step in the intra-operative planning of high-intensity focused ultrasound (HIFU). However, accurate segmentation remains a challenge due to intensity inhomogeneity, blurry boundaries in HIFU US images and the deformation of uterine fibroids caused by patient's breathing or external force. This paper presents a novel dynamic statistical shape model (SSM)-based segmentation method to accurately and efficiently segment the target region in HIFU US images of uterine fibroids. For accurately learning the prior shape information of lesion boundary fluctuations in the training set, the dynamic properties of stochastic differential equation and Fokker-Planck equation are incorporated into SSM (referred to as SF-SSM). Then, a new observation model of lesion areas (named to RPFM) in HIFU US images is developed to describe the features of the lesion areas and provide a likelihood probability to the prior shape given by SF-SSM. SF-SSM and RPFM are integrated into active contour model to improve the accuracy and robustness of segmentation in HIFU US images. We compare the proposed method with four well-known US segmentation methods to demonstrate its superiority. The experimental results in clinical HIFU US images validate the high accuracy and robustness of our approach, even when the quality of the images is unsatisfactory, indicating its potential for practical application in HIFU therapy.
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Uterine Neoplasms
/
Ultrasonography
/
High-Intensity Focused Ultrasound Ablation
/
Leiomyoma
Type of study:
Diagnostic_studies
/
Prognostic_studies
Limits:
Female
/
Humans
Language:
En
Journal:
Comput Med Imaging Graph
Journal subject:
DIAGNOSTICO POR IMAGEM
Year:
2015
Document type:
Article
Publication country:
EEUU
/
ESTADOS UNIDOS
/
ESTADOS UNIDOS DA AMERICA
/
EUA
/
UNITED STATES
/
UNITED STATES OF AMERICA
/
US
/
USA