Prostate segmentation in HIFU therapy.
Prostate segmentation in 3-D transrectal ultrasound images is an important step in the definition of the intra-operative planning of high intensity focused ultrasound (HIFU) therapy. This paper presents two main approaches for the semi-automatic methods based on discrete dynamic contour and optimal surface detection. They operate in 3-D and require a minimal user interaction. They are considered both alone or sequentially combined, with and without postregularization, and applied on anisotropic and isotropic volumes. Their performance, using different metrics, has been evaluated on a set of 28 3-D images by comparison with two expert delineations. For the most efficient algorithm, the symmetric average surface distance was found to be 0.77 mm.
Laboratoire Traitement du Signal et de l'Image, Inserm U642, Université de Rennes 1, F-35000 Rennes, France.
Carole
C
Garnier
Jean-Jacques
JJ
Bellanger
Ke
K
Wu
Huazhong
H
Shu
Nathalie
N
Costet
Romain
R
Mathieu
Renaud
R
de Crevoisier
Jean-Louis
JL
Coatrieux
D000465:Algorithms; D057086:High-Intensity Focused Ultrasound Ablation / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008297:Male; D010363:Pattern Recognition, Automated / Q000379:methods*; D011471:Prostatic Neoplasms / Q000000981:diagnostic imaging* / Q000601:surgery*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D025321:Surgery, Computer-Assisted / Q000379:methods*; D014463:Ultrasonography / Q000379:methods*