title: Segmentation of renal parenchymal area from ultrasound images using level set evolution.
abstract: This paper presents a framework for segmentation of renal parenchymal area from ultrasound images based on a 2-step level set method. We used distance regularized level set evolution method to partition the kidney boundary, followed by region-scalable fitting energy minimization method to segment the kidney collecting system, and determined renal parenchymal area by subtracting the area of the collecting system from the gross kidney area. The proposed method demonstrated excellent validity and low inter-observer variability.
authors.forename: Huixuan
authors.initials: H
authors.lastname: Wang
authors.forename: Jose E
authors.initials: JE
authors.lastname: Pulido
authors.forename: Yihua
authors.initials: Y
authors.lastname: Song
authors.forename: Susan L
authors.initials: SL
authors.lastname: Furth
authors.forename: Changhe
authors.initials: C
authors.lastname: Tu
authors.forename: Caiming
authors.initials: C
authors.lastname: Zhang
authors.forename: Chunming
authors.initials: C
authors.lastname: Li
authors.forename: Gregory E
authors.initials: GE
authors.lastname: Tasian
mesh_terms: D000465:Algorithms; D006801:Humans; D007091:Image Processing, Computer-Assisted; D007223:Infant; D007668:Kidney / Q000000981:diagnostic imaging*; D007685:Kidney Tubules, Collecting / Q000000981:diagnostic imaging; D008297:Male; D015588:Observer Variation; D015203:Reproducibility of Results; D014463:Ultrasonography