Acetabular Cartilage Segmentation in CT Arthrography Based on a Bone-normalized Probabilistic Atlas

Overview

Journal Int J Comput Assist Radiol Surg

Publisher Springer

Specialties General Surgery
Radiology

Date 2014 Jul 24

PMID 25051918

Citations 2

Authors

Pooneh R Tabrizi

Reza A Zoroofi

Futoshi Yokota

Satoru Tamura

Takashi Nishii

Yoshinobu Sato

Affiliations

Soon will be listed here.

Abstract

Purpose: Determination of acetabular cartilage loss in the hip joint is a clinically significant metric that requires image segmentation. A new semiautomatic method to segment acetabular cartilage in computed tomography (CT) arthrography scans was developed and tested.

Methods: A semiautomatic segmentation method was developed based on the combination of anatomical and statistical information. Anatomical information is identified using the pelvic bone position and the contact area between cartilage and bone. Statistical information is acquired from CT intensity modeling of acetabular cartilage and adjacent tissue structures. This method was applied to the identification of acetabular cartilages in 37 intra-articular CT arthrography scans.

Results: The semiautomatic anatomical-statistical method performed better than other segmentation methods. The semiautomatic method was effective in noisy scans and was able to detect damaged cartilage.

Conclusions: The new semiautomatic method segments acetabular cartilage by fully utilizing the statistical and anatomical information in CT arthrography datasets. This method for hip joint cartilage segmentation has potential for use in many clinical applications.

Citing Articles

Reliability of computer-assisted periacetabular osteotomy using a minimally invasive approach.

de Raedt S, Mechlenburg I, Stilling M, Romer L, Murphy R, Armand M Int J Comput Assist Radiol Surg. 2018; 13(12):2021-2028.

PMID: 29876786 DOI: 10.1007/s11548-018-1802-y.

Shape-based acetabular cartilage segmentation: application to CT and MRI datasets.

Tabrizi P, Zoroofi R, Yokota F, Nishii T, Sato Y Int J Comput Assist Radiol Surg. 2015; 11(7):1247-65.

PMID: 26487172 DOI: 10.1007/s11548-015-1313-z.

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