Literature DB >> 17904821

Hip cartilage thickness measurement accuracy improvement.

Yuanzhi Cheng1, Shuguo Wang, Takaharu Yamazaki, Jie Zhao, Yoshikazu Nakajima, Shinichi Tamura.   

Abstract

Accurate measurement of the distance separating two adjacent sheet structures, such as femoral cartilage and acetabular cartilage in the hip joint is important in evaluation of osteoarthritis. A new method, insensitive to the influence of adjacent sheet structures, was developed to improve the accuracy of hip cartilage thickness measurement. A theoretical simulation for investigating the influence of adjacent sheet structures on the accuracy of cartilage thickness measurement in MR images was performed. The thickness is defined as the distance between zero-crossings of the second directional derivatives along the sheet surface normal direction. The simulation measurement showed considerable underestimation in thickness measurement occurred due to the influence of the adjacent sheet. A new method based on a model of the MR imaging process to eliminate the influence of adjacent sheet structure was developed and tested using phantoms and two cadaveric human hip joint MR scans. The new method reduced the influence of the adjacent sheet structure was more accurate than the conventional method for measuring hip cartilage thickness.

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Year:  2007        PMID: 17904821     DOI: 10.1016/j.compmedimag.2007.08.001

Source DB:  PubMed          Journal:  Comput Med Imaging Graph        ISSN: 0895-6111            Impact factor:   4.790


  2 in total

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

Authors:  Pooneh R Tabrizi; Reza A Zoroofi; Futoshi Yokota; Takashi Nishii; Yoshinobu Sato
Journal:  Int J Comput Assist Radiol Surg       Date:  2015-10-20       Impact factor: 2.924

2.  Acetabular cartilage segmentation in CT arthrography based on a bone-normalized probabilistic atlas.

Authors:  Pooneh R Tabrizi; Reza A Zoroofi; Futoshi Yokota; Satoru Tamura; Takashi Nishii; Yoshinobu Sato
Journal:  Int J Comput Assist Radiol Surg       Date:  2014-07-23       Impact factor: 2.924

  2 in total

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