Morphology-based interslice interpolation on manual segmentations of joint bones and muscles in MRI

Yang, Zhengyi, Crozier, Stuart, Engstrom, Craig, Xia, Ying, Neubert, Ales, Brancato, Tania, Schwarz, Raphael, Lauer, Lars, Fripp, Jurgen, Chandra, Shekhar and Salvado, Olivier (2012). Morphology-based interslice interpolation on manual segmentations of joint bones and muscles in MRI. In: 2012 International Conference on Digital Image Computing Techniques and Applications (DICTA). 2012 International Conference on Digital Image Computing Techniques and Applications (DICTA), Fremantle, WA, Australia, (). 3-5 December 2012. doi:10.1109/DICTA.2012.6411678

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Author Yang, Zhengyi
Crozier, Stuart
Engstrom, Craig
Xia, Ying
Neubert, Ales
Brancato, Tania
Schwarz, Raphael
Lauer, Lars
Fripp, Jurgen
Chandra, Shekhar
Salvado, Olivier
Title of paper Morphology-based interslice interpolation on manual segmentations of joint bones and muscles in MRI
Conference name 2012 International Conference on Digital Image Computing Techniques and Applications (DICTA)
Conference location Fremantle, WA, Australia
Conference dates 3-5 December 2012
Proceedings title 2012 International Conference on Digital Image Computing Techniques and Applications (DICTA)
Journal name 2012 International Conference On Digital Image Computing Techniques and Applications (Dicta)
Place of Publication Piscataway, NJ, United States
Publisher IEEE
Publication Year 2012
Sub-type Fully published paper
DOI 10.1109/DICTA.2012.6411678
ISBN 9781467321808
9781467321792
Total pages 8
Collection year 2013
Language eng
Abstract/Summary This paper presents a validation study on the application of a novel interslice interpolation technique for musculoskeletal structure segmentation of articulated joints and muscles on human magnetic resonance imaging data. The interpolation technique is based on morphological shape-based interpolation combined with intensity based voxel classification. Shape-based interpolation in the absence of the original intensity image has been investigated intensively. However, in some applications of medical image analysis, the intensity image of the slice to be interpolated is available. For example, when manual segmentation is conducted on selected slices, the segmentation on those unselected slices can be obtained by interpolation. We proposed a two- step interpolation method to utilize both the shape information in the manual segmentation and local intensity information in the image. The method was tested on segmentations of knee, hip and shoulder joint bones and hamstring muscles. The results were compared with two existing interpolation methods. Based on the calculated Dice similarity coefficient and normalized error rate, the proposed method outperformed the other two methods.
Keyword Bones
Image segmentation
Interpolation
Joints
Manuals
Muscles
Shape
Q-Index Code E1
Q-Index Status Confirmed Code
Institutional Status UQ

 
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Created: Thu, 31 Jan 2013, 00:51:08 EST by Deborah Noon on behalf of School of Human Movement and Nutrition Sciences