Literature DB >> 28285906

Vertebrae localization in CT using both local and global symmetry features.

Kijung Kim1, Seungkyu Lee2.   

Abstract

Automatic vertebrae segmentation and localization in CT images are essential in many medical treatments such as disease diagnosis and surgical planning. However, vertebra is one of the most complex organs to locate precisely due to its complex shape, deformation and occlusion by other organs. In this paper, we propose to incorporate local appearance features with global translational symmetry and local reflection symmetry features. Symmetrical structure of each vertebra provides strong cue for accurate localization. In order to efficiently investigate 3-dimensional reflection symmetry in CT images, we propose a Sphere Surface Expansion method and iterative optimization framework. Quantitative and qualitative evaluations show that the proposed method outperforms existing localization method.
Copyright © 2017 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Spine localization; Symmetry detection; Vertebrae

Mesh:

Year:  2017        PMID: 28285906     DOI: 10.1016/j.compmedimag.2017.02.002

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


  4 in total

1.  Automated Segmentation of Tissues Using CT and MRI: A Systematic Review.

Authors:  Leon Lenchik; Laura Heacock; Ashley A Weaver; Robert D Boutin; Tessa S Cook; Jason Itri; Christopher G Filippi; Rao P Gullapalli; James Lee; Marianna Zagurovskaya; Tara Retson; Kendra Godwin; Joey Nicholson; Ponnada A Narayana
Journal:  Acad Radiol       Date:  2019-08-10       Impact factor: 3.173

2.  Automatic Lumbar MRI Detection and Identification Based on Deep Learning.

Authors:  Yujing Zhou; Yuan Liu; Qian Chen; Guohua Gu; Xiubao Sui
Journal:  J Digit Imaging       Date:  2019-06       Impact factor: 4.056

3.  Automatic Lumbar Spine Tracking Based on Siamese Convolutional Network.

Authors:  Yuan Liu; Xiubao Sui; Chengwei Liu; Xiaodong Kuang; Yong Hu
Journal:  J Digit Imaging       Date:  2020-04       Impact factor: 4.056

4.  Fast and Accurate Craniomaxillofacial Landmark Detection via 3D Faster R-CNN.

Authors:  Xiaoyang Chen; Chunfeng Lian; Hannah H Deng; Tianshu Kuang; Hung-Ying Lin; Deqiang Xiao; Jaime Gateno; Dinggang Shen; James J Xia; Pew-Thian Yap
Journal:  IEEE Trans Med Imaging       Date:  2021-11-30       Impact factor: 10.048

  4 in total

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