Literature DB >> 18941839

A computer-assisted system for diagnostic workstations: automated bone labeling for CT images.

Satoru Furuhashi1, Katsumi Abe, Motoichiro Takahashi, Takuya Aizawa, Takashi Shizukuishi, Masakuni Sakaguchi, Toshiya Maebayashi, Ikue Tanaka, Mitsuhiro Narata, Yasuo Sasaki.   

Abstract

Although accurate information on thoracolumbar bone structure is essential when computed tomography (CT) images are examined, there is no automated method of labeling all the vertebrae and ribs on a CT scan. We are developing a computer-aided diagnosis system that labels ribs and thoracolumbar vertebrae automatically and have evaluated its accuracy. A candidate bone was extracted from the CT image volume data by pixel thresholding and connectivity analysis. All non-bony anatomical structures were removed using a linear discriminate of distribution of CT values and anatomical characteristics. The vertebrae were separated from the ribs on the basis of their distances from the centers of the vertebral bodies. Finally, the thoracic cage and lumbar vertebrae were extracted, and each vertebra was labeled with its own anatomical number by histogram analysis along the craniocaudal midline. The ribs were labeled in a similar manner, based on location data. Twenty-three cases were used for accuracy comparison between our method and the radiologist's. The automated labeling of the thoracolumbar vertebrae was concordant with the judgments of the radiologist in all cases, and all but the first and second ribs were labeled correctly. These two ribs were frequently misidentified, presumably because of pericostal anatomical clutter or high densities of contrast material in the injected veins. We are confident that this system can contribute usefully as part of a picture archiving and communication system workstation, though further technical improvement is required for identification of the upper ribs.

Entities:  

Mesh:

Year:  2008        PMID: 18941839      PMCID: PMC3043723          DOI: 10.1007/s10278-008-9162-8

Source DB:  PubMed          Journal:  J Digit Imaging        ISSN: 0897-1889            Impact factor:   4.056


  5 in total

1.  Automatic rib segmentation and labeling in computed tomography scans using a general framework for detection, recognition and segmentation of objects in volumetric data.

Authors:  Joes Staal; Bram van Ginneken; Max A Viergever
Journal:  Med Image Anal       Date:  2006-11-27       Impact factor: 8.545

2.  Using mathematical morphology for the anatomical labeling of vertebrae from 3D CT-scan images.

Authors:  Benoît Naegel
Journal:  Comput Med Imaging Graph       Date:  2007-02-12       Impact factor: 4.790

3.  Counting ribs on chest CT.

Authors:  M Bhalla; D I McCauley; C Golimbu; B S Leitman; D P Naidich
Journal:  J Comput Assist Tomogr       Date:  1990 Jul-Aug       Impact factor: 1.826

4.  Counting ribs on chest CT scans: the easiest way.

Authors:  Y Kurihara; Y Nakajima; T Ishikawa; J R Galvin
Journal:  AJR Am J Roentgenol       Date:  1995-08       Impact factor: 3.959

5.  Rib counting on CT using the sternal approach.

Authors:  S J Kim; J G Im; S T Cho; S K Lee; K S Park; D Y Kim
Journal:  J Comput Assist Tomogr       Date:  1993 May-Jun       Impact factor: 1.826

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.