Automatic segmentation of the diaphragm in non-contrast CT images

Raja Yalamanchili; Deepak Chittajallu; Paul Balanca; Balaji Tamarappoo; Daniel Berman; Damini Dey; Ioannis Kakadiaris

doi:10.1109/ISBI.2010.5490132

Automatic segmentation of the diaphragm in non-contrast CT images

Raja Yalamanchili, Deepak Chittajallu, Paul Balanca, Balaji Tamarappoo, Daniel Berman, Damini Dey, Ioannis Kakadiaris

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

10 Scopus citations

Abstract

The diaphragm is a thin double-domed muscle that separates the thoracic and abdominal cavities. An accurate delineation of the diaphragm surface will be useful in providing a good region of interest for segmentation problems pertaining to the thoracic and abdominal cavities. In this paper, we present a fully automatic 3D graph-based method for the segmentation of the diaphragm in non-contrast CT data. In particular, we reformulate the diaphragm segmentation problem as an optimal surface segmentation problem in a volumetric graph. Comparison of the results obtained using our method with manual segmentations performed by an expert on non-contrast cardiac CT scans of 7 randomly selected patients indicated an overlap of 94.20 ± 0.01%.

Original language	English (US)
Title of host publication	2010 7th IEEE International Symposium on Biomedical Imaging
Subtitle of host publication	From Nano to Macro, ISBI 2010 - Proceedings
Pages	900-903
Number of pages	4
DOIs	https://doi.org/10.1109/ISBI.2010.5490132
State	Published - 2010
Event	7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2010 - Rotterdam, Netherlands Duration: Apr 14 2010 → Apr 17 2010

Publication series

Name	2010 7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2010 - Proceedings

Other

Other	7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2010
Country/Territory	Netherlands
City	Rotterdam
Period	4/14/10 → 4/17/10

Keywords

Diaphragm segmentation
Max closure
Non-contrast CT

ASJC Scopus subject areas

Biomedical Engineering
Radiology Nuclear Medicine and imaging

Access to Document

10.1109/ISBI.2010.5490132

Cite this

Yalamanchili, R., Chittajallu, D., Balanca, P., Tamarappoo, B., Berman, D., Dey, D., & Kakadiaris, I. (2010). Automatic segmentation of the diaphragm in non-contrast CT images. In 2010 7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2010 - Proceedings (pp. 900-903). [5490132] (2010 7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2010 - Proceedings). https://doi.org/10.1109/ISBI.2010.5490132

Automatic segmentation of the diaphragm in non-contrast CT images. / Yalamanchili, Raja; Chittajallu, Deepak; Balanca, Paul et al.

2010 7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2010 - Proceedings. 2010. p. 900-903 5490132 (2010 7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2010 - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Yalamanchili, R, Chittajallu, D, Balanca, P, Tamarappoo, B, Berman, D, Dey, D & Kakadiaris, I 2010, Automatic segmentation of the diaphragm in non-contrast CT images. in 2010 7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2010 - Proceedings., 5490132, 2010 7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2010 - Proceedings, pp. 900-903, 7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2010, Rotterdam, Netherlands, 4/14/10. https://doi.org/10.1109/ISBI.2010.5490132

Yalamanchili R, Chittajallu D, Balanca P, Tamarappoo B, Berman D, Dey D et al. Automatic segmentation of the diaphragm in non-contrast CT images. In 2010 7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2010 - Proceedings. 2010. p. 900-903. 5490132. (2010 7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2010 - Proceedings). https://doi.org/10.1109/ISBI.2010.5490132

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abstract = "The diaphragm is a thin double-domed muscle that separates the thoracic and abdominal cavities. An accurate delineation of the diaphragm surface will be useful in providing a good region of interest for segmentation problems pertaining to the thoracic and abdominal cavities. In this paper, we present a fully automatic 3D graph-based method for the segmentation of the diaphragm in non-contrast CT data. In particular, we reformulate the diaphragm segmentation problem as an optimal surface segmentation problem in a volumetric graph. Comparison of the results obtained using our method with manual segmentations performed by an expert on non-contrast cardiac CT scans of 7 randomly selected patients indicated an overlap of 94.20 ± 0.01%.",

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AU - Dey, Damini

AU - Kakadiaris, Ioannis

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AB - The diaphragm is a thin double-domed muscle that separates the thoracic and abdominal cavities. An accurate delineation of the diaphragm surface will be useful in providing a good region of interest for segmentation problems pertaining to the thoracic and abdominal cavities. In this paper, we present a fully automatic 3D graph-based method for the segmentation of the diaphragm in non-contrast CT data. In particular, we reformulate the diaphragm segmentation problem as an optimal surface segmentation problem in a volumetric graph. Comparison of the results obtained using our method with manual segmentations performed by an expert on non-contrast cardiac CT scans of 7 randomly selected patients indicated an overlap of 94.20 ± 0.01%.

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Automatic segmentation of the diaphragm in non-contrast CT images

Abstract

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Keywords

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