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Proceedings Paper

Knowledge-based segmentation of the heart from respiratory-gated CT datasets acquired without cardiac contrast-enhancement
Author(s): Joyoni Dey; Tin-Su Pan; David J. Choi; Mark Smyczynski; Hendrik Pretorius; Michael A. King
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Paper Abstract

Respiratory motion degrades image quality in PET and SPECT imaging. Patient specific information on the motion of structures such as the heart if obtained from CT slices from a dual-modality imaging system can be employed to compensate for motion during emission reconstruction. The CT datasets may not be contrast enhanced. Since each patient may have 100-120 coronal slices covering the heart, an automated but accurate segmentation of the heart is important. We developed and implemented an algorithm to segment the heart in non-contrast CT datasets. The algorithm has two steps. In the first step we place a truncated-ellipse curve on a mid-slice of the heart, optimize its pose, and then track the contour through the other slices of the same dataset. During the second step the contour points are drawn to the local edge points by minimizing an distance measure. The segmentation algorithm was tested on 10 patients and the boundaries were determined to be accurate to within 2 mm of the visually ascertained locations of the borders of the heart. The segmentation was automatic except for initial placement of the first truncated-ellipse and for having to re-initialize the contour for 3 patients for less than 3% (1-3 slices) of the coronal slices of the heart. These end-slices constituted less than 0.3% of the heart volume.

Paper Details

Date Published: 10 March 2006
PDF: 8 pages
Proc. SPIE 6144, Medical Imaging 2006: Image Processing, 614409 (10 March 2006); doi: 10.1117/12.655742
Show Author Affiliations
Joyoni Dey, Univ. of Massachusetts Medical School (United States)
Tin-Su Pan, M.D. Anderson Cancer Ctr., Univ. of Texas (United States)
David J. Choi, Univ. of Massachusetts Medical School (United States)
Mark Smyczynski, Univ. of Massachusetts Medical School (United States)
Hendrik Pretorius, Univ. of Massachusetts Medical School (United States)
Michael A. King, Univ. of Massachusetts Medical School (United States)


Published in SPIE Proceedings Vol. 6144:
Medical Imaging 2006: Image Processing
Joseph M. Reinhardt; Josien P. W. Pluim, Editor(s)

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