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Proceedings Paper

Automated lung tumor segmentation for whole body PET volume based on novel downhill region growing
Author(s): Cherry Ballangan; Xiuying Wang; Stefan Eberl; Michael Fulham; Dagan Feng
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Paper Abstract

We propose an automated lung tumor segmentation method for whole body PET images based on a novel downhill region growing (DRG) technique, which regards homogeneous tumor hotspots as 3D monotonically decreasing functions. The method has three major steps: thoracic slice extraction with K-means clustering of the slice features; hotspot segmentation with DRG; and decision tree analysis based hotspot classification. To overcome the common problem of leakage into adjacent hotspots in automated lung tumor segmentation, DRG employs the tumors' SUV monotonicity features. DRG also uses gradient magnitude of tumors' SUV to improve tumor boundary definition. We used 14 PET volumes from patients with primary NSCLC for validation. The thoracic region extraction step achieved good and consistent results for all patients despite marked differences in size and shape of the lungs and the presence of large tumors. The DRG technique was able to avoid the problem of leakage into adjacent hotspots and produced a volumetric overlap fraction of 0.61 ± 0.13 which outperformed four other methods where the overlap fraction varied from 0.40 ± 0.24 to 0.59 ± 0.14. Of the 18 tumors in 14 NSCLC studies, 15 lesions were classified correctly, 2 were false negative and 15 were false positive.

Paper Details

Date Published: 12 March 2010
PDF: 8 pages
Proc. SPIE 7623, Medical Imaging 2010: Image Processing, 76233O (12 March 2010); doi: 10.1117/12.844032
Show Author Affiliations
Cherry Ballangan, The Univ. of Sydney (Australia)
Xiuying Wang, The Univ. of Sydney (Australia)
Stefan Eberl, The Univ. of Sydney (Australia)
Royal Prince Alfred Hospital (Australia)
Michael Fulham, The Univ. of Sydney (Australia)
Royal Prince Alfred Hospital (Australia)
Dagan Feng, The Univ. of Sydney (Australia)
Hong Kong Polytechnic Univ. (Hong Kong, China)

Published in SPIE Proceedings Vol. 7623:
Medical Imaging 2010: Image Processing
Benoit M. Dawant; David R. Haynor, Editor(s)

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