An automatic method for ground glass opacity nodule detection and segmentation from CT studies Conference Paper


Authors: Zhou, J.; Chang, S.; Metaxas, D. N.; Zhao, B.; Ginsberg, M. S.; Schwartz, L. H.
Title: An automatic method for ground glass opacity nodule detection and segmentation from CT studies
Conference Title: 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06
Abstract: Ground Glass Opacity (GGO) is defined as hazy increased attenuation within a lung that is not associated with obscured underlying vessels. Since pure (non-solid) or mixed (partially solid) GGO at the thin-section CT are more likely to be malignant than those with solid opacity, early detection and treatment of GGO can improve a prognosis of lung cancer. However, due to indistinct boundaries and interor intra-observer variation, consistent manual detection and segmentation of GGO have proved to be problematic. In this paper, we propose a novel method for automatic detection and segmentation of GGO from chest CT images. For GGO detection, we develop a classifier by boosting K-Nearest Neighbor (K-NN), whose distance measure is the Euclidean distance between the nonparametric density estimates of two regions. The detected GGO region is then automatically segmented by analyzing the 3D texture likelihood map of the region. We applied our method to clinical chest CT volumes containing 10 GGO nodules. The proposed method detected all of the 10 nodules with only one false positive nodule. We also present the statistical validation of the proposed classifier for automatic GGO detection as well as very promising results for automatic GGO segmentation. The proposed method provides a new powerful tool for automatic detection as well as accurate and reproducible segmentation of GGO. © 2006 IEEE.
Keywords: image analysis; lung cancer; oncology; computerized tomography; image segmentation; statistical methods; chest ct images; ground glass opacity (ggo); k-nearest neighbor (k-nn)
Journal Title IEEE Engineering in Medicine and Biology Society. Conference Proceedings
Conference Dates: 2006 Aug 30-Sep 3
Conference Location: New York, NY
ISBN: 1557-170X
Publisher: IEEE  
Date Published: 2006-08-01
Start Page: 3062
End Page: 3065
Language: English
DOI: 10.1109/IEMBS.2006.260285
PROVIDER: scopus
DOI/URL:
Notes: --- - Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings - Annu Int Conf IEEE Eng Med Biol Proc - "Conference code: 69200" - "Cited By (since 1996): 3" - "Export Date: 4 June 2012" - "Art. No.: 4030078" - "CODEN: CEMBA" - 30 August 2006 through 3 September 2006 - "Source: Scopus"
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  1. Michelle S Ginsberg
    235 Ginsberg
  2. Lawrence H Schwartz
    306 Schwartz
  3. Binsheng Zhao
    55 Zhao