Automatic detection and segmentation of ground glass opacity nodules

Jinghao Zhou, Sukmoon Chang, Dimitris N. Metaxas, Binsheng Zhao, Lawrence H. Schwartz, Michelle S. Ginsberg

Research output: Chapter in Book/Report/Conference proceedingConference contribution

25 Scopus citations

Abstract

Ground Glass Opacity (GGO) is defined as hazy increased attenuation within a lung that is not associated with obscured underlying vessels. Since pure (nonsolid) 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 inter- or 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-NN whose distance measure is the Euclidean distance between the nonparametric density estimates of two examples. The detected GGO region is then automatically segmented by analyzing the 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 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.

Original languageEnglish (US)
Title of host publicationMedical Image Computing and Computer-Assisted Intervention, MICCAI 2006 - 9th International Conference, Proceedings
PublisherSpringer Verlag
Pages784-791
Number of pages8
ISBN (Print)3540447075, 9783540447078
DOIs
StatePublished - Jan 1 2006
Event9th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2006 - Copenhagen, Denmark
Duration: Oct 1 2006Oct 6 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4190 LNCS - I
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other9th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2006
CountryDenmark
CityCopenhagen
Period10/1/0610/6/06

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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    Zhou, J., Chang, S., Metaxas, D. N., Zhao, B., Schwartz, L. H., & Ginsberg, M. S. (2006). Automatic detection and segmentation of ground glass opacity nodules. In Medical Image Computing and Computer-Assisted Intervention, MICCAI 2006 - 9th International Conference, Proceedings (pp. 784-791). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4190 LNCS - I). Springer Verlag. https://doi.org/10.1007/11866565_96