Optimizing lung volume segmentation by texture classification

Panayiotis Korfiatis, Alexandra Kazantzi, Christina Kalogeropoulou, Theodoros Petsas, Lena Costaridou

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

4 Scopus citations

Abstract

Accurate and automated Lung Field (LF) segmentation in volumetric computed tomography protocols is highly challenged by the presence of pathologies affecting lung borders, also affecting the performance of computer-aided diagnosis (CAD) schemes. In this work, a three-dimensional LF segmentation algorithm adapted to interstitial lung disease patterns (ILD) patterns is presented. The algorithm employs kmeans clustering followed by a filling operation to obtain an initial LF order estimate. The final LF border is obtained by an iterative support vector machine neighborhood labeling of border pixels based on 3D texture features. The proposed method is evaluated on a dataset of 10 cases spanning a range of ILD patterns such as ground glass, reticular, and honeycombing. The accuracy of the method is assessed using area overlap and shape differentiation metrics (dmean, drms', and dmax), by comparing automatically derived lung borders to manually traced ones by a radiologist, and further compared to a Gray Level Thresholding-based (GLT-based) method. The proposed method demonstrated the highest segmentation accuracy, overlap=0.942, dmean=1.835 mm, d rms=1.672 mm, and dmax =4.255 mm, which is statistically significant (two-tailed student's t test for paired data, p<0.0001) with respect to all metrics considered as compared to the the GLT-based method overlap=0.836, dmean=2.324 mm, drms=3.890 mm,and d max=2.946 mm. The proposed segmentation method could be used as an initial stage of a CAD scheme for ILD patterns.

Original languageEnglish (US)
Title of host publicationITAB 2010 - 10th International Conference on Information Technology and Applications in Biomedicine
Subtitle of host publicationEmerging Technologies for Patient Specific Healthcare
DOIs
StatePublished - Dec 1 2010
Event10th International Conference on Information Technology and Applications in Biomedicine: Emerging Technologies for Patient Specific Healthcare, ITAB 2010 - Corfu, Greece
Duration: Nov 2 2010Nov 5 2010

Publication series

NameProceedings of the IEEE/EMBS Region 8 International Conference on Information Technology Applications in Biomedicine, ITAB

Other

Other10th International Conference on Information Technology and Applications in Biomedicine: Emerging Technologies for Patient Specific Healthcare, ITAB 2010
CountryGreece
CityCorfu
Period11/2/1011/5/10

ASJC Scopus subject areas

  • Computer Science Applications
  • Biomedical Engineering

Fingerprint Dive into the research topics of 'Optimizing lung volume segmentation by texture classification'. Together they form a unique fingerprint.

  • Cite this

    Korfiatis, P., Kazantzi, A., Kalogeropoulou, C., Petsas, T., & Costaridou, L. (2010). Optimizing lung volume segmentation by texture classification. In ITAB 2010 - 10th International Conference on Information Technology and Applications in Biomedicine: Emerging Technologies for Patient Specific Healthcare [5687763] (Proceedings of the IEEE/EMBS Region 8 International Conference on Information Technology Applications in Biomedicine, ITAB). https://doi.org/10.1109/ITAB.2010.5687763