Multi-stage learning for robust lung segmentation in challenging CT volumes

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6893 LNCS, Issue PART 3, 2011, Pages 667-674

  Sofka, Michal ^a   Wetzl, Jens ^a   Birkbeck, Neil ^a   Zhang, Jingdan ^a   Kohlberger, Timo ^a   Kaftan, Jens ^b   Declerck, Jérôme ^b   Zhou, S Kevin ^a  

^a SIEMENS CORPORATE RESEARCH   (United States)

^b Caernarfon   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ANATOMICAL INFORMATION; BOUNDARY DETECTION; CT VOLUME; DISCRIMINATIVE CLASSIFIERS; HIGH DENSITY; LEARNING-BASED APPROACH; LUNG SEGMENTATION; MULTI-STAGE; SHAPE MODEL; SIMPLE ALGORITHM; STATISTICAL SHAPE MODEL;

BIOLOGICAL ORGANS; COMPUTER AIDED INSTRUCTION; COMPUTERIZED TOMOGRAPHY; MEDICAL COMPUTING; MEDICAL IMAGING; TISSUE;

IMAGE SEGMENTATION;

ALGORITHM; ARTICLE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; COMPUTER PROGRAM; CONE BEAM COMPUTED TOMOGRAPHY; DIAGNOSTIC IMAGING; HUMAN; LEARNING; LUNG; LUNG TUMOR; METHODOLOGY; PATHOLOGY; RADIOGRAPHY; STATISTICAL MODEL;

ALGORITHMS; CONE-BEAM COMPUTED TOMOGRAPHY; DIAGNOSTIC IMAGING; HUMANS; LEARNING; LUNG; LUNG NEOPLASMS; MODELS, STATISTICAL; PATTERN RECOGNITION, AUTOMATED; RADIOGRAPHIC IMAGE INTERPRETATION, COMPUTER-ASSISTED; SOFTWARE;

EID: 82255185704     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-23626-6_82     Document Type: Conference Paper

References (12)

1. De Nunzio, G., Tommasi, E., Agrusti, A., Cataldo, R., De Mitri, I., Favetta, M., Maglio, S., Massafra, A., Quarta, M., Torsello, M., et al.: Automatic lung segmentation in CT images with accurate handling of the hilar region. Journal of Digital Imaging, 1-17 (2009)
2. Hu, S., Hoffman, E., Reinhardt, J.: Automatic lung segmentation for accurate quantitation of volumetric X-ray CT images. IEEE Trans. Med. Imag. 20(6), 490-498 (2002)
3. Kockelkorn, T., van Rikxoort, E., Grutters, J., van Ginneken, B.: Interactive lung segmentation in CT scans with severe abnormalities. In: IEEE Int. Symp. on Biomed. Imag., pp. 564-567 (2010)
4. Korfiatis, P., Kalogeropoulou, C., Karahaliou, A., Kazantzi, A., Skiadopoulos, S., Costaridou, L.: Texture classification-based segmentation of lung affected by interstitial pneumonia in high-resolution CT. Medical Physics 35, 5290 (2008)
5. Ling, H., Zhou, S.K., Zheng, Y., Georgescu, B., Suehling, M., Comaniciu, D.: Hierarchical, learning-based automatic liver segmentation. In: IEEE Conf. on Comp. Vis. and Patt. Recog., Los Alamitos, CA, USA (2008)
6. Prasad, M., Brown, M., Ahmad, S., Abtin, F., Allen, J., Da Costa, I., Kim, H., McNitt-Gray, M., Goldin, J.: Automatic segmentation of lung parenchyma in the presence of diseases based on curvature of ribs. Acad. Radiol. 15(9), 1173-1180 (2008)
7. Sluimer, I., Prokop, M., van Ginneken, B.: Toward automated segmentation of the pathological lung in CT. IEEE Trans. Med. Imag. 24(8), 1025-1038 (2005)
8. Sofka, M., Zhang, J., Zhou, S., Comaniciu, D.: Multiple object detection by sequential Monte Carlo and hierarchical detection network. In: IEEE Conf. on Comp. Vis. and Patt. Recog. (June 13-18, 2010)
9. Sun, S., McLennan, G., Hoffman, E.A., Beichel, R.: Model-based segmentation of pathological lungs in volumetric CT data. In: The Third International Workshop on Pulmonary Image Analysis (2010)
10. Tu, Z.: Probabilistic boosting-tree: learning discriminative models for classification, recognition, and clustering. In: IEEE Int. Conf. on Comp. Vis. and Patt. Recog., vol. 2, pp. 1589-1596 (2005)
11. Vidal, C., Hewitt, J., Davis, S., Younes, L., Jain, S., Jedynak, B.: Template registration with missing parts: Application to the segmentation of M. tuberculosis infected lungs. In: IEEE Int. Symp. on Biomed. Imag., pp. 718-721 (2009)
12. Wang, J., Li, F., Li, Q.: Automated segmentation of lungs with severe interstitial lung disease in CT. Medical Physics 36, 4592 (2009)