Accurate estimation of pulmonary nodule's growth rate in ct images with nonrigid registration and precise nodule detection and segmentation

2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPR Workshops 2009

Volumn , Issue , 2009, Pages 101-108

  Zheng, Yuanjie ^a   Kambhamettu, Chandra ^a   Bauer, Thomas ^b   Steiner, Karl ^a  

^a UNIVERSITY OF DELAWARE   (United States)

^b HELEN F GRAHAM CANCER CENTER   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER VISION; IMAGE SEGMENTATION; POSITRON EMISSION TOMOGRAPHY; TUMORS;

ACCURATE ESTIMATION; HIGH-ACCURACY; NODULE DETECTION; NODULE SEGMENTATION; NONRIGID REGISTRATION; NONRIGID REGISTRATION METHOD; PULMONARY NODULES; REGISTRATION PROCESS;

COMPUTERIZED TOMOGRAPHY;

EID: 70449562419     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2009.5204050     Document Type: Conference Paper

References (20)

1. K. T. Bae and et al. Pulmonary nodules: Automated detection on CT images with morphologic matching algorithm preliminary results. Radiology, 236:286-293, 2005.
2. Cancer Research UK. Commonly diagnosed cancers worldwide. Technical report, Cancer Research UK, http://info.cancerresearchuk.org/cancerstats/ geographic/world/commoncancers/, April 2005.
3. J. J. Erasmus, G. W. Gladish, L. Broemeling, B. S. Sabloff, M. T. Truong, R. S. Herbst, and R. F. Munden. Interobserver and intraobserver variability in measurement of noncsmall-cell carcinoma lung lesions: Implications for assessment of tumor response. Journal of Clinical Oncology, 21:2574-2582, 2003.
4. B. J. Frey and D. Dueck. Clustering by passing messages between data points. Science, 315:972-976, 2007.
5. H. A. Gietema, C. M. Schaefer-Prokop, W. P. T. M. Mali, G. Groenewegen, and M. Prokop. Pulmonary nodules: Interscan variability of semiautomated volume measurements with multisection CT influence of inspiration level, nodule size, and segmentation performance. Radiology, 245:888-894, 2007.
6. X. He and P. Niyogi. Locality preserving projections. In Advances in Neural Information Processing Systems 16, Vancouver, Canada, 2003.
7. K. G. Kim and et al. Computer-aided diagnosis of localized ground-glass opacity in the lung at CT: Initial experience. Radiology, 37:657-661, 2005.
8. W. J. Kostis, A. P. Reeves, D. F. Yankelevitz, and C. I. Henschke. Three-dimensional segmentation and growth-rate estimation of small pulmonary nodules in helical CT images. IEEE Trans. Medical Imaging, 22:1259-1274, 2003.
9. Y. Lee and et al. Automated detection of pulmonary nodules in helical CT images based on an improved template-matching technique. IEEE Transactions on Mecial Imaging, 20:595-604, 2001.
10. C. E. Metz and et al. Maximum likelihood estimation of receiver operating characteristic (ROC) curves from continuously-distributed data. Stat. Med., 17:1033-1053, 1998.
11. J. Pearl. Probabilistic reasoning in intelligent systems: networks of plausible inference. Morgan Kaufmann Publishers Inc., 1988.
12. A. P. Reeves, A. B. Chan, D. F. Yankelevitz, C. I. Henschke, B. Kressler, and W. J. Kostis. On measuring the change in size of pulmonary nodules. IEEE Trans. Medical Imaging, 25:435-450, 2006.
13. D. Rueckert, L. Sonoda, I. C. Hayes, D. L. G. Hill, M. O. Leach, and D. J. Hawkes. Nonrigid registration using free-form deformations: Application to breast MR images. IEEE Transactions on Medical Imaging, 18:712-721, 1999. (Pubitemid 32262025)
14. T. Tan. Rotation invariant texture features and their use in automatic script identification. IEEE Trans. Pattern Anal. Mach. Intell., 20:751-756, 1998.
15. C. Tanner, J. A. Schnabel, D. Chung, M. J. Clarkson, D. Rueckert, D. L. G. Hill, and D. J. Hawkes. Volume and shape preservation of enhancing lesions when applying non-rigid registration to a time series of contrast enhancing MR breast images. In MICCAI 2000, pages 327-337, 2000.
16. D. Wormanns and S. Diederich. Characterization of small pulmonary nodules by CT. European Radiology, 14:1380-1391, 2004.
17. D. F. Yankelevitz, A. P. Reeves, W. J. Kostis, B. Zhao, and C. I. Henschke. Small pulmonary nodules: Volumetrically determined growth rates based on CT evaluation. Radiology, 217:251-256, 2000.
18. R. Zabih and V. Kolmogorov. Spatially coherent clustering using graph cuts. In CVPR 2004, volume 2, pages H-437-n-444, 2004.
19. B. Zhao and et al. Automatic detection of small lung nodules on CT utilizing a local density maximum algorithm. Journal of Applied Clinical Medical Physics, 4:248-260, 2003.
20. J. Zhou and et al. Automatic detection and segmentation of ground glass opacity nodules. In Medical Image Computing and Computer-Assisted Intervention -MICCAI2006, pages 784-791, 2006.