Lung cancer detection from thoracic CT scans using 3-D deformable models based on statistical anatomical analysis
作者： Hotaka Takizawa , Shigeyuki Ishii
DOI: 10.1007/978-3-642-24136-9_3
关键词:
摘要: In the present paper, we propose a novel recognition method of pulmonary nodules (possible lung cancers) in thoracic CT scans. Pulmonary and blood vessels are represented by 3-D deformable spherical cylindrical models. The validity these object models evaluated probability distributions that reflect results statistical anatomical analysis vessel trees human lungs. fidelity to scans five similarity measurements based on differences intensity between templates produced from Through evaluations, posterior probabilities hypotheses appear calculated use Bayes theorem. nodule is performed maximum estimation. Experimental obtained applying proposed actual shown.
springer.com
sci-hub.st 参考文章(29)
Marcin Bator, Leszek J. Chmielewski, Elimination of Linear Structures as an Attempt to Improve the Specificity of Cancerous Mass Detection in Mammograms computer recognition systems. pp. 596- 603 ,(2007) , 10.1007/978-3-540-75175-5_75
Hotaka Takizawa, Hidetoshi Nishizako, Lung Cancer Detection from X-ray CT Scans Using Discriminant Filters and View-based Support Vector Machine The Journal of the Institute of Image Electronics Engineers of Japan. ,vol. 40, pp. 59- 66 ,(2011) , 10.11371/IIEEJ.40.59
Hidetaka Arimura, Shigehiko Katsuragawa, Kenji Suzuki, Feng Li, Junji Shiraishi, Shusuke Sone, Kunio Doi, Computerized scheme for automated detection of lung nodules in low-dose computed tomography images for lung cancer screening Academic Radiology. ,vol. 11, pp. 617- 629 ,(2004) , 10.1016/J.ACRA.2004.02.009
Samuel G. Armato, Maryellen L. Giger, Catherine J. Moran, James T. Blackburn, Kunio Doi, Heber MacMahon, Computerized Detection of Pulmonary Nodules on CT Scans Radiographics. ,vol. 19, pp. 1303- 1311 ,(1999) , 10.1148/RADIOGRAPHICS.19.5.G99SE181303
Sumiaki Matsumoto, Harold L. Kundel, James C. Gee, Warren B. Gefter, Hiroto Hatabu, Pulmonary nodule detection in CT images with quantized convergence index filter Medical Image Analysis. ,vol. 10, pp. 343- 352 ,(2006) , 10.1016/J.MEDIA.2005.07.001
A. El-Baz, G. Gimel'farb, R. Falk, A.A. Farag, Detection and recognition of lung abnormalities using deformable templates international conference on pattern recognition. ,vol. 3, pp. 738- 741 ,(2004) , 10.1109/ICPR.2004.295
S. Yamamoto, M. Matsumoto, Y. Tateno, T. Iinuma, T. Matsumoto, Quoit filter-a new filter based on mathematical morphology to extract the isolated shadow, and its application to automatic detection of lung cancer in X-ray CT international conference on pattern recognition. ,vol. 2, pp. 3- 7 ,(1996) , 10.1109/ICPR.1996.546713
Reyes Zwiggelaar, Timothy C. Parr, James E. Schumm, Ian W. Hutt, Christopher J. Taylor, Susan M. Astley, Caroline R.M. Boggis, Model-based detection of spiculated lesions in mammograms Medical Image Analysis. ,vol. 3, pp. 39- 62 ,(1999) , 10.1016/S1361-8415(99)80016-4
Kenji Suzuki, Samuel G. Armato, Feng Li, Shusuke Sone, Kunio Doi, Massive training artificial neural network (MTANN) for reduction of false positives in computerized detection of lung nodules in low-dose computed tomography. Medical Physics. ,vol. 30, pp. 1602- 1617 ,(2003) , 10.1118/1.1580485
Shinji Yamamoto, Ippei Tanaka, Masahiro Senda, Yukio Tateno, Takeshi Iinuma, Toru Matsumoto, Mitsuomi Matsumoto, Image processing for computer-aided diagnosis of lung cancer by CT (LSCT) Systems and Computers in Japan. ,vol. 25, pp. 67- 80 ,(1994) , 10.1002/SCJ.4690250207