Title :
Variational approach for segmentation of lung nodules
Author :
Farag, A.A. ; Abdelmunim, Hossam ; Graham, James ; Farag, Amal A. ; Elshazly, Salwa ; El-Mogy, Sabry ; El-Mogy, Mohamed ; Falk, Robert ; Al-Jafary, Sahar ; Mahdi, Hani ; Milam, Rebecca
Author_Institution :
Comput. Vision & Image Process. Lab. (CVIP Lab.), Univ. of Louisville, Louisville, KY, USA
Abstract :
Lung nodules from low dose CT (LDCT) scans may be used for early detection of lung cancer. However, these nodules vary in size, shape, texture, location, and may suffer from occlusion within the tissue. This paper presents an approach for segmentation of lung nodules detected by a prior step. First, regions around the detected nodules are segmented; using automatic seed point placement levels sets. The outline of the nodule region is further improved using the curvature characteristics of the segmentation boundary. We illustrate the effectiveness of this method for automatic segmentation of the Juxta-pleural nodules.
Keywords :
cancer; computer graphics; computerised tomography; image segmentation; lung; medical image processing; Juxta-pleural nodule automatic segmentation; automatic seed point placement levels sets; low dose CT scans; lung cancer early detection; lung nodules segmentation; occlusion; variational approach; Computed tomography; Conferences; Databases; Image segmentation; Level set; Lungs; Shape;
Conference_Titel :
Image Processing (ICIP), 2011 18th IEEE International Conference on
Conference_Location :
Brussels
Print_ISBN :
978-1-4577-1304-0
Electronic_ISBN :
1522-4880
DOI :
10.1109/ICIP.2011.6116038