Paper Info
Title
Interactive lung segmentation in ct scans with severe abnormalities
Abstract
Estimation of the volume of the lungs and the viable lung tissue is an important step in the management of patients with severe pulmonary disease. The presence of gross pathology makes it impossible to perform lung segmentation automatically and reliably in CT scans of such patients. An interactive system for lung segmentation is presented, based on precomputed compact regions with homogeneous texture for which general texture feature have been computed. A statistical classifier trained on prior data has classified these regions beforehand and the user corrects any errors until the segmentation of an entire slice is correct. The system proceeds to subsequent slices, which were preclassified using a combined classification strategy that uses both the prior data and the previously approved slices from the test scan. The resulting lung segmentations show a large overlap and a small average boundary distance when compared to completely manual delineations of the lung borders. The lung segmentations can then be used as input for a similar interactive system to determine the viable lung volume.
Year
DOI
Venue
2010
10.1109/ISBI.2010.5490285
ISBI
Keywords
Field
DocType
lung segmentation,severe abnormality,interactive lung segmentation,system proceed,lung border,ct scan,similar interactive system,viable lung volume,general texture feature,interactive system,resulting lung segmentation,prior data,viable lung tissue,image segmentation,pathology,pediatrics,biomedical imaging,image texture,computed tomography,ventilation
Computer vision,Lung,Pattern recognition,Segmentation,Image texture,Medical imaging,Computer science,Homogeneous,Lung volumes,Image segmentation,Artificial intelligence,Lung segmentation
Conference
ISSN
Citations 
PageRank 
1945-7928
3
0.48
References 
Authors
1
4
Name
Order
Citations
PageRank
Thessa T .J .P. Kockelkom130.48
Eva M. van Rikxoort256531.97
Jan C. Grutters352.61
Bram van Ginneken44979307.23