Title :
Automatic Segmentation of Pulmonary Segments From Volumetric Chest CT Scans
Author :
Van Rikxoort, Eva M. ; De Hoop, Bartjan ; Van De Vorst, Saskia ; Prokop, Mathias ; Van Ginneken, Bram
Author_Institution :
Image Sci. Inst., Utrecht
fDate :
4/1/2009 12:00:00 AM
Abstract :
Automated extraction of pulmonary anatomy provides a foundation for computerized analysis of computed tomography (CT) scans of the chest. A completely automatic method is presented to segment the lungs, lobes and pulmonary segments from volumetric CT chest scans. The method starts with lung segmentation based on region growing and standard image processing techniques. Next, the pulmonary fissures are extracted by a supervised filter. Subsequently the lung lobes are obtained by voxel classification where the position of voxels in the lung and relative to the fissures are used as features. Finally, each lobe is subdivided in its pulmonary segments by applying another voxel classification that employs features based on the detected fissures and the relative position of voxels in the lobe. The method was evaluated on 100 low-dose CT scans obtained from a lung cancer screening trial and compared to estimates of both interobserver and intraobserver agreement. The method was able to segment the pulmonary segments with high accuracy (77%), comparable to both interobserver and intraobserver accuracy (74% and 80%, respectively).
Keywords :
computerised tomography; feature extraction; image classification; image segmentation; lung; medical image processing; automatic segmentation; computed tomography; image processing; lobes; lung cancer; lungs; pulmonary fissures; pulmonary segments; volumetric chest CT scans; voxel classification; Anatomy; Computed tomography; Filters; High-resolution imaging; Image analysis; Image processing; Image segmentation; Lesions; Lungs; Surgery; Automatic; classification; computed tomography (CT); pulmonary lobes; pulmonary segments; segmentation; Humans; Image Processing, Computer-Assisted; Lung; Lung Neoplasms; Observer Variation; Tomography, X-Ray Computed;
Journal_Title :
Medical Imaging, IEEE Transactions on
DOI :
10.1109/TMI.2008.2008968