TITLE:
3D segmentation and visualization of lung and its structures using CT images of the thorax
AUTHORS:
Pedro P. Rebouças Filho, Paulo Cesar Cortez, Victor Hugo C. de Albuquerque
KEYWORDS:
3D Region Growing; Lungs segmentation; COPD; Pulmonary Structure Visualization; Computed Tomography
JOURNAL NAME:
Journal of Biomedical Science and Engineering,
Vol.6 No.11,
November
25,
2013
ABSTRACT: Computing
systems have been playing an important role in various medical fields, notably
in image diagnosis. Studies in the field of Computational Vision aim at
developing techniques and systems capable of detecting various illnesses automatically.
What has been highlighted among the existing exams that allow diagnosis
aid and the application of computing systems in parallel is Computed Tomography
(CT). CT enables the visualization of internal organs, such as the lung and its
structures. Computational Vision systems extract information from the CT images
by segmenting the regions of interest, and then recognize and identify details
in those images. This work focuses on the segmentation phase of CT lung images
with singularity-based techniques. Among these methods are the region growing
(RG) technique and its 3D RG variations and the thresholding technique with
multi-thresholding. The 3D RG method is applied to lung segmentation and from
the 3D RG segments of the lung hilum, the multi-thresholding can segment the
blood vessels, lung emphysema and the bones. The results of lung segmentation
in this work were evaluated by two
pulmonologists. The results obtained showed that these methods can integrate
aid systems for medical diagnosis in the pulmonology
field.