Title :
Constrained Region-Based Segmentation of Pleural Effusion in Thin-Slice CT
Author :
Donohue, Rory ; Shearer, Andrew ; Bruzzi, John
Author_Institution :
Phys. Dept, Nat. Univ. of Ireland, Galway, Ireland
Abstract :
A pleural effusion is excess fluid that collects in the pleural cavity, the fluid-filled space that surrounds the lungs. Surplus amounts of such fluid can impair breathing by limiting the expansion of the lungs during inhalation. Measuring the fluid volume is indicative of the effectiveness of any treatment but, due to the similarity to surround regions, fragments of collapsed lung present and topological changes; accurate quantification of the effusion volume is a difficult imaging problem. A novel slice-by-slice code is presented which performs conditional region growth to accurately segment the effusion shape. We demonstrate the applicability of our technique in the segmentation of pleural effusion and pulmonary masses.
Keywords :
biomedical measurement; computerised tomography; diseases; image segmentation; lung; medical image processing; pneumodynamics; tumours; volume measurement; breathing impairment; constrained region-based segmentation; diseases; effusion shape segmentation; effusion volume; fluid volume measurement; fluid-filled space; inhalation; lungs; pleural cavity; pleural effusion; pulmonary masses; slice-by-slice code; thin-slice computerised tomography; tumour masses; Computed tomography; Image processing; Image segmentation; Lungs; Machine vision; Physics; Radiology; Rough surfaces; Shape; Surface roughness; constrained region growth; pleural effusion; pulmonary effusion; rib segmentation; signature matching;
Conference_Titel :
Machine Vision and Image Processing Conference, 2009. IMVIP '09. 13th International
Conference_Location :
Dublin
Print_ISBN :
978-1-4244-4875-3
Electronic_ISBN :
978-0-7695-3796-2
DOI :
10.1109/IMVIP.2009.12