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Proceedings Paper

Automated anatomical description of pleural thickening towards improvement of its computer-assisted diagnosis
Author(s): Kraisorn Chaisaowong; Mingze Jiang; Peter Faltin; Dorit Merhof; Christian Eisenhawer; Monika Gube; Thomas Kraus
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Paper Abstract

Pleural thickenings are caused by asbestos exposure and may evolve into malignant pleural mesothelioma. An early diagnosis plays a key role towards an early treatment and an increased survival rate. Today, pleural thickenings are detected by visual inspection of CT data, which is time-consuming and underlies the physician's subjective judgment. A computer-assisted diagnosis system to automatically assess pleural thickenings has been developed, which includes not only a quantitative assessment with respect to size and location, but also enhances this information with an anatomical description, i.e. lung side (left, right), part of pleura (pars costalis, mediastinalis, diaphragmatica, spinalis), as well as vertical (upper, middle, lower) and horizontal (ventral, dorsal) position. For this purpose, a 3D anatomical model of the lung surface has been manually constructed as a 3D atlas. Three registration sub-steps including rigid, affine, and nonrigid registration align the input patient lung to the 3D anatomical atlas model of the lung surface. Finally, each detected pleural thickening is assigned a set of labels describing its anatomical properties. Through this added information, an enhancement to the existing computer-assisted diagnosis system is presented in order to assure a higher precision and reproducible assessment of pleural thickenings, aiming at the diagnosis of the pleural mesothelioma in its early stage.

Paper Details

Date Published: 24 March 2016
PDF: 8 pages
Proc. SPIE 9785, Medical Imaging 2016: Computer-Aided Diagnosis, 978530 (24 March 2016); doi: 10.1117/12.2216939
Show Author Affiliations
Kraisorn Chaisaowong, King Mongkut’s Univ. of Technology North Bangkok (Thailand)
Mingze Jiang, RWTH Aachen Univ. (Germany)
Peter Faltin, RWTH Aachen Univ. (Germany)
Dorit Merhof, RWTH Aachen Univ. (Germany)
Christian Eisenhawer, Uniklinik RWTH Aachen (Germany)
Monika Gube, Uniklinik RWTH Aachen (Germany)
Thomas Kraus, Uniklinik RWTH Aachen (Germany)


Published in SPIE Proceedings Vol. 9785:
Medical Imaging 2016: Computer-Aided Diagnosis
Georgia D. Tourassi; Samuel G. Armato, Editor(s)

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