Share Email Print

Proceedings Paper

Recognition of lung nodules from x-ray CT images using 3D Markov random field models
Author(s): Hotaka Takizawa; Shinji Yamamoto; Tohru Matsumoto; Yukio Tateno; Takeshi Iinuma; Mitsuomi Matsumoto
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

In this paper we propose a new recognition method of lung nodules from x-ray CT images using 3D Markov random field (MRF) models. Pathological shadow candidates are detected by our Quoit filter which is a kind of mathematical morphology filter, and volume of interest (VOI) areas which include the shadow candidates are extracted. The probabilities of the hypotheses that the VOI areas come from nodules (which are candidates of cancers) and blood vessels are calculated using nodule and blood vessel models evaluating the relations between these object models using 3D MRF models. If the probabilities for the nodule models are higher, the shadow candidates are determined to be abnormal. Otherwise, they are determined to be normal. Experimental results for 38 samples (patients) are shown.

Paper Details

Date Published: 9 May 2002
PDF: 10 pages
Proc. SPIE 4684, Medical Imaging 2002: Image Processing, (9 May 2002); doi: 10.1117/12.467214
Show Author Affiliations
Hotaka Takizawa, Toyohashi Univ. of Technology (Japan)
Shinji Yamamoto, Toyohashi Univ. of Technology (Japan)
Tohru Matsumoto, National Institute of Radiological Science (Japan)
Yukio Tateno, National Institute of Radiological Science (Japan)
Takeshi Iinuma, National Institute of Radiological Science (Japan)
Mitsuomi Matsumoto, Tokyo Metropolitan Univ. of Health Sciences (Japan)

Published in SPIE Proceedings Vol. 4684:
Medical Imaging 2002: Image Processing
Milan Sonka; J. Michael Fitzpatrick, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?