Paper
9 May 2002 Recognition of lung nodules from x-ray CT images using 3D Markov random field models
Hotaka Takizawa, Shinji Yamamoto, Tohru Matsumoto, Yukio Tateno, Takeshi Iinuma, Mitsuomi Matsumoto
Author Affiliations +
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.
© (2002) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hotaka Takizawa, Shinji Yamamoto, Tohru Matsumoto, Yukio Tateno, Takeshi Iinuma, and Mitsuomi Matsumoto "Recognition of lung nodules from x-ray CT images using 3D Markov random field models", Proc. SPIE 4684, Medical Imaging 2002: Image Processing, (9 May 2002); https://doi.org/10.1117/12.467214
Lens.org Logo
CITATIONS
Cited by 12 scholarly publications and 5 patents.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
3D modeling

Blood vessels

X-ray computed tomography

Autoregressive models

3D image processing

Mathematical modeling

Image filtering

Back to Top