Paper Info
Title
Recognition of lung nodules from x-ray CT images considering 3D structure of objects and uncertainty of recognition
Abstract
In this paper, we propose a method of recognition of lung nodules using 3D nodule and blood vessel models considering uncertainty of recognition. Region of interest(ROI) areas are extracted by our quoit filter which is a kind of Mathmatical Morphology filter. We represent nodules as sphere models, blood vessels as cylinder models and the branches of the blood vessels as the connections of the cylinder models, respectively. All of the possible models for nodules and blood vessels are generated which can occur in the ROI areas. The probabilities of the hypotheses of the ROI areas coming from the sphere models are calculated and the probabilities for the cylinder models are also calculated. The most possible sphere models and cylinder models which maximize the probabilities are searched considering uncertainty of recognition. If the maximum probability for the nodule model is higher, the shadow candidate is determined to be abnormal. By applying this new method to actual CT images (37 patient images), good results have been acquired.
Year
DOI
Venue
2000
10.1117/12.387604
Proceedings of SPIE
Keywords
Field
DocType
recognition of lung nodules,3D nodule and blood vessel models,uncertainty of recognition,probability
Nuclear medicine,Shadow,Pattern recognition,Mathematical morphology,Lung disease,Computer science,Cylinder,Computed tomography,Artificial intelligence,Region of interest
Conference
Volume
ISSN
Citations 
3979
0277-786X
0
PageRank 
References 
Authors
0.34
0
7
Name
Order
Citations
PageRank
Hotaka Takizawa18416.49
gentaro fukano2527.53
Shinji Yamamoto39416.35
Tohru Matsumoto48210.34
Yukio Tateno57914.41
Takeshi Iinuma6558.64
Mitsuomi Matsumoto7315.47