| Literature DB >> 9719856 |
K Kanazawa1, Y Kawata, N Niki, H Satoh, H Ohmatsu, R Kakinuma, M Kaneko, N Moriyama, K Eguchi.
Abstract
In this paper, we present a computer-assisted automatic diagnostic system for lung cancer that detects nodule candidates at an early stage from helical CT images of the thorax. Our diagnostic system consists of analytical and diagnostic procedures. In the analytical procedure, first we extract the lung and the pulmonary blood vessel regions using the fuzzy clustering algorithm, then we analyze the features of these regions using image-processing techniques. In the diagnostic procedure, we define diagnostic rules utilizing the extracted features which support the determination of the candidate nodule locations. We show the effectiveness of our system by giving the results from its application to image data for mass screening of 450 patients.Entities:
Mesh:
Year: 1998 PMID: 9719856 DOI: 10.1016/s0895-6111(98)00017-2
Source DB: PubMed Journal: Comput Med Imaging Graph ISSN: 0895-6111 Impact factor: 4.790