Computer aided diagnosis system for lung cancer based on helical CTimages
Kanazawa, K.
Kubo, M.
Niki, N.
Dept. of Inf., Tokushima Univ.;
This paper appears in: Pattern Recognition, 1996., Proceedings of the 13th International Conference on
Publication Date: 25-29 Aug 1996
Volume: 3,
On page(s): 381-385 vol.3
Meeting Date: 08/25/1996 - 08/29/1996
Location: Vienna, Austria
ISBN: 0-8186-7282-X
References Cited: 8
INSPEC Accession Number: 5450636
Digital Object Identifier: 10.1109/ICPR.1996.546974
Current Version Published: 2002-08-06
Abstract
In this paper we describe a computer assisted automatic diagnosis
system for lung cancer that detects tumor candidates at an early stage
from helical computerised tomographic (CT) images. This automation of
the process reduces the time complexity and increases the diagnosis
confidence. Our algorithm consists of an analysis part and a diagnosis
part. In the analysis part, we extract the lung and pulmonary blood
vessel regions and analyze the features of these regions using image
processing techniques. In the diagnosis part, we define diagnosis rules
based on these features, and detect tumor candidates using these rules.
We have applied our algorithm to 450 patient's data for mass screening.
The results show that our algorithm detected lung cancer candidates
successfully
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