Automated pulmonary nodule detection system in computed tomography images based on Active-contour and SVM classification algorithmстатья
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Дата последнего поиска статьи во внешних источниках: 15 февраля 2024 г.
Аннотация:Lung cancer is a common type of cancer that requires early diagnosis. Computer
systems by particular different image processing techniques can use for increase the speed and
accuracy of lung nodule detection. CT images used in this work in order to process medical
images. In this paper proposed an automatic lung nodule detection algorithm using active contour
method and SVM classification method. In proposed method, at first in order to achieve better
results, lung CT image pre-processing is performed. Then the lung area is segmented by
thresholding method followed by some reconstruction techniques to transfer non-isolated
nodules into isolated ones. In the next step the nodule candidates are determined using active
contour method. Then, nodules are detected by the support vector machine (SVM) classifier
using efficient 2D stochastic and 3D anatomical features. In the result, nodules are detected with
an overall detection rate of 87%; the number of false positive is 7.5/scan and the location of all
detected nodules are recognized correctly.