Automatic Segmentation for Pulmonary Vessels in Plain Thoracic CT Scans

Lai, Jun; Xie, Mei

doi:10.11591/telkomnika.v10i4.864

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“…Vessal tree reconstruction algorithm [10] reduced the number of false positives by 38%. Camarlinght et al [11] has used three different computer aided detection techniques to identify the pulmonary nodules in CT images.…”

Section: Introductionmentioning

confidence: 99%

Automated diagnosis of Lungs Tumor Using Segmentation Techniques

Kailasam¹,

Sathik²

2016

IJECS

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Abstract-The Objective is to detect the cancerous lung nodules from 3D CT chest image and classify the lung disease and its severity. Although so many researches has been done in this stream, the problem still remains a challenging one. To extract the lung region FCM segmentation is used. Here we used six feature extraction techniques such as bag of visual words based on the histogram oriented gradients, the wavelet transform based features, the local binary pattern, SIFT and Zernike moment . The Particle swarm optimization algorithm is used to select the best features.

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Section: Introductionmentioning

confidence: 99%