The week's pick
Reseach Article
Lung Nodule Classification Techniques for Low Dose Computed Tomography (LDCT) Scan Images as Survey
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 131 - Number 14 |
| Year of Publication: 2015 |
| Authors: Suganya A., Mohanapriya N., B. Kalaavathi |
10.5120/ijca2015907464
|
Suganya A., Mohanapriya N., B. Kalaavathi . Lung Nodule Classification Techniques for Low Dose Computed Tomography (LDCT) Scan Images as Survey. International Journal of Computer Applications. 131, 14 ( December 2015), 12-15. DOI=10.5120/ijca2015907464
Abstract
Image classification is one of the most complex areas in image processing. It is more complex and difficult to classify if it contain blurry and noisy content. Medical image Classification is an important task within the field of computer vision. Here, perform four type of lung nodules classification , i.e., well-circumscribed, vascularized, juxta-pleural and pleural-tail, in low dose computed tomography (LDCT) scans images. The classification method combine the lung nodule and surrounding anatomical structures through contextual analysis. Here, presents a survey on the various techniques used for classifying image which is mainly based on object in the given image. The proposed method was classified on a publicly available dataset.
References
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