A Deep Learning Based Automatic Classification Algorithms Used for Pulmonary Veins and Arteries Separation in CT Images
Ambika Sekhar1, L. Padma Suresh2, Jaya Mary Jacob3
1Ambika Sekhar, Research Scholar, Department of Electronics and Communication, Sree Buddha College of Engineering Pattoor, Alappuzha (Kerala), India.
2Dr. L. Padma Suresh, Professor and Principal, Department of Computer Science, Base Baselios Mathews II College of Engineering, Sasthamkotta (Kerala), India.
3Dr. Jaya Mary Jacob, Bio CARe Scientist, Department of Bio-Technology and Bio-Chemical Engineering, Sree Buddha College of Engineering Pattoor, Alappuzha, (Kerala), India.
Manuscript received on 26 May 2019 | Revised Manuscript received on 13 June 2019 | Manuscript Published on 26 June 2019 | PP: 322-325 | Volume-8 Issue-1S5 June 2019 | Retrieval Number: A00560681S519/2019©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Nowadays most of patients are suffering from pulmonary vascular diseases which can cause pulmonary emboli or pulmonary hypertension. Manual as well as automatic analysis of chest CT image of the sick personis carried out for diagnosing changes in vascular trees. Manual analysis of CT scan takes more time,is not standardized, and is also tiresome. So semi-automatic and automatic separation of vascular trees in CT images is nowadays used, which can help doctors to accurately detect abnormal conditions. Different methods for detection and classification of pulmonary vascular diseases using deep learning are discussed in this review paper.
Keywords: Vascular Disease, Deep Learning, Automatic Classification.
Scope of the Article: Deep Learning