Segmentation of Lungs from Chest X-rays using Firefly Optimized Spatial FCM(FASFCM)
Ebenezer Jangam1, Rahul Kumar2, Rajesh Dwivedi3, Vishnu Kumar4
1Ebenezer Jangam, Department of CSE, Vignan Foundation for Science Technology and Research, (Andhra Pradesh), India.
2Rahul Kumar, Department of CSE, Vignan Foundation for Science Technology and Research, (Andhra Pradesh), India.
3Rajesh Dwivedi, Department of CSE, Vignan Foundation for Science Technology and Research, (Andhra Pradesh), India.
4Vishnu Kumar, Department of CSE, Vignan Foundation for Science Technology and Research, (Andhra Pradesh), India.
Manuscript received on 12 February 2019 | Revised Manuscript received on 02 March 2019 | Manuscript Published on 08 June 2019 | PP: 75-78 | Volume-7 Issue-5S4, February 2019 | Retrieval Number: E10150275S419/19©BEIESP
Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© 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: Segmentation of lungs from chest x ray is a non-trivial task required as a preprocessing step for detection of different diseases like cardiomegaly, tuberculosis, pneumonia. High accuracy in segmentation of lung results in high accuracy of detection of diseases from lungs. For the past four decades multiple techniques were proposed for automatic segmentation of lungs. In this paper, we propose a hybrid segmentation technique based on Bat optimized fuzzy c-means clustering algorithm. The output of the fuzzy c-means is given to level set to finalize the segmentation of the lungs. The performance of the proposed technique is evaluated using two public chest x ray datasets: JRST and Montgomery County. JRST contains 247 chest X-rays and MC dataset contains 138 chest X-rays. The Jaccard coefficient for the proposed segmentation technique is 95.1 which is on par with the state of art segmentation techniques.
Keywords: Use About Five Key Words or Phrases in Alphabetical Order, Separated by Semicolon.
Scope of the Article: Artificial Intelligence