A New Retrieval Algorithm Based on Pulse Coupled Neural Network for Biomedical Images
G. Kalaiarasi1, K. K. Thyagharajan2

1G. Kalaiarasi, Sathyabama Institute of Science and Technology, Chennai (Tamil Nadu), India.

2K. K. Thyagharajan, R.M.D. Engineering College, Anna University, Chennai (Tamil Nadu), India.

Manuscript received on 22 November 2019 | Revised Manuscript received on 03 December 2019 | Manuscript Published on 14 December 2019 | PP: 9-13 | Volume-9 Issue-1S November 2019 | Retrieval Number: A10031191S19/2019©BEIESP | DOI: 10.35940/ijitee.A1003.1191S19

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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: The rapid expansion and improvement in medical science and technology lead to the generation of more image data in its regular activity such as computed tomography (CT), X-ray, magnetic resonance imaging (MRI) etc. To manage the medical images properly for clinical decision making, content-based medical image retrieval (CBMIR) system emerged. In this paper, Pulse Coupled Neural Network (PCNN) based feature descriptor is proposed for retrieval of biomedical images. Time series is used as an image feature which contains the entire information of the feature, based on which the similar biomedical images are retrieved in our work. Here, the physician can point out the disorder present in the patient report by retrieving the most similar report from related reference reports. Open Access Series of Imaging Studies (OASIS) magnetic resonance imaging dataset is used for the evaluation of the proposed approach. The experimental result of the proposed system shows that the retrieval efficiency is better than the other existing systems.

Keywords: CBMIR, PCNN, Biomedical Applications, Biological Model, Time Series.
Scope of the Article: Biomedical Computing