Deep Learning Based Medical Image Categorization for Clear Feature Extraction

Authors

  • G. Erna Assistant Professor, Department of Electronics and Communication Engineering, PACE Institute of Technology & Sciences (UGC Autonomous), Ongole-523272, Andhra Pradesh, India.
  • V. Saidulu Sr. Assistant Professor, ECE Department, Mahatma Gandhi Institute of Technology, Gandipet, Hyderabad.
  • T. Padmapriya Melange Publications, Puducherry, India.
  • S. V. Manikanthan Director, Melange Academic Research Associates, Puducherry, India.
  • S. Manikandan Founder and CEO, Edison Techzone Pvt Ltd, Namakkal District Tamilnadu, India 637001.

Keywords:

Deep learning, Medical Imaging, Disease Detection, Accurate prediction

Abstract

In the discipline of recognition, medical image recognition plays a vital role in accurate prediction and quick determination of harmful diseases. Since medical images can be employed to regulate, handle, and diagnose sickness, they are a fundamental component of a patient's medical record. Nonetheless, image categorization is a tough issue in the arena of diagnostics. This article proposes a medical image technique using deep learning to enhance image classification and grouping in the health industry. In recent years, scientific research has centered on deep learning and its utilization in medical imaging, particularly image reconstruction. Considering deep learning models outperform in a broad spectrum of vision circumstances, a great deal of work is currently being focused on reliving pictures taken medical photos. In the current era of swiftly developing technology, MRI, and CT are considered to be the most reliable imaging techniques from scientific viewpoints for detecting and categorizing different diseases. The present article provides different deep learning strategies for rebuilding photographs in addition to a detailed examination of the most prominent databases. We talk about obstacles and prospective opportunities in medical reconstruction. The outcome of the trial indicates our proposed approach functions greater and attains 98% accuracy.

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Published

24.03.2024

How to Cite

Erna, G. ., Saidulu, V. ., Padmapriya, T. ., Manikanthan, S. V. ., & Manikandan, S. . (2024). Deep Learning Based Medical Image Categorization for Clear Feature Extraction. International Journal of Intelligent Systems and Applications in Engineering, 12(20s), 745–754. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/5272

Issue

Vol. 12 No. 20s (2024)

Section

Research Article

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