Medical Image Analysis for Brain and Kidney Tumor Detection Using Convolutional Neural Networks

Authors

  • Muhammad Sarmad Shakil Department of Computer Science, Minhaj University, Lahore, Pakistan.
  • Zahra Maryam Department of Computer Science, Minhaj University, Lahore, Pakistan.
  • Hamid Manzoor Department of Computer Science, Minhaj University, Lahore, Pakistan.
  • Sidra Ramzan School of System and Technology, Deparment of Computer Science, Univeristy of Management and Technology, Lahore, Pakistan.
  • Saima Yousaf Department of Computer Science, Minhaj University, Lahore, Pakistan.
  • Muhamamd Yousif Department of Computer Science, Minhaj University, Lahore, Pakistan.

Keywords:

Kidney Tumor, Brain Tumor, Convolution Neural Network

Abstract

Rapid and unchecked cell proliferation is the cause of brain tumors. It can be fatal if left untreated in the early stages. A crucial area of study and clinical application is the issue of tumor detection and segmentation in medical imaging. Accurate and effective procedures are required for the detection and delineation of brain tumors and kidney tumors due to their complexity and indecision. The problem's essential features and complexities are further examined in the problem elaboration. The Significance of Correct Tumor Identification for efficient treatment planning and patient management, brain tumor, and kidney tumor detection must occur as soon as possible. Healthcare providers can confidently decide on treatments such as radiation therapy, surgery, and other treatment methods when they can accurately identify the tumor regions in medical pictures. Convolutional neural network shows better outcomes with 96% accuracy.

Downloads

Published

2025-08-16

How to Cite

Muhammad Sarmad Shakil, Zahra Maryam, Hamid Manzoor, Sidra Ramzan, Saima Yousaf, & Muhamamd Yousif. (2025). Medical Image Analysis for Brain and Kidney Tumor Detection Using Convolutional Neural Networks. Journal of Computing & Biomedical Informatics. Retrieved from https://www.jcbi.org/index.php/Main/article/view/1018

Issue

Section

Articles