Deep Learning-Based Brain Tumor Detection from MRI Images.

Subject area: Computer Science

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Abstract

Brain malignant tumors, which are aberrant cell growths, are known as tumors. Frequently, infectious brain tissues are caught by CT and MRI scans. There are many other methods that are used for the detection of brain tumors and some of them are positive charges imaging and cerebral X-ray photography of blood or lymph vessels and tests at the molecular level. So, this paper will use different MRI images to detect ailment cause like tumors. The main purpose of this research paper is to 1) identify irregular sample images and 2) find the tumor area. The abnormal sections of images will forecast the levels of tumors so that proper treatment can be done. Deep learning is used to find abnormal regions from sample images. This paper will use VGG-16 to segment the abnormal part. The density of the infected region is defined by the number of pixels with malignancy.

Keywords

Brain Tumor DetectionMachine LearningDeep LearningMRI ImagesConvolutional Neural Network (CNN)Medical Image ProcessingArtificial IntelligenceTumor Classification

Cite this article

Bhagyashree Kashetty, Chaitra, Daneshwari Hiremath, Joshua, Dr.Savitha Patil (2026). Deep Learning-Based Brain Tumor Detection from MRI Images.. International Innovations & Scholarly Trends Journal, 2(6), 2393–2398.

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© 2026 — Authors retain the copyright of this article. This is an open access article distributed under the Creative Commons Attribution License (CC BY 4.0) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.