Brain Tumor Detection by Aggregating Deep Learning and GAN Models for Faster MRI image Synthesis

Year : 2025 | Volume : 02 | Issue : 02 | Page : 45 53
    By

    Saryu Verma,

  • Jatin Arora,

  1. PHD Scholar, Department of Computer Science & Engineering, Chitkara University Institute of Engineering and Technology, Punjab, India
  2. Professor, Department of Computer Science & Engineering, Chitkara University Institute of Engineering and Technology, Punjab, India

Abstract

Brain tumors comprise a global health challenge that, in order to be treated and organized, need early and accurate diagnosis. Usually conducted through medical imaging, brain tumor detection techniques have problems of accuracy, efficiency, and confidentiality. Issues of limited datasets, strict privacy laws that provide restrictions on data sharing, and the necessity for specialized expertise on medical image analysis relegates modern methodologies to vulgar charades. For patient prognosis, treatment planning, and diagnosis, accurate brain tumor identification is key. To boost the medical imaging brain cancer detection, we suggest a novel hybrid technique within this work based on ResNet 50 and synthetic GANs. In developing several artificial brain scans that look like actual images of tumors, we explore Augmentation techniques that are critical to expanding and diversifying our dataset. Such methodology for augmenting datasets is crucial when it comes to train models when there is a scarcity of quality medical images.

Keywords: ResNet50, GAN, Brain tumor images, Deep learning. ResNet architecture, MRI

[This article belongs to International Journal of Brain Sciences ]

How to cite this article:
Saryu Verma, Jatin Arora. Brain Tumor Detection by Aggregating Deep Learning and GAN Models for Faster MRI image Synthesis. International Journal of Brain Sciences. 2025; 02(02):45-53.
How to cite this URL:
Saryu Verma, Jatin Arora. Brain Tumor Detection by Aggregating Deep Learning and GAN Models for Faster MRI image Synthesis. International Journal of Brain Sciences. 2025; 02(02):45-53. Available from: https://journals.stmjournals.com/ijbs/article=2025/view=216898


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Regular Issue Subscription Review Article
Volume 02
Issue 02
Received 27/05/2025
Accepted 09/07/2025
Published 14/07/2025
Publication Time 48 Days
300

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