Improving Medical Image Classification Using Vision transformers
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Date
2025-06-15
Journal Title
Journal ISSN
Volume Title
Publisher
Mohamed Boudiaf University of M'sila
Abstract
The integration of Vision Transformers (ViTs) into the field of medical imaging has opened new
avenues for accurate, data-driven diagnostics by leveraging self-attention mechanisms to capture global
contextual information. in this project we explored the application of ViTs to various medical imaging
tasks, including classification, segmentation, and anomaly detection in X-raysour project utilizes the
Vision Transformer (ViT) deep learning technique to accurately classify medical images from a chest
X-ray dataset, demonstrating its effectiveness in various fields like computer vision and medical
applications.
Description
Keywords
Vision Transformer, deep learning, Convolutional Neural Networks, medical image classification, Chest X-ray, Computer vision, hyperparameters, model efficiency, healthcare improvement