NeuraScan uses deep learning (MobileNetV2) to analyze brain MRI scans and classify tumor types with clinical-grade accuracy — helping researchers and medical professionals make faster, better-informed decisions.
NeuraScan is a Final Year Project developed at KFUEIT, combining transfer learning with MobileNetV2 to build a clinically-relevant tool for brain tumor detection from MRI images.
Our model identifies and classifies the most clinically significant brain tumor types
Originates from glial cells. Most common and aggressive brain tumor.
Arises from the meninges surrounding the brain. Often slow-growing.
Affects the pituitary gland and hormonal regulation.
No evidence of tumor. High specificity minimizes false positives.
Production-grade technologies powering every layer of NeuraScan
Create a free account and start uploading MRI scans for instant AI-powered classification. Built for researchers, medical students, and healthcare professionals.