NeuroScanCare: Intelligent Brain Tumor Detection With Integrated Medical Support
Yamini R. Potbhare, Dr. Ravi Mathey
Brain tumors represent a critical medical condition requiring prompt diagnosis and immediate access
to specialized healthcare facilities. This research presents NeuroScanCare, an innovative integrated
platform that combines artificial intelligence-based medical imaging analysis with intelligent healthcare
navigation services.
The system employs a custom-designed Convolutional Neural Network (CNN) architecture featuring
three convolutional layers, maxpooling operations, and dropout regularization to analyze uploaded
MRI scans. Through comprehensive model evaluation, our custom CNN achieved superior performance
with 84% classification accuracy, outperforming established architectures including VGG16 (80%),
ResNet50 (78%), and InceptionV3 (70%). The model successfully categorizes brain scans into four
distinct classifications: Glioma, Pituitary tumors, Meningioma, and non-tumor cases.
Upon tumor detection, the platform automatically activates its location-based recommendation engine
utilizing the Geolocation API to determine user coordinates. The system implements the Haversine
formula for precise distance calculations, identifying the five nearest healthcare facilities from the
patient's current position. Each recommended hospital is presented with comprehensive details
including specialization areas, patient ratings, supported insurance plans, contact information, and
visual mapping integration.
The application leverages Flask framework for backend operations, HTML/CSS/JavaScript for user
interface design, and Google Maps API for navigation services with multiple transportation options.
Pandas library manages hospital database operations through CSV file handling.
NeuroScanCare bridges the gap between advanced medical diagnosis and accessible healthcare
delivery, providing patients with immediate diagnostic insights coupled with actionable healthcare
facility recommendations, ultimately enhancing clinical outcomes through timely medical intervention.
