Primary Office: 10:00 AM – 6:00 PM IST | Extended Support Available
Primary Office: 10:00 AM – 6:00 PM IST | Extended Support Available

AI-Based Brain Lesion & Tumour Detection System

A multi-specialty diagnostic center aimed to enhance early detection of brain lesions and tumours using AI-powered medical imaging analysis to support radiologists and reduce reporting time.

Location:

UAS

Industry:

Manufacturing & Operations

Services Provided

IT Consulting

Client Overview

A multi-specialty diagnostic center aimed to enhance early detection of brain lesions and tumours using AI-powered medical imaging analysis to support radiologists and reduce reporting time.

Business Challenge

  • Increasing MRI scan volumes
  • Delays in radiology reporting
  • Risk of human error in early-stage lesion detection
  • Need for faster second-opinion support
  • Requirement for HIPAA-compliant and secure AI processing

Solution Implemented

We developed an AI-driven Brain Lesion & Tumor Detection System using deep learning models trained on annotated MRI datasets.

Key Components:

  • Convolutional Neural Network (CNN)-based image classification
  • Automated lesion segmentation
  • Tumour grading assistance
  • Radiologist dashboard with heatmap visualization
  • Cloud-based secure processing architecture
  • PACS integration support

Technology Stack

  • AI/ML Frameworks: TensorFlow / PyTorch
  • Medical Imaging: DICOM processing
  • Cloud Infrastructure: AWS secure environment
  • Backend: Python
  • Dashboard: Web-based analytics portal

POC & Validation

  • Trained on 50,000+ anonymized MRI images
  • Achieved 94% detection accuracy in POC phase
  • Reduced preliminary screening time by 60%
  • Assisted radiologists with AI-highlighted regions of concern

Security & Compliance

  • End-to-end encryption (at rest & in transit)
  • Role-based access control
  • Audit logs for diagnostic tracking
  • GDPR & HIPAA-ready architecture

Business Impact

  • Faster diagnostic turnaround
  • Improved early-stage tumour identification
  • Reduced radiologist workload
  • Enhanced patient confidence
  • Scalable for multi-center deployment

Future Enhancements

  • Multi-modal imaging integration (CT + MRI)
  • Predictive tumour growth analytics
  • AI-assisted treatment recommendation support

Conclusion

The AI Brain Lesion & Tumour Detection System successfully enhanced diagnostic accuracy and operational efficiency, positioning the client as a technology-driven healthcare provider.

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