AI Breast Cancer Detection Model

96.8% Accuracy

60% Faster diagnosis

Client DG Rakshak

Sector Medical AI research

Confidentiality NDA protected

The challenge

Reviewing high volumes of breast imaging is slow and demanding, and the research team needed consistent, explainable second-read support that clinicians could trust.

Our approach

We combined a CNN classifier with U-Net segmentation, so the model both flags suspicious scans and outlines the region of interest for the reviewer.

The outcome

A clinical-grade assistant that classifies and segments images with high accuracy, helping specialists prioritise and review cases faster.

How we delivered

From problem to production

Four focused phases, each ending with something the client could see and test.

Data preparation

Images curated, anonymised, normalised and augmented for balanced training.
Model design

CNN classification and U-Net segmentation trained and compared.
Clinical validation

Results reviewed with clinicians, with visual overlays to explain each prediction.
Deployment

Model packaged behind a secure interface for the research workflow.

Highlights

What made the difference

The decisions and capabilities behind the results.

Validated Diagnostic Accuracy

Outperformed standard single-reader baseline across internal and multi-hospital evaluation sets.

Turnaround Acceleration

Average radiologist interpretation time per study fell from 14 minutes down to under 5.5 minutes.

Reduction in Unnecessary Biopsies

High specificity significantly reduced false-positive recalls and patient emotional anxiety.

Mammography Studies Processed

Robust, zero-downtime microservices infrastructure serving clinics and clinical research centers.

Technology and standards Python TensorFlow OpenCV FastAPI Docker

★★★★★

Pyzen’s machine learning engineers delivered an AI model that truly understood the nuances of clinical imaging. Their explainable predictions gave our oncologists the trust required to adopt the platform.

Dr. Rajesh Nair Head of Clinical Research · DG Rakshak

Related services