Raspberry Pi 5 Medical Imaging Edge Inference Kit — Point-of-Care AI Diagnostics Without the Cloud

Every part needed, pre-tested for compatibility, with an AI build companion trained on medical imaging inference. Shipped from Bengaluru in 3-5 days.

Build a portable, privacy-preserving diagnostic assistant that classifies chest X-rays and analyses retinal fundus images right at the point of care. Using a Raspberry Pi 5 with an NVMe SSD, you deploy TensorFlow Lite models that deliver AI inference without any network connection — demonstrating how India’s healthcare tech can move beyond cloud dependency.

What You'll Build

A standalone medical imaging inference station that loads quantized TFLite models for pneumonia/normal chest X-ray classification and diabetic retinopathy detection from fundus photographs. The 7‑inch HDMI display becomes your diagnostic dashboard, showing real‑time results with confidence scores. The entire pipeline runs locally on the Pi 5’s quad‑core processor, accelerated by the M.2 HAT+ and NVMe SSD, making it suitable for low‑resource clinical settings or hackathon demos like the Smart India Hackathon.

What You'll Learn

• Deploy quantized TFLite models on a Raspberry Pi 5 and measure inference latency on CPU and GPU delegates
• Optimize the medical imaging pipeline using NVMe storage over M.2 HAT+ to handle large DICOM and JPEG inputs
• Pre‑process chest X‑rays and retinal fundus images (resizing, normalization, CLAHE) for model compatibility
• Build a responsive Python UI with Tkinter or PyQt5 that displays predictions and stores results locally

Kit Contents

Why Buy This Kit Instead of Sourcing Parts Separately

Who This Kit Is For

Designed for B.Tech ECE and EEE students in their final year who need a capstone project that combines embedded systems with practical AI. It’s equally relevant for Smart India Hackathon teams building healthcare innovation, and for IoT/AI engineers prototyping edge medical devices at IITs, NITs, VIT, or BITS. The kit assumes intermediate Python skills and a working knowledge of machine learning concepts, but the AI companion fills any gaps in TensorFlow Lite deployment.

Built and Backed by Compoden

Every Compoden kit ships with an AI build companion trained on this exact project — accessible via a QR code on the box, with WhatsApp and email backup. We've spent 10 years building projects for makers, schools, and institutions across India. If a part fails because of a manufacturing defect, replace it free within 7 days.