More than 50 million people worldwide need MRI interpretation every year, yet neuroradiologists are scarce and expensive. Neurolytics lets anyone upload a brain MRI, receive an AI‑driven diagnostic summary, and ask follow‑up questions in natural language – all inside a single web page.
We combine Next.js, Google Gemini Vision, and AWS S3 to deliver expert‑level insights in seconds, freeing clinicians to focus on critical cases and empowering students to learn neuro‑oncology hands‑on.
| Step | Action | Tech |
|---|---|---|
| 1 | Upload any T1/T2 slice (JPEG/PNG) | Next.js file input |
| 2 | Instant Analysis of tumor type, grey‑matter loss, abnormalities | Gemini Vision 2.0 |
| 3 | One‑Click Chat – ask anything about the scan with grounded answers | Gemini LLM + JSON context |
| 4 | Auto‑Archival – each run saved to S3 and visible in History tab | AWS S3 |
- Context‑Grounded Chat – every reply cites the exact JSON analysis, avoiding hallucinations.
- Timestamp Keys – frontend & backend stay perfectly in‑sync even with concurrent uploads.
- Zero‑Sound UX – purely visual + textual; ideal for quiet clinical settings.
- Plug‑and‑Play Cloud – no GPUs needed; Gemini handles all computation.
User ─▶ Next.js ──▶ Flask API ──▶ Gemini Vision
│ ▲ │
│ │ └──▶ AWS S3 (images + JSON + summary)
▼ │
Chat UI ◀──────────┘
- /analyze_mri → uploads image, gets JSON analysis, stores to
saved/<timestamp>/. - /chat → receives
{ prompt, timestamp }, loads matching JSON, returns answer. - /history → lists past runs with thumbnails & summaries.
- Frontend –
Next.js 14,TypeScript,TailwindCSS,shadcn/ui - Backend –
Python 3.10,Flask,google-generativeai,boto3 - Cloud –
AWS S3,GitHub Actions(CI/CD)
| Verb | Endpoint | Payload | Returns |
|---|---|---|---|
| POST | /analyze_mri |
form‑data file |
{ timestamp, image_url, … } |
| POST | /chat |
{ prompt, timestamp } |
{ response } |
| GET | /history |
– | [{ timestamp, mri_url, summary }] |
- Segmentation overlay masks
- DICOM upload + series handling
- HIPAA‑grade audit logging


