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| <title>ICH Detection Pipeline — AI-Powered CT Brain Scan Analysis</title> |
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| content="Clinical-grade intracranial hemorrhage detection using deep learning. Upload DICOM CT scans and get instant AI-powered screening with Grad-CAM heatmaps and triage reports." /> |
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| <span class="brand-name">ICH <span>Pipeline</span></span> |
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| <a href="{{ url_for('auth.login') }}" class="btn-ghost">Sign In</a> |
| <a href="{{ url_for('auth.register') }}" class="btn-primary"> |
| Get Started |
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| AI-Powered Medical Screening |
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| <h1> |
| Detect Brain Hemorrhage<br> |
| <span class="grad">In Seconds, Not Hours</span> |
| </h1> |
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| <p class="hero-sub"> |
| Upload a DICOM CT brain scan and get an AI-powered hemorrhage probability score, |
| Grad-CAM heatmap visualization, and automated clinical triage report — instantly. |
| </p> |
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| Start Screening Free |
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| Sign In to Dashboard |
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| <div class="trust-bar"> |
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| EfficientNet-B4 Model |
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| Grad-CAM Heatmaps |
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| Calibrated Confidence Scores |
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| Automated Triage |
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| <div class="stat-num">~90%</div> |
| <div class="stat-desc">Sensitivity on ICH-positive slices</div> |
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| <div class="stat-item"> |
| <div class="stat-num">< 30s</div> |
| <div class="stat-desc">Time to first result per scan</div> |
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| <div class="stat-item"> |
| <div class="stat-num">DICOM</div> |
| <div class="stat-desc">Native .dcm & .zip batch support</div> |
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| <section class="features"> |
| <div class="section-label">Core Capabilities</div> |
| <h2 class="section-title">Everything a radiologist needs — fast</h2> |
| <p class="section-sub">From raw DICOM upload to clinical-grade report in under a minute.</p> |
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| <h3>Batch DICOM Processing</h3> |
| <p>Upload a .dcm file or a .zip archive of hundreds of slices. The pipeline handles CT windowing, preprocessing, |
| and inference on every slice automatically.</p> |
| </div> |
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| <div class="feat-icon" style="background:rgba(52,211,153,0.1);border-color:rgba(52,211,153,0.2);color:#34d399;"> |
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| <h3>Calibrated AI Confidence</h3> |
| <p>Our EfficientNet-B4 model outputs probability scores calibrated with temperature scaling, so a 90% score |
| actually means 90%.</p> |
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| style="background:rgba(251,113,133,0.1);border-color:rgba(251,113,133,0.2);color:#fb7185;"> |
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| <h3>Grad-CAM Heatmaps</h3> |
| <p>Gradient-weighted class activation maps overlay on every scan, highlighting the exact regions that drove the |
| model's hemorrhage prediction.</p> |
| </div> |
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| <div class="feat-card"> |
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| style="background:rgba(129,140,248,0.1);border-color:rgba(129,140,248,0.2);color:#818cf8;"> |
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| <h3>LLM Clinical Summary</h3> |
| <p>Each scan triggers a Groq-powered LLM that generates a human-readable clinical narrative with triage action |
| and urgency classification.</p> |
| </div> |
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| <h3>Model Evaluation Metrics</h3> |
| <p>Built-in evaluation dashboard with ROC curves, calibration plots, and confidence band analysis to track model |
| performance over time.</p> |
| </div> |
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| <div class="feat-card"> |
| <div class="feat-icon" style="background:rgba(52,211,153,0.1);border-color:rgba(52,211,153,0.2);color:#34d399;"> |
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| <h3>Secure & Isolated</h3> |
| <p>Every user gets their own isolated data directory. All uploads are user-scoped and access-controlled with |
| rate limiting and audit logs.</p> |
| </div> |
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| </div> |
| </section> |
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| <section class="how"> |
| <div class="section-label">Workflow</div> |
| <h2 class="section-title">Four steps to a clinical report</h2> |
| <p class="section-sub" style="margin-bottom:48px;">The entire pipeline runs in the background — you just upload and |
| wait.</p> |
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| <div class="steps"> |
| <div class="step"> |
| <div class="step-num">1</div> |
| <h4>Upload DICOM</h4> |
| <p>Upload a .dcm slice or a .zip batch. Single exams or full series are both supported.</p> |
| </div> |
| <div class="step"> |
| <div class="step-num">2</div> |
| <h4>AI Inference</h4> |
| <p>EfficientNet-B4 scores each slice for ICH probability with calibrated confidence.</p> |
| </div> |
| <div class="step"> |
| <div class="step-num">3</div> |
| <h4>Grad-CAM</h4> |
| <p>Gradient-weighted heatmaps highlight regions driving the hemorrhage prediction.</p> |
| </div> |
| <div class="step"> |
| <div class="step-num">4</div> |
| <h4>Clinical Report</h4> |
| <p>Auto-generated PDF report with findings, confidence bands, and triage action.</p> |
| </div> |
| </div> |
| </section> |
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| <section class="cta-section"> |
| <h2>Ready to try it?</h2> |
| <p>Create a free account and upload your first scan in under a minute.</p> |
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| <div class="disclaimer"> |
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| <span> |
| <strong>Medical Disclaimer:</strong> This is an AI-assisted screening tool and does <strong>not</strong> |
| constitute a medical diagnosis. All findings must be reviewed by a qualified medical professional |
| before any clinical action is taken. |
| </span> |
| </div> |
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| Create Free Account |
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| </section> |
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| |
| <footer> |
| <p>ICH Detection Pipeline — AI screening tool, not a diagnostic device.</p> |
| <p style="margin-top:6px;font-size:0.78rem;opacity:0.6;">All findings must be reviewed by a qualified medical |
| professional.</p> |
| </footer> |
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