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<html lang="en">
<head>
<meta charset="UTF-8" />
<title>NeuraScan</title>
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<style>
:root{
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.examples .ex{
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.examples .desc{padding:0 10px 10px;color:var(--muted)}
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.modal{
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border-radius:16px;
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width:420px;
}
</style>
</head>
<body>
<header>
<div class="brand">
<img src="{{ url_for('static', filename='assets/brain/brain.svg') }}">
<div>
<strong>NeuraScan</strong><br>
<small style="color:var(--muted)">AI-assisted MRI screening (demo)</small>
</div>
</div>
<button id="themeToggle" class="chip">☀️</button>
</header>
<nav>
<button class="tab active" onclick="showSection('scan',this)">Scan</button>
<button class="tab" onclick="showSection('info',this)">Info</button>
</nav>
<section id="scan" class="section show">
<main>
<div class="card">
<h2>New scan</h2>
<div class="controls">
<span class="select-wrap"><select id="modelSelect"></select></span>
<label class="file-btn">
Choose image
<input type="file" id="fileInput" accept="image/*" hidden>
</label>
<button class="primary" id="runBtn" onclick="runScan()">Run scan</button>
<button class="secondary" id="newBtn" style="display:none" onclick="newScan()">New scan</button>
</div>
<div class="upload-box" id="dropZone">
Drag & drop or paste (Ctrl+V) an MRI image
</div>
<div class="preview hidden" id="previewBox">
<img id="previewImg">
</div>
<div class="result">
<div id="resultTitle" class="result-title">—</div>
<div id="resultMsg" class="result-msg">Upload an image to begin.</div>
<button id="likelyBtn" class="secondary" style="display:none;margin-top:10px" onclick="showLikely()">Show most likely result</button>
</div>
</div>
<div class="card">
<h2>Examples</h2>
<div class="examples">
<div class="ex">
<div class="lbl">Supported example</div>
<div class="desc">Brain-only MRI slice (no skull visible).</div>
<img src="{{ url_for('static', filename='assets/brain/supportedexample.jpg') }}">
</div>
<div class="ex">
<div class="lbl">Unsupported example</div>
<div class="desc">Skull visible — please upload a brain-only slice.</div>
<img src="{{ url_for('static', filename='assets/brain/unsupportedexample.jpg') }}">
</div>
</div>
</div>
</main>
</section>
<section id="info" class="section">
<main>
<div class="card">
<h2>About NeuraScan</h2>
<p>Educational demo for Alzheimer’s stage classification. Low confidence → <b>Uncertain</b>.</p>
<h2>Under the supervision of:</h2>
<p>
Prof. Muhammad Sayed Hammad<br>
Eng. Heidi Ahmed
</p>
<h2>Team</h2>
<div class="team">
<div class="member"><img src="{{ url_for('static', filename='assets/images/team/fatma.jpg') }}" onclick="window.open('https://www.linkedin.com/in/fatma-al-zahraa-emad-326b64234/')"><span>Fatma Al-Zahraa Emad</span></div>
<div class="member"><img src="{{ url_for('static', filename='assets/images/team/gehad.jpg') }}" onclick="window.open('https://www.linkedin.com/in/gehad-mohamed-2a4946252/')"><span>Gehad Mohamed</span></div>
<div class="member"><img src="{{ url_for('static', filename='assets/images/team/heba.jpg') }}" onclick="window.open('https://www.linkedin.com/in/hebatullah-elgazoly-308ab2243/')"><span>Hebatullah El Gazoly</span></div>
<div class="member"><img src="{{ url_for('static', filename='assets/images/team/asem.jpg') }}" onclick="window.open('https://www.linkedin.com/in/mohamedasem318/')"><span>Mohamed Assem</span></div>
<div class="member"><img src="{{ url_for('static', filename='assets/images/team/sameh.jpg') }}" onclick="window.open('https://www.linkedin.com/in/muhamedsameh/')"><span>Mohamed Sameh</span></div>
</div>
</div>
</main>
</section>
<footer>
Contact: <a href="mailto:mohamedasem318@gmail.com">Mohamed Assem</a> •
<a href="mailto:mohamed.sameh8103@gmail.com">Mohamed Sameh</a><br>
Educational demo — not medical advice
</footer>
<div class="modal-backdrop" id="modalBackdrop" onclick="closeModalIfBackdrop(event)">
<div class="modal">
<h3>Most likely result</h3>
<p id="modalLabel"></p>
<p id="modalProb"></p>
<button class="secondary" onclick="closeModal()">Close</button>
</div>
</div>
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async function loadModels(){
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async function runScan(){
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resultTitle.textContent="Running…";
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fd.append("file",currentFile);
fd.append("model_id",modelSelect.value);
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const d=await r.json();
if(d.prediction.label==="Uncertain"){
resultTitle.textContent="Uncertain";
resultMsg.textContent="Consult a professional.";
const probs=[...(d.probabilities||[])].sort((a,b)=>b.prob-a.prob);
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likelyBtn.style.display="inline-block";
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loadModels();
</script>
</body>
</html>
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