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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Brain Tumor Segmentation</title>
<style>
* {
margin: 0;
padding: 0;
box-sizing: border-box;
}
body {
font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
min-height: 100vh;
padding: 20px;
display: flex;
flex-direction: column;
align-items: center;
}
.container {
max-width: 1400px;
width: 100%;
background: rgba(255, 255, 255, 0.95);
border-radius: 20px;
box-shadow: 0 20px 60px rgba(0, 0, 0, 0.3);
overflow: hidden;
}
.header {
background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
color: white;
padding: 40px;
text-align: center;
}
.header h1 {
font-size: 2.5em;
margin-bottom: 10px;
display: flex;
align-items: center;
justify-content: center;
gap: 15px;
}
.header p {
font-size: 1.1em;
opacity: 0.95;
}
.content {
padding: 40px;
}
.info-section {
background: linear-gradient(135deg, #f8f9fa 0%, #e9ecef 100%);
border-radius: 15px;
padding: 30px;
margin-bottom: 30px;
border-left: 5px solid #667eea;
}
.info-section h2 {
color: #667eea;
margin-bottom: 20px;
font-size: 1.8em;
}
.info-grid {
display: grid;
grid-template-columns: repeat(auto-fit, minmax(300px, 1fr));
gap: 20px;
margin-top: 20px;
}
.info-card {
background: white;
padding: 20px;
border-radius: 10px;
box-shadow: 0 2px 10px rgba(0, 0, 0, 0.1);
}
.info-card h3 {
color: #764ba2;
margin-bottom: 10px;
font-size: 1.2em;
display: flex;
align-items: center;
gap: 10px;
}
.info-card p {
color: #495057;
line-height: 1.6;
}
.info-card ul {
margin-top: 10px;
margin-left: 20px;
color: #495057;
}
.info-card li {
margin: 5px 0;
}
.github-link {
display: inline-flex;
align-items: center;
gap: 8px;
color: #667eea;
text-decoration: none;
font-weight: 600;
font-size: 1.1em;
padding: 10px 20px;
background: white;
border-radius: 8px;
box-shadow: 0 2px 8px rgba(0,0,0,0.1);
transition: all 0.3s;
}
.github-link:hover {
transform: translateY(-2px);
box-shadow: 0 4px 12px rgba(102, 126, 234, 0.3);
color: #764ba2;
}
.upload-section {
background: #f8f9fa;
border-radius: 15px;
padding: 40px;
text-align: center;
margin-bottom: 30px;
border: 3px dashed #667eea;
transition: all 0.3s;
}
.upload-section:hover {
border-color: #764ba2;
background: #f0f1f5;
}
.upload-section.dragover {
background: #e3e8ff;
border-color: #764ba2;
}
.upload-icon {
font-size: 4em;
margin-bottom: 20px;
color: #667eea;
}
.file-input-wrapper {
position: relative;
display: inline-block;
margin: 20px 0;
}
input[type="file"] {
display: none;
}
.file-input-label {
background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
color: white;
padding: 15px 40px;
border-radius: 50px;
cursor: pointer;
font-size: 1.1em;
font-weight: 600;
transition: all 0.3s;
display: inline-block;
box-shadow: 0 4px 15px rgba(102, 126, 234, 0.4);
}
.file-input-label:hover {
transform: translateY(-2px);
box-shadow: 0 6px 20px rgba(102, 126, 234, 0.6);
}
.example-btn {
background: #6c757d;
color: white;
padding: 12px 30px;
border: none;
border-radius: 50px;
cursor: pointer;
font-size: 1em;
margin-left: 15px;
transition: all 0.3s;
}
.example-btn:hover {
background: #5a6268;
transform: translateY(-2px);
}
.selected-file {
margin-top: 20px;
color: #667eea;
font-weight: 600;
font-size: 1.1em;
}
.analyze-btn {
background: linear-gradient(135deg, #11998e 0%, #38ef7d 100%);
color: white;
padding: 15px 50px;
border: none;
border-radius: 50px;
cursor: pointer;
font-size: 1.2em;
font-weight: 600;
margin-top: 20px;
transition: all 0.3s;
box-shadow: 0 4px 15px rgba(17, 153, 142, 0.4);
}
.analyze-btn:hover:not(:disabled) {
transform: translateY(-2px);
box-shadow: 0 6px 20px rgba(17, 153, 142, 0.6);
}
.analyze-btn:disabled {
background: #ccc;
cursor: not-allowed;
box-shadow: none;
}
.loading {
display: none;
margin: 30px 0;
text-align: center;
}
.spinner {
border: 4px solid #f3f3f3;
border-top: 4px solid #667eea;
border-radius: 50%;
width: 50px;
height: 50px;
animation: spin 1s linear infinite;
margin: 0 auto 20px;
}
@keyframes spin {
0% { transform: rotate(0deg); }
100% { transform: rotate(360deg); }
}
.results {
display: none;
margin-top: 40px;
}
.results-grid {
display: grid;
grid-template-columns: repeat(auto-fit, minmax(350px, 1fr));
gap: 25px;
margin-top: 25px;
}
.result-card {
background: white;
border-radius: 15px;
padding: 20px;
box-shadow: 0 4px 20px rgba(0, 0, 0, 0.1);
transition: all 0.3s;
}
.result-card:hover {
transform: translateY(-5px);
box-shadow: 0 6px 30px rgba(0, 0, 0, 0.15);
}
.result-card h3 {
color: #667eea;
margin-bottom: 15px;
font-size: 1.3em;
}
.result-card img {
width: 100%;
border-radius: 10px;
margin-bottom: 15px;
}
.stats {
background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
color: white;
border-radius: 15px;
padding: 30px;
margin-top: 25px;
text-align: center;
}
.stats h3 {
font-size: 1.5em;
margin-bottom: 20px;
}
.stats-grid {
display: grid;
grid-template-columns: repeat(auto-fit, minmax(200px, 1fr));
gap: 20px;
}
.stat-item {
background: rgba(255, 255, 255, 0.2);
padding: 20px;
border-radius: 10px;
}
.stat-value {
font-size: 2em;
font-weight: bold;
margin: 10px 0;
}
.stat-label {
font-size: 0.9em;
opacity: 0.9;
}
.error {
background: #f8d7da;
color: #721c24;
padding: 20px;
border-radius: 10px;
margin: 20px 0;
display: none;
}
.footer {
background: #f8f9fa;
padding: 30px;
text-align: center;
color: #6c757d;
margin-top: 40px;
}
@media (max-width: 768px) {
.header h1 {
font-size: 1.8em;
}
.results-grid {
grid-template-columns: 1fr;
}
.content {
padding: 20px;
}
}
</style>
</head>
<body>
<div class="container">
<div class="header">
<h1>
<span>🧠</span>
Brain Tumor Segmentation
<span>🔬</span>
</h1>
<p>AI-Powered Medical Image Analysis for Brain MRI Scans</p>
</div>
<div class="content">
<!-- Info Section -->
<div class="info-section">
<p style="color: #495057; font-size: 1.05em; line-height: 1.6; margin-bottom: 15px;">
<strong>🧠 This app performs automatic brain tumor segmentation</strong> using a U-Net deep learning model trained on BraTS dataset.
Upload a <strong>.mha brain MRI file</strong> (FLAIR modality) and get pixel-level tumor detection with visualization.
</p>
<a href="https://github.com/koesan/Brain_Segmentation" target="_blank" class="github-link">
<svg width="24" height="24" viewBox="0 0 24 24" fill="currentColor">
<path d="M12 0c-6.626 0-12 5.373-12 12 0 5.302 3.438 9.8 8.207 11.387.599.111.793-.261.793-.577v-2.234c-3.338.726-4.033-1.416-4.033-1.416-.546-1.387-1.333-1.756-1.333-1.756-1.089-.745.083-.729.083-.729 1.205.084 1.839 1.237 1.839 1.237 1.07 1.834 2.807 1.304 3.492.997.107-.775.418-1.305.762-1.604-2.665-.305-5.467-1.334-5.467-5.931 0-1.311.469-2.381 1.236-3.221-.124-.303-.535-1.524.117-3.176 0 0 1.008-.322 3.301 1.23.957-.266 1.983-.399 3.003-.404 1.02.005 2.047.138 3.006.404 2.291-1.552 3.297-1.23 3.297-1.23.653 1.653.242 2.874.118 3.176.77.84 1.235 1.911 1.235 3.221 0 4.609-2.807 5.624-5.479 5.921.43.372.823 1.102.823 2.222v3.293c0 .319.192.694.801.576 4.765-1.589 8.199-6.086 8.199-11.386 0-6.627-5.373-12-12-12z"/>
</svg>
View on GitHub
</a>
</div>
<div class="upload-section" id="dropZone">
<div class="upload-icon">📤</div>
<h2 style="color: #667eea; margin-bottom: 15px;">Upload Brain MRI Scan (.mha)</h2>
<p style="color: #6c757d; margin-bottom: 20px;">
Drag and drop your .mha MRI file here or click to browse
</p>
<div class="file-input-wrapper">
<input type="file" id="fileInput" accept=".mha">
<label for="fileInput" class="file-input-label">
Choose .mha File
</label>
<button class="example-btn" onclick="testExample()">
🧪 Test Example
</button>
</div>
<div class="selected-file" id="selectedFile"></div>
<button class="analyze-btn" id="analyzeBtn" onclick="analyzeBrain()" disabled>
Analyze Brain Scan
</button>
</div>
<div class="loading" id="loading">
<div class="spinner"></div>
<p style="color: #667eea; font-size: 1.2em;">Analyzing brain scan...</p>
</div>
<div class="error" id="error"></div>
<div class="results" id="results">
<h2 style="color: #667eea; margin-bottom: 20px;">Segmentation Results</h2>
<div class="results-grid">
<div class="result-card">
<h3>🖼️ Original MRI</h3>
<img id="originalImg" src="" alt="Original">
</div>
<div class="result-card">
<h3>🎯 Tumor Mask</h3>
<img id="maskImg" src="" alt="Mask">
</div>
<div class="result-card">
<h3>🔍 Overlay</h3>
<img id="overlayImg" src="" alt="Overlay">
</div>
</div>
<div class="stats">
<h3>📊 Analysis Statistics</h3>
<div class="stats-grid">
<div class="stat-item">
<div class="stat-label">Tumor Coverage</div>
<div class="stat-value" id="tumorPercentage">-</div>
<div class="stat-label">of brain area</div>
</div>
<div class="stat-item">
<div class="stat-label">Image Resolution</div>
<div class="stat-value" id="imageSize">-</div>
<div class="stat-label">pixels</div>
</div>
</div>
</div>
</div>
</div>
<div class="footer">
<p>⚠️ For research and educational purposes only. Not for clinical diagnosis.</p>
<p style="margin-top: 10px;">Powered by Deep Learning | TensorFlow & Keras</p>
</div>
</div>
<script>
let selectedFile = null;
// File input change handler
document.getElementById('fileInput').addEventListener('change', function(e) {
if (e.target.files.length > 0) {
selectedFile = e.target.files[0];
document.getElementById('selectedFile').textContent = '✓ ' + selectedFile.name;
document.getElementById('analyzeBtn').disabled = false;
hideResults();
}
});
// Drag and drop handlers
const dropZone = document.getElementById('dropZone');
dropZone.addEventListener('dragover', (e) => {
e.preventDefault();
dropZone.classList.add('dragover');
});
dropZone.addEventListener('dragleave', () => {
dropZone.classList.remove('dragover');
});
dropZone.addEventListener('drop', (e) => {
e.preventDefault();
dropZone.classList.remove('dragover');
const files = e.dataTransfer.files;
if (files.length > 0) {
selectedFile = files[0];
document.getElementById('fileInput').files = files;
document.getElementById('selectedFile').textContent = '✓ ' + selectedFile.name;
document.getElementById('analyzeBtn').disabled = false;
hideResults();
}
});
// Test with example MHA file
function testExample() {
// Show loading
document.getElementById('loading').style.display = 'block';
document.getElementById('results').style.display = 'none';
document.getElementById('error').style.display = 'none';
document.getElementById('selectedFile').textContent = '🧪 Testing with example MRI...';
fetch('/test-example', {
method: 'POST'
})
.then(response => response.json())
.then(data => {
if (data.error) {
showError(data.error);
} else {
document.getElementById('selectedFile').textContent = '✓ Example: VSD.Brain.XX.O.MR_Flair.35796.mha';
showResults(data);
}
})
.catch(error => {
showError('Example test failed: ' + error.message);
})
.finally(() => {
document.getElementById('loading').style.display = 'none';
});
}
// Analyze brain scan
function analyzeBrain() {
if (!selectedFile) {
showError('Please select a file first');
return;
}
const formData = new FormData();
formData.append('file', selectedFile);
// Show loading
document.getElementById('loading').style.display = 'block';
document.getElementById('results').style.display = 'none';
document.getElementById('error').style.display = 'none';
document.getElementById('analyzeBtn').disabled = true;
fetch('/predict', {
method: 'POST',
body: formData
})
.then(response => response.json())
.then(data => {
if (data.error) {
showError(data.error);
} else {
showResults(data);
}
})
.catch(error => {
showError('Analysis failed: ' + error.message);
})
.finally(() => {
document.getElementById('loading').style.display = 'none';
document.getElementById('analyzeBtn').disabled = false;
});
}
// Show results
function showResults(data) {
document.getElementById('originalImg').src = data.original;
document.getElementById('maskImg').src = data.mask;
document.getElementById('overlayImg').src = data.overlay;
document.getElementById('tumorPercentage').textContent = data.tumor_percentage.toFixed(2) + '%';
document.getElementById('imageSize').textContent = data.image_size;
document.getElementById('results').style.display = 'block';
// Scroll to results
document.getElementById('results').scrollIntoView({ behavior: 'smooth' });
}
// Show error
function showError(message) {
document.getElementById('error').textContent = '❌ ' + message;
document.getElementById('error').style.display = 'block';
setTimeout(() => {
document.getElementById('error').style.display = 'none';
}, 5000);
}
// Hide results
function hideResults() {
document.getElementById('results').style.display = 'none';
document.getElementById('error').style.display = 'none';
}
</script>
</body>
</html>