RSK World - Medical Imaging Dataset - Project Files Browser | RSK World

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    Medical Imaging Dataset - Demo Page
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    Project: Medical Imaging Dataset
    Website: https://rskworld.in
    Contact: help@rskworld.in, support@rskworld.in
    Phone: +91 93305 39277
    Founder: Molla Samser
    Designer & Tester: Rima Khatun
    
    This project contains medical images including X-rays, CT scans, and MRI images
    with diagnostic labels and annotations for medical image analysis.
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                <i class="fas fa-image text-info"></i> Medical Imaging Dataset
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    <!-- Hero Section -->
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            <h1 class="display-4 fw-bold mb-4">
                <i class="fas fa-image text-info"></i> Medical Imaging Dataset
            </h1>
            <p class="lead mb-4">Medical image dataset with X-rays, CT scans, and MRI images with diagnostic labels for medical image analysis and disease detection.</p>
            <div class="mt-4">
                <span class="badge bg-warning text-dark fs-6 px-3 py-2">Advanced Difficulty</span>
                <span class="badge bg-info text-dark fs-6 px-3 py-2 ms-2">Image Data</span>
            </div>
        </div>
    </section>

    <!-- Overview Section -->
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                        <h2 class="card-title mb-4">
                            <i class="fas fa-info-circle text-info"></i> Project Overview
                        </h2>
                        <p class="card-text lead">
                            This dataset contains medical images including X-rays, CT scans, and MRI images with diagnostic labels and annotations. 
                            Perfect for medical image analysis, disease detection, computer-aided diagnosis, and healthcare AI applications.
                        </p>
                        <p class="card-text">
                            The dataset is designed for researchers, data scientists, and developers working on medical imaging AI projects. 
                            It includes various imaging modalities with corresponding diagnostic information to facilitate training and evaluation 
                            of machine learning models for healthcare applications.
                        </p>
                    </div>
                </div>
            </div>
        </div>
    </section>

    <!-- Features Section -->
    <section id="features" class="container mb-5">
        <h2 class="text-center mb-5 text-white">
            <i class="fas fa-star text-warning"></i> All Project Features
        </h2>
        
        <!-- Feature 1: Data Loading -->
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                        <h4 class="card-title mb-3">
                            <i class="fas fa-code text-info"></i> 1. Data Loading & Dataset Management
                        </h4>
                        <p class="card-text mb-3">
                            Load medical images from X-ray, CT scan, and MRI datasets with automatic label matching. 
                            Supports multiple image formats including PNG, JPG, JPEG, and DICOM.
                        </p>
                        <div class="bg-dark text-light p-3 rounded mb-3">
                            <code class="text-info">from scripts.load_data import MedicalImagingDataset</code><br>
                            <code class="text-success">dataset = MedicalImagingDataset(data_path='./data')</code><br>
                            <code class="text-warning">xray_images, xray_labels = dataset.load_xray_images()</code><br>
                            <code class="text-warning">ct_images, ct_labels = dataset.load_ct_images()</code><br>
                            <code class="text-warning">mri_images, mri_labels = dataset.load_mri_images()</code>
                        </div>
                        <ul class="list-unstyled">
                            <li><i class="fas fa-check text-success"></i> Automatic image-label pairing</li>
                            <li><i class="fas fa-check text-success"></i> Support for PNG, JPG, JPEG formats</li>
                            <li><i class="fas fa-check text-success"></i> DICOM file support (with pydicom)</li>
                            <li><i class="fas fa-check text-success"></i> JSON label loading with error handling</li>
                        </ul>
                    </div>
                </div>
            </div>
        </div>

        <!-- Feature 2: Image Preprocessing -->
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                            <i class="fas fa-sliders-h text-info"></i> 2. Advanced Image Preprocessing
                        </h4>
                        <p class="card-text mb-3">
                            Professional preprocessing pipeline with modality-specific enhancements including CLAHE, 
                            noise reduction, normalization, and window/level adjustments.
                        </p>
                        <div class="bg-dark text-light p-3 rounded mb-3">
                            <code class="text-info">from scripts.preprocess import preprocess_image</code><br>
                            <code class="text-success">processed = preprocess_image('image.png', image_type='xray')</code><br>
                            <code class="text-success"># X-ray: CLAHE + Gaussian blur</code><br>
                            <code class="text-success"># CT Scan: Histogram equalization + Median filter</code><br>
                            <code class="text-success"># MRI: CLAHE + Bilateral filter</code>
                        </div>
                        <div class="row">
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                                <strong>Preprocessing Functions:</strong>
                                <ul>
                                    <li>CLAHE (Contrast Limited AHE)</li>
                                    <li>Gaussian blur for noise reduction</li>
                                    <li>Histogram equalization</li>
                                    <li>Median filtering</li>
                                    <li>Bilateral filtering</li>
                                    <li>Pixel normalization [0, 1]</li>
                                </ul>
                            </div>
                            <div class="col-md-6">
                                <strong>Modality-Specific:</strong>
                                <ul>
                                    <li><strong>X-ray:</strong> CLAHE + Gaussian blur</li>
                                    <li><strong>CT Scan:</strong> Histogram + Median filter</li>
                                    <li><strong>MRI:</strong> CLAHE + Bilateral filter</li>
                                    <li>Window/Level transformation</li>
                                    <li>Contrast enhancement</li>
                                    <li>Batch preprocessing support</li>
                                </ul>
                            </div>
                        </div>
                    </div>
                </div>
            </div>
        </div>

        <!-- Feature 3: Visualization -->
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                        <h4 class="card-title mb-3">
                            <i class="fas fa-eye text-info"></i> 3. Medical Image Visualization
                        </h4>
                        <p class="card-text mb-3">
                            Visualize medical images with diagnostic annotations, labels, and overlays. 
                            Includes batch visualization and preprocessing comparison tools.
                        </p>
                        <div class="bg-dark text-light p-3 rounded mb-3">
                            <code class="text-info">from scripts.visualize import visualize_medical_image</code><br>
                            <code class="text-success">visualize_medical_image('image.png', 'label.json')</code><br>
                            <code class="text-warning">visualize_batch(images, labels, cols=3)</code><br>
                            <code class="text-warning">compare_preprocessing('image.png')</code><br>
                            <code class="text-warning">plot_statistics(dataset_info)</code>
                        </div>
                        <ul class="list-unstyled">
                            <li><i class="fas fa-check text-success"></i> Single image visualization with annotations</li>
                            <li><i class="fas fa-check text-success"></i> Batch image grid visualization</li>
                            <li><i class="fas fa-check text-success"></i> Before/After preprocessing comparison</li>
                            <li><i class="fas fa-check text-success"></i> Dataset statistics charts (bar/pie)</li>
                            <li><i class="fas fa-check text-success"></i> Diagnostic label overlay display</li>
                            <li><i class="fas fa-check text-success"></i> Confidence score visualization</li>
                        </ul>
                    </div>
                </div>
            </div>
        </div>

        <!-- Feature 4: Dataset Statistics -->
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                            <i class="fas fa-info-circle text-info"></i> 4. Dataset Statistics & Information
                        </h4>
                        <p class="card-text mb-3">
                            Get comprehensive dataset statistics including image counts, distribution, and metadata information.
                        </p>
                        <div class="bg-dark text-light p-3 rounded mb-3">
                            <code class="text-success">info = dataset.get_dataset_info()</code><br>
                            <code class="text-warning"># Returns: {'xray_count': 10, 'ct_count': 10,</code><br>
                            <code class="text-warning">#          'mri_count': 10, 'total_images': 30}</code>
                        </div>
                        <ul class="list-unstyled">
                            <li><i class="fas fa-check text-success"></i> Image count per modality</li>
                            <li><i class="fas fa-check text-success"></i> Total dataset statistics</li>
                            <li><i class="fas fa-check text-success"></i> Visual statistics plots</li>
                            <li><i class="fas fa-check text-success"></i> Bar charts and pie charts</li>
                        </ul>
                    </div>
                </div>
            </div>
        </div>

        <!-- Feature 5: Image Types -->
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                        <i class="fas fa-x-ray feature-icon"></i>
                        <h5 class="card-title">X-ray Images</h5>
                        <p class="card-text">Comprehensive collection of X-ray images with diagnostic annotations. Supports chest, abdomen, and extremity X-rays.</p>
                        <span class="badge bg-info">10 Images</span>
                    </div>
                </div>
            </div>
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                        <i class="fas fa-lungs feature-icon"></i>
                        <h5 class="card-title">CT Scan Images</h5>
                        <p class="card-text">CT scan images with detailed diagnostic labels for analysis. Includes head, chest, and abdomen CT scans.</p>
                        <span class="badge bg-info">10 Images</span>
                    </div>
                </div>
            </div>
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                        <i class="fas fa-brain feature-icon"></i>
                        <h5 class="card-title">MRI Images</h5>
                        <p class="card-text">MRI images with comprehensive diagnostic information. Brain, spine, and joint MRI scans included.</p>
                        <span class="badge bg-info">10 Images</span>
                    </div>
                </div>
            </div>
        </div>

        <!-- Feature 6: Additional Features -->
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                        <h5 class="card-title">
                            <i class="fas fa-tags text-info"></i> Diagnostic Labels
                        </h5>
                        <p class="card-text">All images include JSON-format diagnostic labels with:</p>
                        <ul>
                            <li>Diagnosis information</li>
                            <li>Confidence scores</li>
                            <li>Patient metadata (anonymized)</li>
                            <li>Annotations and findings</li>
                            <li>Date and modality information</li>
                        </ul>
                        <div class="bg-dark text-light p-2 rounded mt-2">
                            <small><code class="text-success">{"diagnosis": "Normal", "confidence": 0.95, ...}</code></small>
                        </div>
                    </div>
                </div>
            </div>
            <div class="col-md-6">
                <div class="card h-100">
                    <div class="card-body p-4">
                        <h5 class="card-title">
                            <i class="fas fa-file-medical text-info"></i> DICOM Support
                        </h5>
                        <p class="card-text">Full support for DICOM medical imaging format:</p>
                        <ul>
                            <li>Read and parse DICOM files</li>
                            <li>Extract pixel arrays</li>
                            <li>Automatic format detection</li>
                            <li>Compatible with medical imaging standards</li>
                        </ul>
                        <div class="bg-dark text-light p-2 rounded mt-2">
                            <small><code class="text-success"># Requires: pip install pydicom</code></small>
                        </div>
                    </div>
                </div>
            </div>
        </div>

        <!-- Feature 7: AI Ready -->
        <div class="card mt-4 bg-gradient" style="background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);">
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                <h4 class="card-title">Ready for Medical AI Models</h4>
                <p class="card-text lead">Pre-processed and formatted for immediate use in medical AI model training. 
                Perfect for deep learning, computer vision, and healthcare AI applications.</p>
                <div class="row mt-4">
                    <div class="col-md-4">
                        <i class="fas fa-brain fa-2x mb-2"></i>
                        <p>Deep Learning</p>
                    </div>
                    <div class="col-md-4">
                        <i class="fas fa-search fa-2x mb-2"></i>
                        <p>Computer Vision</p>
                    </div>
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                        <i class="fas fa-stethoscope fa-2x mb-2"></i>
                        <p>Healthcare AI</p>
                    </div>
                </div>
            </div>
        </div>
    </section>

    <!-- Image Gallery Section -->
    <section id="gallery" class="container mb-5">
        <h2 class="text-center mb-5 text-white">
            <i class="fas fa-images text-warning"></i> Dataset Image Gallery
        </h2>
        
        <!-- X-ray Images Gallery -->
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            <div class="card-header bg-info text-white">
                <h4 class="mb-0"><i class="fas fa-x-ray"></i> X-ray Images (10 images)</h4>
            </div>
            <div class="card-body p-4">
                <div class="row g-3" id="xray-gallery">
                    <div class="col-md-3 col-sm-4 col-6">
                        <div class="card h-100 shadow-sm">
                            <img src="data/xray/images/000001-1.jpg" class="card-img-top" alt="X-ray Image 1" style="height: 200px; object-fit: contain; background: #000;" onerror="this.style.display='none'">
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                                <small class="text-muted">000001-1.jpg</small>
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                            <img src="data/xray/images/000001-1.png" class="card-img-top" alt="X-ray Image 2" style="height: 200px; object-fit: contain; background: #000;" onerror="this.style.display='none'">
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                            <img src="data/xray/images/000001-10.jpg" class="card-img-top" alt="X-ray Image 3" style="height: 200px; object-fit: contain; background: #000;" onerror="this.style.display='none'">
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                            <img src="data/xray/images/000001-12.jpg" class="card-img-top" alt="X-ray Image 5" style="height: 200px; object-fit: contain; background: #000;" onerror="this.style.display='none'">
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                            <img src="data/xray/images/000001-13.jpg" class="card-img-top" alt="X-ray Image 6" style="height: 200px; object-fit: contain; background: #000;" onerror="this.style.display='none'">
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        <!-- CT Scan Images Gallery -->
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                <h4 class="mb-0"><i class="fas fa-lungs"></i> CT Scan Images (10 images)</h4>
            </div>
            <div class="card-body p-4">
                <div class="row g-3">
                    <div class="col-md-3 col-sm-4 col-6">
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                            <img src="data/ct_scan/images/000000.jpeg" class="card-img-top" alt="CT Scan 1" style="height: 200px; object-fit: contain; background: #000;" onerror="this.style.display='none'">
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                            <img src="data/ct_scan/images/000002.jpeg" class="card-img-top" alt="CT Scan 3" style="height: 200px; object-fit: contain; background: #000;" onerror="this.style.display='none'">
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                        <div class="card h-100 shadow-sm">
                            <img src="data/ct_scan/images/000003.jpeg" class="card-img-top" alt="CT Scan 4" style="height: 200px; object-fit: contain; background: #000;" onerror="this.style.display='none'">
                            <div class="card-body p-2 text-center">
                                <small class="text-muted">000003.jpeg</small>
                            </div>
                        </div>
                    </div>
                    <div class="col-md-3 col-sm-4 col-6">
                        <div class="card h-100 shadow-sm">
                            <img src="data/ct_scan/images/000004.jpeg" class="card-img-top" alt="CT Scan 5" style="height: 200px; object-fit: contain; background: #000;" onerror="this.style.display='none'">
                            <div class="card-body p-2 text-center">
                                <small class="text-muted">000004.jpeg</small>
                            </div>
                        </div>
                    </div>
                    <div class="col-md-3 col-sm-4 col-6">
                        <div class="card h-100 shadow-sm">
                            <img src="data/ct_scan/images/000005.jpeg" class="card-img-top" alt="CT Scan 6" style="height: 200px; object-fit: contain; background: #000;" onerror="this.style.display='none'">
                            <div class="card-body p-2 text-center">
                                <small class="text-muted">000005.jpeg</small>
                            </div>
                        </div>
                    </div>
                    <div class="col-md-3 col-sm-4 col-6">
                        <div class="card h-100 shadow-sm">
                            <img src="data/ct_scan/images/000006.jpeg" class="card-img-top" alt="CT Scan 7" style="height: 200px; object-fit: contain; background: #000;" onerror="this.style.display='none'">
                            <div class="card-body p-2 text-center">
                                <small class="text-muted">000006.jpeg</small>
                            </div>
                        </div>
                    </div>
                    <div class="col-md-3 col-sm-4 col-6">
                        <div class="card h-100 shadow-sm">
                            <img src="data/ct_scan/images/000007.jpeg" class="card-img-top" alt="CT Scan 8" style="height: 200px; object-fit: contain; background: #000;" onerror="this.style.display='none'">
                            <div class="card-body p-2 text-center">
                                <small class="text-muted">000007.jpeg</small>
                            </div>
                        </div>
                    </div>
                    <div class="col-md-3 col-sm-4 col-6">
                        <div class="card h-100 shadow-sm">
                            <img src="data/ct_scan/images/000008.jpeg" class="card-img-top" alt="CT Scan 9" style="height: 200px; object-fit: contain; background: #000;" onerror="this.style.display='none'">
                            <div class="card-body p-2 text-center">
                                <small class="text-muted">000008.jpeg</small>
                            </div>
                        </div>
                    </div>
                    <div class="col-md-3 col-sm-4 col-6">
                        <div class="card h-100 shadow-sm">
                            <img src="data/ct_scan/images/000009.jpeg" class="card-img-top" alt="CT Scan 10" style="height: 200px; object-fit: contain; background: #000;" onerror="this.style.display='none'">
                            <div class="card-body p-2 text-center">
                                <small class="text-muted">000009.jpeg</small>
                            </div>
                        </div>
                    </div>
                </div>
            </div>
        </div>

        <!-- MRI Images Gallery -->
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                <h4 class="mb-0"><i class="fas fa-brain"></i> MRI Images (10 images)</h4>
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                        <div class="card h-100 shadow-sm">
                            <img src="data/mri/images/1 no.jpeg" class="card-img-top" alt="MRI 1" style="height: 200px; object-fit: contain; background: #000;" onerror="this.style.display='none'">
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                                <small class="text-muted">1 no.jpeg</small>
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                            <img src="data/mri/images/10 no.jpg" class="card-img-top" alt="MRI 2" style="height: 200px; object-fit: contain; background: #000;" onerror="this.style.display='none'">
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                                <small class="text-muted">10 no.jpg</small>
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                        <div class="card h-100 shadow-sm">
                            <img src="data/mri/images/11 no.jpg" class="card-img-top" alt="MRI 3" style="height: 200px; object-fit: contain; background: #000;" onerror="this.style.display='none'">
                            <div class="card-body p-2 text-center">
                                <small class="text-muted">11 no.jpg</small>
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                        <div class="card h-100 shadow-sm">
                            <img src="data/mri/images/12 no.jpg" class="card-img-top" alt="MRI 4" style="height: 200px; object-fit: contain; background: #000;" onerror="this.style.display='none'">
                            <div class="card-body p-2 text-center">
                                <small class="text-muted">12 no.jpg</small>
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                        <div class="card h-100 shadow-sm">
                            <img src="data/mri/images/13 no.jpg" class="card-img-top" alt="MRI 5" style="height: 200px; object-fit: contain; background: #000;" onerror="this.style.display='none'">
                            <div class="card-body p-2 text-center">
                                <small class="text-muted">13 no.jpg</small>
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                    <div class="col-md-3 col-sm-4 col-6">
                        <div class="card h-100 shadow-sm">
                            <img src="data/mri/images/14 no.jpg" class="card-img-top" alt="MRI 6" style="height: 200px; object-fit: contain; background: #000;" onerror="this.style.display='none'">
                            <div class="card-body p-2 text-center">
                                <small class="text-muted">14 no.jpg</small>
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                        </div>
                    </div>
                    <div class="col-md-3 col-sm-4 col-6">
                        <div class="card h-100 shadow-sm">
                            <img src="data/mri/images/15 no.jpg" class="card-img-top" alt="MRI 7" style="height: 200px; object-fit: contain; background: #000;" onerror="this.style.display='none'">
                            <div class="card-body p-2 text-center">
                                <small class="text-muted">15 no.jpg</small>
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                        </div>
                    </div>
                    <div class="col-md-3 col-sm-4 col-6">
                        <div class="card h-100 shadow-sm">
                            <img src="data/mri/images/17 no.jpg" class="card-img-top" alt="MRI 8" style="height: 200px; object-fit: contain; background: #000;" onerror="this.style.display='none'">
                            <div class="card-body p-2 text-center">
                                <small class="text-muted">17 no.jpg</small>
                            </div>
                        </div>
                    </div>
                    <div class="col-md-3 col-sm-4 col-6">
                        <div class="card h-100 shadow-sm">
                            <img src="data/mri/images/18 no.jpg" class="card-img-top" alt="MRI 9" style="height: 200px; object-fit: contain; background: #000;" onerror="this.style.display='none'">
                            <div class="card-body p-2 text-center">
                                <small class="text-muted">18 no.jpg</small>
                            </div>
                        </div>
                    </div>
                    <div class="col-md-3 col-sm-4 col-6">
                        <div class="card h-100 shadow-sm">
                            <img src="data/mri/images/19 no.jpg" class="card-img-top" alt="MRI 10" style="height: 200px; object-fit: contain; background: #000;" onerror="this.style.display='none'">
                            <div class="card-body p-2 text-center">
                                <small class="text-muted">19 no.jpg</small>
                            </div>
                        </div>
                    </div>
                </div>
            </div>
        </div>
    </section>

    <!-- Technologies Section -->
    <section id="technologies" class="container mb-5">
        <div class="card">
            <div class="card-body p-5">
                <h2 class="card-title mb-4 text-center">
                    <i class="fas fa-tools text-info"></i> Technologies Used
                </h2>
                <div class="text-center">
                    <span class="tech-badge">DICOM</span>
                    <span class="tech-badge">PNG</span>
                    <span class="tech-badge">JPG</span>
                    <span class="tech-badge">NumPy</span>
                    <span class="tech-badge">PIL</span>
                    <span class="tech-badge">OpenCV</span>
                </div>
                <div class="mt-4">
                    <h5>Technology Stack:</h5>
                    <ul class="list-group list-group-flush">
                        <li class="list-group-item"><strong>DICOM:</strong> Medical imaging standard format</li>
                        <li class="list-group-item"><strong>PNG/JPG:</strong> Standard image formats for processing</li>
                        <li class="list-group-item"><strong>NumPy:</strong> Numerical computing and array operations</li>
                        <li class="list-group-item"><strong>PIL (Pillow):</strong> Image processing and manipulation</li>
                        <li class="list-group-item"><strong>OpenCV:</strong> Computer vision and image analysis</li>
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                <h2 class="card-title mb-4">
                    <i class="fas fa-download"></i> Download Dataset
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                <p class="card-text lead mb-4">
                    Get the complete Medical Imaging Dataset with all images, labels, and documentation.
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                <div class="mb-4">
                    <a href="./medical-imaging.zip" class="btn btn-light btn-lg" download>
                        <i class="fas fa-file-archive"></i> Download Dataset (ZIP) - 2.11 MB
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                <div class="alert alert-light mt-3 text-dark">
                    <i class="fas fa-info-circle"></i> <strong>ZIP File Location:</strong> 
                    <code class="text-primary">medical-imaging.zip</code> (root directory)<br>
                    <small>Contains: 30 images (10 X-ray, 10 CT scan, 10 MRI) + labels + all scripts + documentation</small>
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