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<title>Bilateral View Hypercomplex Breast Classification</title>
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<h1 class="title">Bilateral View Hypercomplex Breast Classification</h1>
<h2 class="subtitle">Kalbe Digital Lab</h2>
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<h3 class="overview-heading"><span class="vl">Overview</span></h3>
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Breast cancer classification using 2-views (bilateral) that compose a mammography exam, owing to the correlations contained in mammography views, which present crucial information for identifying tumors.
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Reference: <a href="https://arxiv.org/abs/2204.05798" target="_blank">https://arxiv.org/abs/2204.05798</a>
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<h3 class="overview-heading"><span class="vl">Dataset</span></h3>
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<p class="overview-content">The model is trained using CBIS <a href="https://pubmed.ncbi.nlm.nih.gov/22078258/" target="_blank">INBReast Dataset</a></p>
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<li>Target: Lesions (masses, calcifications, asymmetries, and distortions)</li>
<li>Task: Classification</li>
<li>Modality: Grayscale</li>
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<h3 class="overview-heading"><span class="vl">Model Architecture</span></h3>
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<p class="overview-content">Parameterized Hypercomplex ResNets-18 Variants (PHYResNet).</p>
<img class="content-image" src="file/figures/phresnet18.png" alt="model-architecture" />
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<h3 class="overview-heading"><span class="vl">Demo</span></h3>
<p class="overview-content">Please select the example below or upload 2 pairs of mammography exam result.</p>
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