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dnwjddl authored Jun 4, 2024
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Expand Up @@ -216,144 +216,6 @@ <h4 class="title is-4 has-text-centered">Eigen Aggregation Module</h4>
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</section>




<section class="section">
<div class="container is-max-desktop">
<div class="columns is-centered">
<div class="column is-four-fifths">
<h3 class="title is-3 has-text-centered">Visualization of Primary Elements</h3>

<br>
<h4 class="title is-4 has-text-centered">Eigenvectors</h4>
<section class="hero is-light is-small">
<div class="slideContent">
<div style="width: 100%;">
<div id="results-carousel" class="carousel results-carousel">
<div class="">
<div class="content has-text-centered">
<img src="./static/images/vector1.png" alt="Eigenvectors figure">
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<img src="./static/images/vector2.png" alt="Eigenvectors figure">
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<img src="./static/images/vector3.png" alt="Eigenvectors figure">
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<img src="./static/images/vector4.png" alt="Eigenvectors figure">
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<img src="./static/images/vector5.png" alt="Eigenvectors figure">
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<img src="./static/images/vector6.png" alt="Eigenvectors figure">
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<img src="./static/images/vector8.png" alt="Eigenvectors figure">
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<img src="./static/images/vector9.png" alt="Eigenvectors figure">
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</div>
</div>
</div>
</section>
<div class="content has-text-justified">
<p>
Visualizing eigenvectors derived from \( \mathrm{S} \) in the Eigen Aggregation Module.
These eigenvectors not only distinguish different objects but also identify semantically related areas,
highlighting how EiCue captures object semantics and boundaries effectively.
</p>
</div>

<br>
<h4 class="title is-4 has-text-centered">EiCue</h4>
<section class="hero is-light is-small">
<div class="slideContent">
<div style="width: 100%;">
<div id="results-carousel" class="carousel results-carousel">
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<img src="./static/images/eicue1.png" alt="EiCue figure">
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<img src="./static/images/eicue2.png" alt="EiCue figure">
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<img src="./static/images/eicue3.png" alt="EiCue figure">
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<img src="./static/images/eicue4.png" alt="EiCue figure">
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<img src="./static/images/eicue5.png" alt="EiCue figure">
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<img src="./static/images/eicue6.png" alt="EiCue figure">
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<img src="./static/images/eicue7.png" alt="EiCue figure">
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<img src="./static/images/eicue8.png" alt="EiCue figure">
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<img src="./static/images/eicue9.png" alt="EiCue figure">
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</section>
<div class="content has-text-justified">
<p>
Comparison between K-means and EiCue.
The bottom row presents EiCue, highlighting its superior ability to capture subtle structural
intricacies and understand deeper semantic relationships, which is not as effectively achieved
by K-means.
</p>
</div>

</div>
</div>
</div>
</section>

<section class="section">
<div class="container is-max-desktop">

Expand All @@ -362,19 +224,15 @@ <h4 class="title is-4 has-text-centered">EiCue</h4>
<h3 class="title is-3 has-text-centered">Qualitative Results</h3>

<br>
<h4 class="title is-4 has-text-centered">Qualitative ablation on each reward model</h4>
<h4 class="title is-4 has-text-centered">Additional Qualitative results</h4>
<section class="hero is-light is-small">
<div class="content has-text-centered">
<img src="./static/images/result1.png" alt="Qualitative ablation">
</div>
</section>
<div class="content has-text-centered">
<p>
<ul>
<li>(a): CXRL shows significantly better alignment of the <i>clavicle</i> and <i>costophrenic angle</i> compared to the anchor regarding posture alignment.</li>
<li>(b): CXRL demonstrates improved predictive diagnostic accuracy, closely matching the GT and enhancing clinical decision-making</li>
<li>(c): The multimodal consistency reward ensures that CXRs and reports correspond well, as observed by arrows and text in matching colors.</li>
</ul>
Comparison between previous state-of-the-art report-to-CXR generation models [19,3] and ours. The blue and green texts match their corresponding colored arrows.
</p>
</div>

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