tasks.html

<!DOCTYPE html>
<html lang="en">

<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>SegRap2025 Challenge</title>
    <link rel="stylesheet" href="shared.css">
    <style>
        .task-section {
            margin-bottom: 60px;
        }

        .task-content {
            background: white;
            border-radius: 12px;
            padding: 20px;
            margin-bottom: 20px;
        }

        .task-content li {
            color: #064b43;
            margin-bottom: 0.3em;
            line-height: 1.5;
        }

        .task-overview {
            margin-bottom: 40px;
            line-height: 1.6;
        }

        .evaluation-metrics {
            margin-top: 20px;
        }

        .metric-item {
            margin-bottom: 20px;
        }

        .metric-name {
            font-weight: 500;
            color: var(--text-primary);
            font-size: 20px;
            margin-bottom: 8px;
            margin-top: 0px;
        }

        .metric-description {
            color: var(--text-secondary);
            font-size: 0.95em;
            line-height: 1.5;
            margin-left: 20px;
        }

        .news-list {
            list-style: none;
            padding: 0;
            margin: 0;
        }

        .news-list li {
            position: relative;
            padding-left: 25px;
            margin-top: 20px;
            margin-bottom: 20px;
            line-height: 1.5;
            color: #000000;
            font-weight: 500;
        }

        .news-list li::before {
            content: "•";
            position: absolute;
            left: 10px;
            color: #00bfa5;
        }

        .news-list a {
            color: #00bfa5;
            text-decoration: none;
            font-weight: 500;
            transition: color 0.2s ease;
        }

        .news-list a:hover {
            color: #00897b;
        }
    </style>
</head>

<body>
    <div class="site-header">
        <div class="header-image" style="text-align: center;">
            <img src="logo_web.png" alt="SegRap Logo" style="width: 50%; height: auto;">
        </div>
        <div class="header-container">
            <div class="content-section">
                <nav class="nav-links">
                    <a href="index.html">Home</a>
                    <a href="tasks.html" class="active">Tasks</a>
                    <a href="dataset.html">Dataset</a>
                    <a href="evaluate.html">Evaluate</a>
                    <a href="prizes.html">Prizes</a>
                    <a href="leaderboard.html">Leaderboard</a>
                    <a href="organizing.html">Organizing</a>
                    <a href="contact.html">Contact</a>
                </nav>
            </div>
        </div>
    </div>

    <main class="main-content">
        <!-- Overview Section -->
        <section id="overview" class="task-section">
            <h1 class="section-title">Challenge Tasks</h1>
            <div class="task-content">
                <p>The SegRap2025 Challenge focuses on accurate Gross Tumor Volume (GTV) and Lymph Node Clinical Target
                    Volume (LN CTV) segmentation in Computed Tomography (CT) images, aiming to support clinical manual
                    delineation, enhance research on radiation dose calculation, and improve efficiency of
                    radiotherapy treatment planning.
                </p>
            </div>

            <!-- Task01 -->
            <!-- <h2 class="section-title">Task01: GTV Segmentation</h2> -->
            <!-- <div class="task-content"> -->
            <div class="metric-name">Task01: GTV Segmentation</div>
            <p class="metric-description">
                Task01 (GTV segmentation) emphasizes <strong>model generalizability</strong>. <br>
                <br>

                Models are supposed to accurately delineate Gross Target Volume of nasopharynx (<strong>GTVnx</strong>,
                also named GTVp)
                and Gross Target Volume of lymph node (<strong>GTVnd</strong>) within paired non-contrast computed
                tomography (ncCT) and
                contrast computed tomography (ceCT) images. <br>

                <br>
                The testing data are from two cohorts: one internal cohort and one external cohort.
            </p>
            <br>

            <div class="metric-name">Task02: LN CTV Segmentation</div>
            <p class="metric-description">
                Task02 (LN CTV segmentation) evaluates model's ability to handle <strong>missing modality</strong>
                problem. <br>
                <br>

                Models are supposed to accurately delineate 6 LN CTVs: L_Ib, L_II+III+Va, L_IV+Vb+Vc, R_Ib,
                R_II+III+Va, and R_IV+Vb+Vc within paired ncCT and ceCT images or ncCT/ceCT images. <br>

                <br>
                The validation and
                testing data are come from one external cohort, comprising cases with: <em>both ncCT and ceCT</em>
                scans; <em>only ncCT</em> scans; and <em>only ceCT</em> scans.
            </p>
            <br>
        </section>


    </main>
</body>

</html>