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 <div class="sc-jegwdG lhLRCf"><div class="sc-UEtKG dGqiYy sc-flttKd cguEtd"><div class="sc-fqwslf gsqkEc"><div class="sc-cBQMlg kAHhUk"><h2 class="sc-dcKlJK sc-cVttbi gqEuPW ksnHgj">About Dataset</h2></div></div></div><div class="sc-davvxH eCVTlP"><div class="sc-jCNfQM ikRdXB"><div style="min-height: 80px;"><div class="sc-etVRix jqYJaa sc-gVIFzB gQKGyV"><h1>Abstract</h1>
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   <p>130 CT scans for segmentation of the liver as well as tumor lesions.</p>
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 <h1>About this dataset</h1>
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   <p>Liver cancer is the <strong>fifth</strong> most commonly occurring cancer in men and the <strong>ninth</strong> most commonly occurring cancer in women. There were over <strong>840,000 new cases in 2018</strong>.</p>
   <p>The liver is a common site of primary or secondary tumor development. Due to their heterogeneous and diffusive shape, automatic segmentation of tumor lesions is very challenging.</p>
   <p>In light of that, we encourage the development of automatic segmentation algorithms to segment liver lesions in contrast­-enhanced abdominal CT scans. The data and segmentations are provided by various clinical sites around the world.<br>
   This dataset was extracted from LiTS – Liver Tumor Segmentation Challenge (LiTS17) organised in conjunction with ISBI 2017 and MICCAI 2017.</p>
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 <h1>How to use</h1>
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   <ul>
   <li>Create a segmentation model for segmenting liver and/or liver tumor lesions.</li>
   <li>Your kernel can be featured here!</li>
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   <li><a rel="noreferrer nofollow" aria-label="Dataset article (opens in a new tab)" target="_blank" href="https://arxiv.org/abs/1901.04056">Dataset article</a></li>
   <li><a aria-label="More Datasets (opens in a new tab)" target="_blank" href="https://www.kaggle.com/andrewmvd/datasets">More Datasets</a></li>
   </ul>
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 <h1>Acknowledgements</h1>
 <p>If you use this dataset in your research, please credit the authors.</p>
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   <h3>Splash banner</h3>
   <p>Image by ©yodiyim</p>
   <h3>Splash icon</h3>
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       archivePrefix={arXiv},<br>
       primaryClass={cs.CV}<br>
   }</p>
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