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<button class="button is-small is-link">Go</button> </div> </div> </form> </div> </div> <ol class="breathe-horizontal" start="1"> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2401.14206">arXiv:2401.14206</a> <span> [<a href="https://arxiv.org/pdf/2401.14206">pdf</a>, <a href="https://arxiv.org/format/2401.14206">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Image and Video Processing">eess.IV</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Artificial Intelligence">cs.AI</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1109/BigData55660.2022.10020613">10.1109/BigData55660.2022.10020613 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> Exploiting Liver CT scans in Colorectal Carcinoma genomics mutation classification </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Perlo%2C+D">Daniele Perlo</a>, <a href="/search/cs?searchtype=author&query=Berton%2C+L">Luca Berton</a>, <a href="/search/cs?searchtype=author&query=Delpiano%2C+A">Alessia Delpiano</a>, <a href="/search/cs?searchtype=author&query=Menchini%2C+F">Francesca Menchini</a>, <a href="/search/cs?searchtype=author&query=Tibaldi%2C+S">Stefano Tibaldi</a>, <a href="/search/cs?searchtype=author&query=Grosso%2C+M">Marco Grosso</a>, <a href="/search/cs?searchtype=author&query=Fonio%2C+P">Paolo Fonio</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2401.14206v1-abstract-short" style="display: inline;"> The liver is the most involved organ by distant metastasis in colon-rectal cancer (CRC) patients and it comes necessary to be aware of the mutational status of the lesions to correctly design the best individual treatment. So far, efforts have been made in order to develop non-invasive and real-time methods that permit the analysis of the whole tumor, using new artificial intelligence tools to ana… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2401.14206v1-abstract-full').style.display = 'inline'; document.getElementById('2401.14206v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2401.14206v1-abstract-full" style="display: none;"> The liver is the most involved organ by distant metastasis in colon-rectal cancer (CRC) patients and it comes necessary to be aware of the mutational status of the lesions to correctly design the best individual treatment. So far, efforts have been made in order to develop non-invasive and real-time methods that permit the analysis of the whole tumor, using new artificial intelligence tools to analyze the tumor's image obtained by Computed Tomography (CT) scan. In order to address the current medical workflow, that is biopsy analysis-based, we propose the first DeepLearning-based exploration, to our knowledge, of such classification approach from the patient medical imaging. We propose i) a solid pipeline for managing undersized datasets of available CT scans and ii) a baseline study for genomics mutation diagnosis support for preemptive patient follow-up. Our method is able to identify CRC RAS mutation family from CT images with 0.73 F1 score. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2401.14206v1-abstract-full').style.display = 'none'; document.getElementById('2401.14206v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 25 January, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> January 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">ACM Class:</span> J.3; I.1.2 </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Journal ref:</span> 2022 IEEE International Conference on Big Data (Big Data) </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2208.00641">arXiv:2208.00641</a> <span> [<a href="https://arxiv.org/pdf/2208.00641">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Image and Video Processing">eess.IV</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Computer Vision and Pattern Recognition">cs.CV</span> </div> </div> <p class="title is-5 mathjax"> Lung nodules segmentation from CT with DeepHealth toolkit </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Chaudhry%2C+H+A+H">Hafiza Ayesha Hoor Chaudhry</a>, <a href="/search/cs?searchtype=author&query=Renzulli%2C+R">Riccardo Renzulli</a>, <a href="/search/cs?searchtype=author&query=Perlo%2C+D">Daniele Perlo</a>, <a href="/search/cs?searchtype=author&query=Santinelli%2C+F">Francesca Santinelli</a>, <a href="/search/cs?searchtype=author&query=Tibaldi%2C+S">Stefano Tibaldi</a>, <a href="/search/cs?searchtype=author&query=Cristiano%2C+C">Carmen Cristiano</a>, <a href="/search/cs?searchtype=author&query=Grosso%2C+M">Marco Grosso</a>, <a href="/search/cs?searchtype=author&query=Fiandrotti%2C+A">Attilio Fiandrotti</a>, <a href="/search/cs?searchtype=author&query=Lucenteforte%2C+M">Maurizio Lucenteforte</a>, <a href="/search/cs?searchtype=author&query=Cavagnino%2C+D">Davide Cavagnino</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2208.00641v1-abstract-short" style="display: inline;"> The accurate and consistent border segmentation plays an important role in the tumor volume estimation and its treatment in the field of Medical Image Segmentation. Globally, Lung cancer is one of the leading causes of death and the early detection of lung nodules is essential for the early cancer diagnosis and survival rate of patients. The goal of this study was to demonstrate the feasibility of… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2208.00641v1-abstract-full').style.display = 'inline'; document.getElementById('2208.00641v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2208.00641v1-abstract-full" style="display: none;"> The accurate and consistent border segmentation plays an important role in the tumor volume estimation and its treatment in the field of Medical Image Segmentation. Globally, Lung cancer is one of the leading causes of death and the early detection of lung nodules is essential for the early cancer diagnosis and survival rate of patients. The goal of this study was to demonstrate the feasibility of Deephealth toolkit including PyECVL and PyEDDL libraries to precisely segment lung nodules. Experiments for lung nodules segmentation has been carried out on UniToChest using PyECVL and PyEDDL, for data pre-processing as well as neural network training. The results depict accurate segmentation of lung nodules across a wide diameter range and better accuracy over a traditional detection approach. The datasets and the code used in this paper are publicly available as a baseline reference. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2208.00641v1-abstract-full').style.display = 'none'; document.getElementById('2208.00641v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 1 August, 2022; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> August 2022. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">Workshop ICIAP 2021 - Deep-Learning and High Performance Computing to Boost Biomedical Applications</span> </p> </li> </ol> <div class="is-hidden-tablet">  <span class="help" style="display: inline-block;"><a href="https://github.com/arXiv/arxiv-search/releases">Search v0.5.6 released 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