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Mehdi Astaraki

As seen in: Nature, Frontiers
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Articles

Computer Science > Machine Learning

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By Mehdi Astaraki, Fernando Casals Seoane, Farhad Abtahi
| arxiv.org
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
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A comprehensive evaluation of MRI-based radiogenomics and prognosis prediction in glioma

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By Mehdi Astaraki, Marta Lazzeroni, Iuliana Toma-daşu
| Frontiers
1 Introduction Gliomas are the most common malignant primary brain tumors in adults. Based on the 2021 World Health Organization (WHO) classification, three main types of gliomas are astrocytoma, oligodendroglioma, and glioblastoma (GBM) (1).
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Results from the autoPET challenge on fully automated lesion segmentation in oncologic PET/CT imaging - Nature Machine Intelligence

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By Christian la Fougère, Lei Bi, Jia Zhang, Zdravko Marinov, Jan Egger, Jens Kleesiek, Simone Bendazzoli, Michael Ingrisch, Yige Peng, Mehdi Astaraki
| Nature Verified
Abstract Automated detection of tumour lesions on positron emission tomography–computed tomography (PET/CT) image data is a clinically relevant but highly challenging task. Progress in this field has been hampered in the past owing to the lack of publicly available annotated data and limited availability of platforms for inter-institutional collaboration.
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