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<datestamp>2017-12-21</datestamp>
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<publisher>HAL CCSD</publisher>
<title lang=en>In silico model to simulate the radiation response at various fractionation from histopathological images of prostate tumors</title>
<creator>Aubert, V.</creator>
<creator>Acosta, O.</creator>
<creator>Rioux-Leclercq, N.</creator>
<creator>Mathieu, R.</creator>
<creator>Commandeur, F.</creator>
<creator>De Crevoisier, R.</creator>
<contributor>Laboratoire Traitement du Signal et de l'Image (LTSI) ; Université de Rennes 1 (UR1) - Institut National de la Santé et de la Recherche Médicale (INSERM)</contributor>
<contributor>Institut de recherche, santé, environnement et travail [Rennes] (Irset) ; Université d'Angers (UA) - Université des Antilles et de la Guyane (UAG) - Université de Rennes 1 (UR1) - École des Hautes Études en Santé Publique [EHESP] (EHESP) - Institut National de la Santé et de la Recherche Médicale (INSERM) - Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique )</contributor>
<description>International audience</description>
<source>14th IEEE International Symposium on Biomedical Imaging, ISBI 2017</source>
<coverage>Melbourne, Australia</coverage>
<identifier>hal-01618934</identifier>
<identifier>https://hal-univ-rennes1.archives-ouvertes.fr/hal-01618934</identifier>
<source>https://hal-univ-rennes1.archives-ouvertes.fr/hal-01618934</source>
<source>14th IEEE International Symposium on Biomedical Imaging, ISBI 2017, Apr 2017, Melbourne, Australia. 〈10.1109/ISBI.2017.7950643〉</source>
<identifier>DOI : 10.1109/ISBI.2017.7950643</identifier>
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<language>en</language>
<subject lang=en>Tumor mathematical model</subject>
<subject lang=en>Radiosensitivity</subject>
<subject lang=en>Gleason score</subject>
<subject lang=en>Hypoxia</subject>
<subject lang=en>Prostate radiotherapy</subject>
<subject>[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing</subject>
<subject>[SDV.IB] Life Sciences [q-bio]/Bioengineering</subject>
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<type>Conference papers</type>
<description lang=en>Objectives: Using in silico simulations from histopathological cancer prostate specimen, the objectives were to identify the total dose corresponding to various fractionations necessary to destroy the tumor cells (50% to 99.9%) and to assess the impact of the Gleason score on those doses. © 2017 IEEE.</description>
<date>2017-04-18</date>
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