Výsledky vyhledávání - "Vladimir Groza"

3D-Morphomics, Morphological Features on CT scans for lung nodule malignancy diagnosis

Autor: Elias Munoz, Antoine Iannessi, Yan Liu, Benoit Huet, Pierre Baudot, Van-Khoa Le, Charles Voyton, Benjamin Renoust, Danny Francis, Vladimir Groza, Jean-Christophe Brisset, Ezequiel Geremia

Publikováno v: Web of Science

Pathologies systematically induce morphological changes, thus providing a major but yet insufficiently quantified source of observables for diagnosis. The study develops a predictive model of the pathological states based on morphological features (3

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::77fa538f72916287973ab3c16212ca1c
http://arxiv.org/abs/2207.13830

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3D Visualization of Brain Tumors via Artificial Intelligence

Autor: Nikolay Tolstokulakov, Bair Tuchinov, Sergey Golushko, Mikhail Amelin, Evgeniy N. Pavlovskiy, Vladimir Groza, Andrey Letyagin, E. V. Amelina

Publikováno v: 2021 IEEE Ural-Siberian Conference on Computational Technologies in Cognitive Science, Genomics and Biomedicine (CSGB).

Neuro-oncological MRI imaging is a complex, expensive procedure that is responsible for all further treatment tactics. The following issues must be unambiguously resolved: (1) to detect a volumetric process in the brain (e.g., tumor); (2) to outline

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::14c6c5315a115177d7dbe3d2e7089065
https://doi.org/10.1109/csgb53040.2021.9496040

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CHAOS Challenge - Combined (CT-MR) Healthy Abdominal Organ Segmentation

Publikováno v: Medical Image Analysis
Medical Image Analysis, Elsevier, 2021, 69, ⟨10.1016/j.media.2020.101950⟩

Segmentation of abdominal organs has been a comprehensive, yet unresolved, research field for many years. In the last decade, intensive developments in deep learning (DL) introduced new state-of-the-art segmentation systems. Despite outperforming the

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::062a182f507db13c73a8422353093c1a
https://hdl.handle.net/10278/3736173

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Brain Tumor Segmentation and Associated Uncertainty Evaluation Using Multi-sequences MRI Mixture Data Preprocessing

Autor: Mikhail Amelin, Nikolay Tolstokulakov, Vladimir Groza, E. V. Amelina, Bair Tuchinov, Andrey Letyagin, Evgeniy N. Pavlovskiy, Sergey Golushko

Publikováno v: Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries ISBN: 9783030720865
BrainLes@MICCAI (2)

The brain tumor segmentation is one of the crucial tasks nowadays among other directions and domains where daily clinical workflow requires to put a lot of efforts while studying computer tomography (CT) or structural magnetic resonance imaging (MRI)

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::63905ecaeb7c857fe2433119c2a6aef4
https://doi.org/10.1007/978-3-030-72087-2_13

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A Model-Strengthened Imaging Biomarker for Survival Prediction in EGFR-Mutated Non-small-cell Lung Carcinoma Patients Treated with Tyrosine Kinase Inhibitors

Autor: François Chomy, Vladimir Groza, Olivier Saut, Thierry Colin, Annabelle Collin, Louise Missenard, Jean Palussière

Publikováno v: Bulletin of Mathematical Biology
Bulletin of Mathematical Biology, 2021, 83 (6), ⟨10.1007/s11538-021-00902-7⟩
Bulletin of Mathematical Biology, Springer Verlag, 2021, 83 (6), ⟨10.1007/s11538-021-00902-7⟩

International audience; Non-small-cell lung carcinoma is a frequent type of lung cancer with a bad prognosis. Depending on the stage, genomics, several therapeutical approaches are used. Tyrosine Kinase Inhibitors (TKI) may be successful for a time i

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::56f799369dca47d0503806ef5f2bd9cf
https://pubmed.ncbi.nlm.nih.gov/33966172

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Multi-class Brain Tumor Segmentation via Multi-sequences MRI Mixture Data Preprocessing

Autor: E. V. Amelina, Evgeniy N. Pavlovskiy, Andrey Letyagin, Vladimir Groza, Bair Tuchinov, Nikolay Tolstokulakov, Sergey Golushko, Mikhail Amelin

Publikováno v: 2020 Cognitive Sciences, Genomics and Bioinformatics (CSGB).

In this paper, we extend the previous work on the robust pre-processing technique which allows to consider all available information from MRI scans by composition of T1, T1C and FLAIR sequences in the unique input. Such approach enriches the input da

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::62d978e3ab858424df2f1d8caff7d10f
https://doi.org/10.1109/csgb51356.2020.9214645

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Data Preprocessing Via Compositions Multi-Channel MRI Images to Improve Brain Tumor Segmentation

Autor: Sergey Golushko, Evgeniy N. Pavlovskiy, E. V. Amelina, Nikolay Tolstokulakov, Vladimir Groza, Bair Tuchinov, Mikhail Amelin, Andrey Letyagin

Publikováno v: ISBI Workshops

Magnetic resonance imaging (MRI) stays one of the most essential noninvasive methods for brain diagnostics. It allows obtaining the detailed 3D image of the brain, including various types of soft tissues. In this paper, we compare the influence of th

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::e4dace7b3b12b7e3bf11e26cbd8deefd
https://doi.org/10.1109/isbiworkshops50223.2020.9153416

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