Advances in the use of deep learning for the analysis of magnetic resonance image in neuro-oncology
Machine Learning is entering a phase of maturity, but its medical applications still lag behind in terms of practical use. The field of oncological radiology (and neuro-oncology in particular) is at the forefront of these developments, now boosted by the success of Deep-Learning methods for the anal...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2024 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/402636 |
| Acceso en línea: | https://hdl.handle.net/2117/402636 https://dx.doi.org/10.3390/cancers16020300 |
| Access Level: | acceso abierto |
| Palabra clave: | Machine learning Magnetic resonance imaging Brain --Tumors Neuro-oncology Radiology Deep learning Data analysis pipeline Ultra-low field magnetic resonance imaging Aprenentatge automàtic Imatgeria per ressonància magnètica Cervell -- Tumors Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Aprenentatge automàtic |
| Sumario: | Machine Learning is entering a phase of maturity, but its medical applications still lag behind in terms of practical use. The field of oncological radiology (and neuro-oncology in particular) is at the forefront of these developments, now boosted by the success of Deep-Learning methods for the analysis of medical images. This paper reviews in detail some of the most recent advances in the use of Deep Learning in this field, from the broader topic of the development of Machine-Learning-based analytical pipelines to specific instantiations of the use of Deep Learning in neuro-oncology; the latter including its use in the groundbreaking field of ultra-low field magnetic resonance imaging. |
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