Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/9734
Título: | Computer-aided diagnosis in Brain Computer Tomography screening |
Autor(es): | Peixoto, Hugo Alves, Victor |
Palavras-chave: | Medical imaging Computer aided detection Brain Computer Tomography Artificial intelligence Machine learning Brain Computed Tomography |
Data: | 9-Jul-2009 |
Editora: | Springer |
Revista: | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
Citação: | PERNER, Petra, ed. lit. – “Advances in Data Mining : applications and theoretical aspects : proceedings of the Industrial Conference on Data Mining, 9, Leipzig, Germany, 2009.” Heidelberg : Springer Berlin, 2009. ISBN 978-3-642-03066-6. p. 62-72. |
Resumo(s): | Currently, interpretation of medical images is almost exclusively made by specialized physicians. Although, the next decades will most certainly be of change and computer-aided diagnosis systems will play an important role in the reading process. Assisted interpretation of medical images has become one of the major research subjects in medical imaging and diagnostic radiology. From a methodological point of view, the main attraction for the resolution of this kind of problem arises from the combination of the image reading made by the radiologists, with the results obtained from using Artificial Intelligence (AI) based applications that will contribute to the reduction and eventually the elimination of perception errors. This article describes how machine learning algorithms can help distinguish normal readings in Brain Computer Tomography (CT) from all its variations. The goal is to have a system that is able to identify abnormal appearing structures making the reading by the radiologist unnecessary for a large proportion of the brain CT scans. |
Tipo: | Artigo em ata de conferência |
URI: | https://hdl.handle.net/1822/9734 |
ISBN: | 978-3-642-03066-6 |
DOI: | 10.1007/978-3-642-03067-3_7 |
ISSN: | 0302-9743 |
Arbitragem científica: | yes |
Acesso: | Acesso aberto |
Aparece nas coleções: | DI/CCTC - Artigos (papers) |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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89.pdf | documento principal | 462,94 kB | Adobe PDF | Ver/Abrir |