WEN HUNG TZU

(Fonte: Lattes)
Índice h a partir de 2011
9
Projetos de Pesquisa
Unidades Organizacionais
Instituto Central, Hospital das Clínicas, Faculdade de Medicina - Médico
LIM/62 - Laboratório de Fisiopatologia Cirúrgica, Hospital das Clínicas, Faculdade de Medicina

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  • article 23 Citação(ões) na Scopus
    Texture analysis of high resolution MRI allows discrimination between febrile and afebrile initial precipitating injury in mesial temporal sclerosis
    (2012) ALEGRO, Maryana de Carvalho; SILVA, Alexandre Valotta; BANDO, Silvia Yumi; LOPES, Roseli de Deus; CASTRO, Luiz Henrique Martins de; HUNGTSU, Wen; MOREIRA-FILHO, Carlos Alberto; AMARO JR., Edson
    A computational pipeline combining texture analysis and pattern classification algorithms was developed for investigating associations between high-resolution MRI features and histological data. This methodology was tested in the study of dentate gyrus images of sclerotic hippocampi resected from refractory epilepsy patients. Images were acquired using a simple surface coil in a 3.0T MRI scanner. All specimens were subsequently submitted to histological semiquantitative evaluation. The computational pipeline was applied for classifying pixels according to: a) dentate gyrus histological parameters and b) patients' febrile or afebrile initial precipitating insult history. The pipeline results for febrile and afebrile patients achieved 70% classification accuracy, with 78% sensitivity and 80% specificity [area under the reader observer characteristics (ROC) curve: 0.89]. The analysis of the histological data alone was not sufficient to achieve significant power to separate febrile and afebrile groups. Interesting enough, the results from our approach did not show significant correlation with histological parameters (which per se were not enough to classify patient groups). These results showed the potential of adding computational texture analysis together with classification methods for detecting subtle MRI signal differences, a method sufficient to provide good clinical classification. A wide range of applications of this pipeline can also be used in other areas of medical imaging. Magn Reson Med, 2012. (c) 2012 Wiley Periodicals, Inc.