Computer-Aided Prostate Cancer Detection Using Ultrasound RF Time Series: In Vivo Feasibility Study.
IEEE Trans Med Imaging
; 34(11): 2248-57, 2015 Nov.
Article
em En
| MEDLINE
| ID: mdl-25935029
ABSTRACT
UNLABELLED This paper presents the results of a computer-aided intervention solution to demonstrate the application of RF time series for characterization of prostate cancer, in vivo. METHODS:
We pre-process RF time series features extracted from 14 patients using hierarchical clustering to remove possible outliers. Then, we demonstrate that the mean central frequency and wavelet features extracted from a group of patients can be used to build a nonlinear classifier which can be applied successfully to differentiate between cancerous and normal tissue regions of an unseen patient.RESULTS:
In a cross-validation strategy, we show an average area under receiver operating characteristic curve (AUC) of 0.93 and classification accuracy of 80%. To validate our results, we present a detailed ultrasound to histology registration framework.CONCLUSION:
Ultrasound RF time series results in differentiation of cancerous and normal tissue with high AUC.
Texto completo:
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Base de dados:
MEDLINE
Assunto principal:
Próstata
/
Neoplasias da Próstata
/
Interpretação de Imagem Assistida por Computador
Tipo de estudo:
Diagnostic_studies
/
Prognostic_studies
Limite:
Humans
/
Male
Idioma:
En
Ano de publicação:
2015
Tipo de documento:
Article