Detection of prostate cancer in multiparametric MRI using random forest with instance weighting

A prostate computer-aided diagnosis (CAD) based on random forest to detect prostate cancer using a combination of spatial, intensity, and texture features extracted from three sequences, T2W, ADC, and B2000 images, is proposed. The random forest training considers instance-level weighting for equal...

ver descrição completa

Na minha lista:
Detalhes bibliográficos
Publicado no:J Med Imaging (Bellingham)
Main Authors: Lay, Nathan, Tsehay, Yohannes, Greer, Matthew D., Turkbey, Baris, Kwak, Jin Tae, Choyke, Peter L., Pinto, Peter, Wood, Bradford J., Summers, Ronald M.
Formato: Artigo
Idioma:Inglês
Publicado em: Society of Photo-Optical Instrumentation Engineers 2017
Assuntos:
Computer-Aided Diagnosis
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC5467765/
https://ncbi.nlm.nih.gov/pubmed/28630883
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1117/1.JMI.4.2.024506
Tags: Adicionar Tag
Sem tags, seja o primeiro a adicionar uma tag!

Registos relacionados