Cooperative strategy for a dynamic ensemble of classification models in clinical applications: the case of MRI vertebral compression fractures.
Int J Comput Assist Radiol Surg
; 12(11): 1971-1983, 2017 Nov.
Article
em En
| MEDLINE
| ID: mdl-28616809
ABSTRACT
PURPOSE:
In clinical practice, the constructive consultation among experts improves the reliability of the diagnosis and leads to the definition of the treatment plan for the patient. Aggregation of the different opinions collected by many experts can be performed at the level of patient information, abnormality delineation, or final assessment.METHODS:
In this study, we present a novel cooperative strategy that exploits the dynamic contribution of the classification models composing the ensemble to make the final class assignment. As a proof of concept, we applied the proposed approach to the assessment of malignant infiltration in 103 vertebral compression fractures in magnetic resonance images.RESULTS:
The results obtained with repeated random subsampling and receiver operating characteristic analysis indicate that the cooperative system statistically improved ([Formula see text]) the classification accuracy of individual modules as well as of that based on the manual segmentation of the fractures provided by the experts.CONCLUSIONS:
The performances have been also compared with those obtained with those of standard ensemble classification algorithms showing superior results.Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Processamento de Imagem Assistida por Computador
/
Fraturas da Coluna Vertebral
/
Fraturas por Compressão
Tipo de estudo:
Guideline
/
Prognostic_studies
Limite:
Aged
/
Female
/
Humans
/
Male
/
Middle aged
Idioma:
En
Revista:
Int J Comput Assist Radiol Surg
Assunto da revista:
RADIOLOGIA
Ano de publicação:
2017
Tipo de documento:
Article
País de afiliação:
Itália