Machine learning for evolutive lymphoma and residual masses recognition in whole body diffusion weighted magnetic resonance images

•The complementarity of the functional and anatomical criteria of DW-MR images through a fusion step based on DWT.•Automatic segmentation of the lesions, their localization, their enumeration and the generation of the parametric ADC map.•The analysis of the heterogeneous lesions to select the solid...

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Bibliographic Details
Published in:	Computer methods and programs in biomedicine Vol. 209; p. 106320
Main Authors:	Ferjaoui, Radhia, Cherni, Mohamed Ali, Boujnah, Sana, Kraiem, Nour El Houda, Kraiem, Tarek
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 01-09-2021
Subjects:	Back-propagation artificial neural network Convolutional neural network (CNN) Deep learning Evolutive lymphoma K-nearest neighbours Machine learning Random forest Relevance vectors machine (RVM) Residual masses Support vector machine Deep learning K-nearest neighbours Residual masses Evolutive lymphoma Back-propagation artificial neural network Machine learning Random forest Support vector machine Relevance vectors machine (RVM) Convolutional neural network (CNN)
Online Access:	Get full text
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