Using LCModel & Whole Tissue Representations for the Classification of Single Voxel 1H Spectra of Paediatric Brain Tumours

Keywords

accepting account accounting accuracies accuracy achieve achieved acquisition additional additionally adjacent adult applied apply association basis best better bounds brain calculation cancer cerebellum children choline classes classification classifications classifier clinical combination common component components comprised confident confirms consistently constant constraints contributions correct cram criteria dataset defined dept determined deviation diagnosis direct discriminant discriminating distribution dotted easy england estimations evaluate every examples excluded excluding fast fits fitted flexibility funded gives giving grant health heterogeneity highest important improve improvements incl included individual influence instead investigate involved iteration iterations kingdom linear martin metabolite methodology misclassified normalized novel ones overall part partial pattern peak performance planning poor posterior potential preparation previously print promises proof proportion proportions published question random recently recognition relatively reliable represent representations resection sample scanner sciences setting short since soft solid spectra spectrum table taken term throughout tissue tool training treated treatment true type types uncertainty unity variability volume whereas whole widespread