首页 | 本学科首页   官方微博 | 高级检索  
     


On the relevance of automatically selected single-voxel MRS and multimodal MRI and MRSI features for brain tumour differentiation
Authors:Postma Geert J  Luts Jan  Idema Albert J  Julià-Sapé Margarida  Moreno-Torres Angel  Gajewicz Witek  Suykens Johan A K  Heerschap Arend  Van Huffel Sabine  Buydens Lutgarde M C
Affiliation:aInstitute for Molecules and Materials, Radboud University Nijmegen, Heijendaalseweg 135, 6525 AJ Nijmegen, The Netherlands;bDepartment of Electrical Engineering (ESAT), Research Division SCD, Katholieke Universiteit Leuven, Kasteelpark Arenberg 10, B-3001 Leuven, Belgium;cDepartment of Neurosurgery, Radboud University Nijmegen, University Medical Center, Geert Grooteplein Z18, PO Box 9101, 6500 HB Nijmegen, The Netherlands;dCentro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Spain;eUniversitat Autònoma de Barcelona, Departament de Bioquímica i Biologia Molecular, Facultat de Biociències, Edifici C, Universitat Autònoma de Barcelona (UAB), 08193 Cerdanyola del Vallès, Spain;fInstitut de Biotecnologia i Biomedicina (IBB), Universitat Autònoma de Barcelona (UAB), Cerdanyola del Vallès, Spain;gResearch Department, Centre Diagnòstic Pedralbes, Esplugues de Llobregat, Barcelona, Spain;hCIBER-BBN, Esplugues de Llobregat, Spain;iDepartment of Radiology, Medical University Lodz, 90-156Lodz, Kopcinskiego 22, Poland;jDepartment of Radiology, Radboud University Nijmegen, University Medical Center, Geert Grooteplein Z18, PO Box 9101, 6500 HB Nijmegen, The Netherlands
Abstract:In order to evaluate the relevance of magnetic resonance (MR) features selected by automatic feature selection techniques to build classifiers for differential diagnosis and tissue segmentation two data sets containing MR spectroscopy data from patients with brain tumours were investigated. The automatically selected features were evaluated using literature and clinical experience. It was observed that a significant part of the automatically selected features correspond to what is known from the literature and clinical experience. We conclude that automatic feature selection is a useful tool to obtain relevant and possibly interesting features, but evaluation of the obtained features remains necessary.
Keywords:Brain tumour   Differential diagnosis   Automatic feature selection   MRS   MRSI   MRI
本文献已被 ScienceDirect PubMed 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号