title: Enhancing the discrimination accuracy between metastases, gliomas and meningiomas on brain MRI by volumetric textural features and ensemble pattern recognition methods.
abstract: Three-dimensional (3D) texture analysis of volumetric brain magnetic resonance (MR) images has been identified as an important indicator for discriminating among different brain pathologies. The purpose of this study was to evaluate the efficiency of 3D textural features using a pattern recognition system in the task of discriminating benign, malignant and metastatic brain tissues on T1 postcontrast MR imaging (MRI) series. The dataset consisted of 67 brain MRI series obtained from patients with verified and untreated intracranial tumors. The pattern recognition system was designed as an ensemble classification scheme employing a support vector machine classifier, specially modified in order to integrate the least squares features transformation logic in its kernel function. The latter, in conjunction with using 3D textural features, enabled boosting up the performance of the system in discriminating metastatic, malignant and benign brain tumors with 77.14%, 89.19% and 93.33% accuracy, respectively. The method was evaluated using an external cross-validation process; thus, results might be considered indicative of the generalization performance of the system to "unseen" cases. The proposed system might be used as an assisting tool for brain tumor characterization on volumetric MRI series.
authors.affiliation: Medical Image Processing and Analysis (MIPA) Group, Laboratory of Medical Physics, Department of Radiology, School of Medicine, University of Patras, Rio GR-26503, Greece. pgeorgiadis@med.upatras.gr
authors.forename: Pantelis
authors.initials: P
authors.lastname: Georgiadis
authors.forename: Dionisis
authors.initials: D
authors.lastname: Cavouras
authors.forename: Ioannis
authors.initials: I
authors.lastname: Kalatzis
authors.forename: Dimitris
authors.initials: D
authors.lastname: Glotsos
authors.forename: Emmanouil
authors.initials: E
authors.lastname: Athanasiadis
authors.forename: Spiros
authors.initials: S
authors.lastname: Kostopoulos
authors.forename: Koralia
authors.initials: K
authors.lastname: Sifaki
authors.forename: Menelaos
authors.initials: M
authors.lastname: Malamas
authors.forename: George
authors.initials: G
authors.lastname: Nikiforidis
authors.forename: Ekaterini
authors.initials: E
authors.lastname: Solomou
mesh_terms: D001932:Brain Neoplasms / Q000175:diagnosis* / Q000473:pathology / Q000556:secondary; D003937:Diagnosis, Differential; D005910:Glioma / Q000175:diagnosis* / Q000473:pathology / Q000556:secondary; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D021621:Imaging, Three-Dimensional; D016018:Least-Squares Analysis; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008579:Meningioma / Q000175:diagnosis* / Q000473:pathology / Q000556:secondary; D010363:Pattern Recognition, Automated / Q000379:methods*; D012680:Sensitivity and Specificity