title: Automated glioblastoma segmentation based on a multiparametric structured unsupervised classification.
abstract: Automatic brain tumour segmentation has become a key component for the future of brain tumour treatment. Currently, most of brain tumour segmentation approaches arise from the supervised learning standpoint, which requires a labelled training dataset from which to infer the models of the classes. The performance of these models is directly determined by the size and quality of the training corpus, whose retrieval becomes a tedious and time-consuming task. On the other hand, unsupervised approaches avoid these limitations but often do not reach comparable results than the supervised methods. In this sense, we propose an automated unsupervised method for brain tumour segmentation based on anatomical Magnetic Resonance (MR) images. Four unsupervised classification algorithms, grouped by their structured or non-structured condition, were evaluated within our pipeline. Considering the non-structured algorithms, we evaluated K-means, Fuzzy K-means and Gaussian Mixture Model (GMM), whereas as structured classification algorithms we evaluated Gaussian Hidden Markov Random Field (GHMRF). An automated postprocess based on a statistical approach supported by tissue probability maps is proposed to automatically identify the tumour classes after the segmentations. We evaluated our brain tumour segmentation method with the public BRAin Tumor Segmentation (BRATS) 2013 Test and Leaderboard datasets. Our approach based on the GMM model improves the results obtained by most of the supervised methods evaluated with the Leaderboard set and reaches the second position in the ranking. Our variant based on the GHMRF achieves the first position in the Test ranking of the unsupervised approaches and the seventh position in the general Test ranking, which confirms the method as a viable alternative for brain tumour segmentation.
authors.affiliation: Grupo de Informática Biomédica (IBIME), Instituto de Aplicaciones de las Tecnologías de la Información y de las Comunicaciones Avanzadas (ITACA), Universitat Politècnica de València, Valencia, Spain.
authors.forename: Javier
authors.initials: J
authors.lastname: Juan-Albarracín
authors.affiliation: Grupo de Informática Biomédica (IBIME), Instituto de Aplicaciones de las Tecnologías de la Información y de las Comunicaciones Avanzadas (ITACA), Universitat Politècnica de València, Valencia, Spain; Veratech for Health S.L., Valencia, Spain.
authors.forename: Elies
authors.initials: E
authors.lastname: Fuster-Garcia
authors.affiliation: Grupo de Informática Biomédica (IBIME), Instituto de Aplicaciones de las Tecnologías de la Información y de las Comunicaciones Avanzadas (ITACA), Universitat Politècnica de València, Valencia, Spain.
authors.forename: José V
authors.initials: JV
authors.lastname: Manjón
authors.affiliation: Grupo de Informática Biomédica (IBIME), Instituto de Aplicaciones de las Tecnologías de la Información y de las Comunicaciones Avanzadas (ITACA), Universitat Politècnica de València, Valencia, Spain.
authors.forename: Montserrat
authors.initials: M
authors.lastname: Robles
authors.affiliation: Servicio de Radiología, Área imagen Clínica, Hospital Universitario y Politécnico La Fe, Valencia, Spain.
authors.forename: F
authors.initials: F
authors.lastname: Aparici
authors.affiliation: Department of Radiology and GIBI230 Research Group on Biomedical Imaging, Hospital Universitario y Politécnico La Fe, Valencia, Spain.
authors.forename: L
authors.initials: L
authors.lastname: Martí-Bonmatí
authors.affiliation: Grupo de Informática Biomédica (IBIME), Instituto de Aplicaciones de las Tecnologías de la Información y de las Comunicaciones Avanzadas (ITACA), Universitat Politècnica de València, Valencia, Spain; Department of Radiology and GIBI230 Research Group on Biomedical Imaging, Hospital Universitario y Politécnico La Fe, Valencia, Spain.
authors.forename: Juan M
authors.initials: JM
authors.lastname: García-Gómez
mesh_terms: D000465:Algorithms; D001932:Brain Neoplasms / Q000175:diagnosis; D005909:Glioblastoma / Q000175:diagnosis*; D006801:Humans; D008279:Magnetic Resonance Imaging