3D Probabilistic Morphable Models for Brain Tumor Segmentation

  • David A. Jimenez
  • Hernán F. García
  • Andres M. Álvarez
  • Álvaro A. Orozco
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10657)


Segmenting abnormal areas in brain volumes is a difficult task, due to the shape variability that the brain tumors exhibit between patients. The main problem in these processes is that the common segmentation techniques used in these tasks, lack of the property of modeling the shape structure that the tumor presents, which leads to an inaccurate segmentation. In this paper, we propose a probabilistic framework in order to model the shape variations related to abnormal tissues relevant in brain tumor segmentation procedures. For this purpose the database of the Brain Tumor Image Segmentation Challenge (Brats) 2015 is used. We use a Probabilistic extension of the 3D morphable model to learn those tumor variations between patients. Then from the trained model, we perform a non-rigid matching to fit the deformed modeled tumor in the medical image. The experimental results show that by using Probabilistic morphable models, the non-rigid properties of the abnormal tissues can be learned and hence improve the segmentation task.


Brain tumor segmentation 3D brain models Shape fitting Probabilistic morphable models 



This research is developed under the project “Desarrollo de un sistema de soporte clínico basado en el procesamiento estócasitco para mejorar la resolución espacial de la resonancia magnética estructural y de difusión con aplicación al procedimiento de la ablación de tumores” financed by COLCIENCIAS with code 111074455860 under the program: 744 Convocatoria para proyectos de ciencia, tecnología e innovación en salud 2016. H.F. García is funded by Colciencias under the program: Formación de alto nivel para la ciencia, la tecnología y la innovación - Convocatoria 617 de 2013 with code 111065740687. Thanks to the master program of electrical engineer of the UTP for the support.


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • David A. Jimenez
    • 1
  • Hernán F. García
    • 1
  • Andres M. Álvarez
    • 1
  • Álvaro A. Orozco
    • 1
  1. 1.Grupo de Investigación en AutomáticaUniversidad Tecnológica de PereiraPereiraColombia

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