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A Texture Analysis Approach for Spine Metastasis Classification in T1 and T2 MRI

  • Mohamed Amine LarhmamEmail author
  • Saïd Mahmoudi
  • Stylianos Drisis
  • Mohammed Benjelloun
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10814)

Abstract

This paper presents a learning based approach for the classification of pathological vertebrae. The proposed method is applied to spine metastasis, a malignant tumor that develops inside bones and requires a rapid diagnosis for an effective treatment monitoring. We used multiple texture analysis techniques to extract useful features from two co-registered MR images sequences (T1, T2). These MRIs are part of a diagnostic protocol for vertebral metastases follow up. We adopted a slice by slice MRI analysis of 153 vertebra region of interest. Our method achieved a classification accuracy of \(90.17\% \pm 5.49\), using only a subset of 67 relevant selected features from the initial 142.

Keywords

MRI Machine learning Texture analysis GLCM LBP 

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Computer Science Department, Faculty of EngineeringUniversity of MonsMonsBelgium
  2. 2.Radiology Department, Jules Bordet InstituteUniversité Libre de BruxellesBrusselsBelgium

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