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2018 | OriginalPaper | Buchkapitel

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

verfasst von : Mohamed Amine Larhmam, Saïd Mahmoudi, Stylianos Drisis, Mohammed Benjelloun

Erschienen in: Bioinformatics and Biomedical Engineering

Verlag: Springer International Publishing

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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.

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Fußnoten
1
Multidisciplinary and autonomous hospital totally dedicated to cancer located in Brussels, Belgium.
 
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Metadaten
Titel
A Texture Analysis Approach for Spine Metastasis Classification in T1 and T2 MRI
verfasst von
Mohamed Amine Larhmam
Saïd Mahmoudi
Stylianos Drisis
Mohammed Benjelloun
Copyright-Jahr
2018
DOI
https://doi.org/10.1007/978-3-319-78759-6_19