Literature DB >> 25000054

3D texture analysis of MR images to improve classification of paediatric brain tumours: a preliminary study.

Ahmed E Fetit1, Jan Novak2, Andrew C Peet2, Theodoros N Arvanitis1.   

Abstract

Brain and central nervous system (CNS) tumours form the second most common group of cancers in children in the UK, accounting for 27% of all childhood cancers. Initial assessment of tumours from MRI scans is usually performed qualitatively, via radiologists' visual inspection. However, different brain tumours do not always demonstrate clear differences in physical appearance, so a diagnosis is usually made via histopathological examination of biopsy samples taken through surgery. This gives rise to the need for accurate, yet non-invasive diagnostic aids. In a previous study, we demonstrated the potential of MRI texture analysis in capturing quantitative information about paediatric brain tumours. In this work, we carry out a preliminary investigation on the use of 3D (volumetric) texture analysis of T1 and T2-weighted MR images in order to classify paediatric brain tumours. We then compare its performance with the traditional 2D texture analysis approach. Our preliminary findings are very encouraging and show that 3D textural features are capable of capturing more discriminative information about the tumours than the traditional 2D approach. However, it remains necessary to expand the work further to include larger cohorts and additional modalities.

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Year:  2014        PMID: 25000054

Source DB:  PubMed          Journal:  Stud Health Technol Inform        ISSN: 0926-9630


  4 in total

1.  Applications of Artificial Intelligence in Pediatric Oncology: A Systematic Review.

Authors:  Siddhi Ramesh; Sukarn Chokkara; Timothy Shen; Ajay Major; Samuel L Volchenboum; Anoop Mayampurath; Mark A Applebaum
Journal:  JCO Clin Cancer Inform       Date:  2021-12

2.  Machine Learning for Brain Images Classification of Two Language Speakers.

Authors:  Alejandro-Israel Barranco-Gutiérrez
Journal:  Comput Intell Neurosci       Date:  2020-06-06

3.  Hybrid RGSA and Support Vector Machine Framework for Three-Dimensional Magnetic Resonance Brain Tumor Classification.

Authors:  R Rajesh Sharma; P Marikkannu
Journal:  ScientificWorldJournal       Date:  2015-10-04

4.  Prognostic Value of MR Imaging Texture Analysis in Brain Non-Small Cell Lung Cancer Oligo-Metastases Undergoing Stereotactic Irradiation.

Authors:  Valerio Nardone; Paolo Tini; Michelangelo Biondi; Lucio Sebaste; Eleonora Vanzi; Gianmarco De Otto; Giovanni Rubino; Tommaso Carfagno; Giuseppe Battaglia; Pierpaolo Pastina; Alfonso Cerase; Lorenzo Nicola Mazzoni; Fabrizio Banci Buonamici; Luigi Pirtoli
Journal:  Cureus       Date:  2016-04-25
  4 in total

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