Characterization of Pineal Region in MR Brain Images using Texture Analysis

Journal Title: IOSR Journal of Applied Physics (IOSR-JAP) - Year 2018, Vol 10, Issue 5

Abstract

The classification processes of MRI brain were defining the corpus,pineal gland, techunum, and third ventricle were carried out using Interactive Data Language (IDL) program as platform for the generated codes. The result of the classification showed that the pineal gland areas were classified well from the rest of the tissues although it has characteristics mostly similar to surrounding tissue. The results show that the Gray Level variation and features give classification accuracy Several texture features are introduced using Gray Level variation and features and the FOS gives a classification score matrix generated by linear discriminate analysis and the overall classification accuracy was 92.7%, were the classification accuracy of corpus 93.3%, pineal gland 97.9%, techunum 89.9%, while the third ventricle showed classification accuracy 88.5%. These relationshipsare stored in a Texture Dictionary that can be later used to automatically annotate new MRI with the appropriate pineal gland

Authors and Affiliations

Mazin B. A. Hassib1,2,, Ahmed B. A. Hassib1 ,, Abbas K. A. Ibrahim3 ,

Keywords

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Characterization of Pineal Region in MR Brain Images using Texture Analysis

The classification processes of MRI brain were defining the corpus,pineal gland, techunum, and third ventricle were carried out using Interactive Data Language (IDL) program as platform for the generated codes. The resul...

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  • EP ID EP415519
  • DOI -
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How To Cite

Mazin B. A. Hassib1, 2, , Ahmed B. A. Hassib1, , Abbas K. A. Ibrahim3, (2018). Characterization of Pineal Region in MR Brain Images using Texture Analysis. IOSR Journal of Applied Physics (IOSR-JAP), 10(5), 32-37. https://www.europub.co.uk/articles/-A-415519