Volume of Interest-Based Fractal Analysis of Huffaz’s Brain
The robust process in memorising the Quran is expected to cause neuroplasticity changes in the brain. To date, the analysis of neuroplasticity is limited in binary images because greyscale analysis requires the usage of more robust processing techniques. This research work aims to explore and charac...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-07-01
|
| Series: | Fractal and Fractional |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2504-3110/6/7/396 |
| _version_ | 1797406278073450496 |
|---|---|
| author | Iqbal Jamaludin Mohd Zulfaezal Che Azemin Mohd Izzuddin Mohd Tamrin Abdul Halim Sapuan |
| author_facet | Iqbal Jamaludin Mohd Zulfaezal Che Azemin Mohd Izzuddin Mohd Tamrin Abdul Halim Sapuan |
| author_sort | Iqbal Jamaludin |
| collection | DOAJ |
| description | The robust process in memorising the Quran is expected to cause neuroplasticity changes in the brain. To date, the analysis of neuroplasticity is limited in binary images because greyscale analysis requires the usage of more robust processing techniques. This research work aims to explore and characterise the complexity of textual memorisation brain structures using fractal analysis between huffaz and non-huffaz applying global box-counting, global Fourier fractal dimension (FFD), and volume of interest (VOI)-based analysis. The study recruited 47 participants from IIUM Kuantan Campus. The huffaz group had their 18 months of systematic memorisation training. The brain images were acquired by using MRI. Global box-counting and FFD analysis were conducted on the brain. Magnetic resonance imaging (MRI) found no significant statistical difference between brains of huffaz and non-huffaz. VOI-based analysis found nine significant areas: two for box-counting analysis (angular gyrus and medial temporal gyrus), six for FFD analysis (BA20, BA30, anterior cingulate, fusiform gyrus, inferior temporal gyrus, and frontal lobe), and only a single area (BA33) showed significant volume differences between huffaz and non-huffaz. The results have highlighted the sensitivity of VOI-based analysis because of its local nature, as compared to the global analysis by box-counting and FFD. |
| first_indexed | 2024-03-09T03:23:09Z |
| format | Article |
| id | doaj.art-06dff4a2fc79462880b77735874d7e30 |
| institution | Directory Open Access Journal |
| issn | 2504-3110 |
| language | English |
| last_indexed | 2024-03-09T03:23:09Z |
| publishDate | 2022-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Fractal and Fractional |
| spelling | doaj.art-06dff4a2fc79462880b77735874d7e302023-12-03T15:04:57ZengMDPI AGFractal and Fractional2504-31102022-07-016739610.3390/fractalfract6070396Volume of Interest-Based Fractal Analysis of Huffaz’s BrainIqbal Jamaludin0Mohd Zulfaezal Che Azemin1Mohd Izzuddin Mohd Tamrin2Abdul Halim Sapuan3Department of Diagnostic Imaging and Radiotherapy, Kulliyyah of Allied Health Sciences, International Islamic University Malaysia, Kuantan 25200, MalaysiaDepartment of Optometry and Visual Science, Kulliyyah of Allied Health Sciences, International Islamic University Malaysia, Kuantan 25200, MalaysiaDepartment of Information System, Kulliyyah of Information and Communication Technology, International Islamic University Malaysia, Kuala Lumpur 53100, MalaysiaDepartment of Diagnostic Imaging and Radiotherapy, Kulliyyah of Allied Health Sciences, International Islamic University Malaysia, Kuantan 25200, MalaysiaThe robust process in memorising the Quran is expected to cause neuroplasticity changes in the brain. To date, the analysis of neuroplasticity is limited in binary images because greyscale analysis requires the usage of more robust processing techniques. This research work aims to explore and characterise the complexity of textual memorisation brain structures using fractal analysis between huffaz and non-huffaz applying global box-counting, global Fourier fractal dimension (FFD), and volume of interest (VOI)-based analysis. The study recruited 47 participants from IIUM Kuantan Campus. The huffaz group had their 18 months of systematic memorisation training. The brain images were acquired by using MRI. Global box-counting and FFD analysis were conducted on the brain. Magnetic resonance imaging (MRI) found no significant statistical difference between brains of huffaz and non-huffaz. VOI-based analysis found nine significant areas: two for box-counting analysis (angular gyrus and medial temporal gyrus), six for FFD analysis (BA20, BA30, anterior cingulate, fusiform gyrus, inferior temporal gyrus, and frontal lobe), and only a single area (BA33) showed significant volume differences between huffaz and non-huffaz. The results have highlighted the sensitivity of VOI-based analysis because of its local nature, as compared to the global analysis by box-counting and FFD.https://www.mdpi.com/2504-3110/6/7/3963D Fourier fractal dimension3D box-counting fractal dimensionmagnetic resonance imaging (MRI)volume of interest (VOI) |
| spellingShingle | Iqbal Jamaludin Mohd Zulfaezal Che Azemin Mohd Izzuddin Mohd Tamrin Abdul Halim Sapuan Volume of Interest-Based Fractal Analysis of Huffaz’s Brain Fractal and Fractional 3D Fourier fractal dimension 3D box-counting fractal dimension magnetic resonance imaging (MRI) volume of interest (VOI) |
| title | Volume of Interest-Based Fractal Analysis of Huffaz’s Brain |
| title_full | Volume of Interest-Based Fractal Analysis of Huffaz’s Brain |
| title_fullStr | Volume of Interest-Based Fractal Analysis of Huffaz’s Brain |
| title_full_unstemmed | Volume of Interest-Based Fractal Analysis of Huffaz’s Brain |
| title_short | Volume of Interest-Based Fractal Analysis of Huffaz’s Brain |
| title_sort | volume of interest based fractal analysis of huffaz s brain |
| topic | 3D Fourier fractal dimension 3D box-counting fractal dimension magnetic resonance imaging (MRI) volume of interest (VOI) |
| url | https://www.mdpi.com/2504-3110/6/7/396 |
| work_keys_str_mv | AT iqbaljamaludin volumeofinterestbasedfractalanalysisofhuffazsbrain AT mohdzulfaezalcheazemin volumeofinterestbasedfractalanalysisofhuffazsbrain AT mohdizzuddinmohdtamrin volumeofinterestbasedfractalanalysisofhuffazsbrain AT abdulhalimsapuan volumeofinterestbasedfractalanalysisofhuffazsbrain |