Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/519529
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.coverage.spatial | Development of an image processing pipeline for the extraction of white matter from MRI | |
dc.date.accessioned | 2023-10-22T05:12:14Z | - |
dc.date.available | 2023-10-22T05:12:14Z | - |
dc.identifier.uri | http://hdl.handle.net/10603/519529 | - |
dc.description.abstract | newline On 100 test images, the acuity of the output images of the two-way diffusion, Adaptive Bilateral Filter (ABF), AKTV and LASKR, measured with the help of Maximum Local Variation (MLV) sharpness metric are 0.0634 ± 0.0041, 0.1218 ± 0.0213, 0.1263 ± 0.0368 and 0.1685 ± 0.0163. Standard Deviation (SD) of noise measured from the output images are 0.0676 ± 0.0158, 1.8654 ± 0.6203, 0.6285 ± 0.2140 and 0.4939 ± 0.2951. On100 low-field MRI slices used for performance assessment, the FCET exhibited Visual Information Fidelity (VIF) scores of 1.3340±0.2764 which is higher than those exhibited by ten state-of-the-art image contrast enhancement algorithms. On 100 MRI slices the Dice Similarity Index (DSI) shown by the Enhanced Fuzzy Segmentation Framework (EFSF), Modified FCM based on Double Estimation (MFCMDE), Spatial FCM (SFCM), Weighted SFCM (WSFCM), and PMSFCA in order are 0.7747 ± 0.0357, 0.38435 ± 0.246, 0.6212 ± 0.3655, 0.4207 ± 0.2784, 0.8300 ± 0.0158 | |
dc.format.extent | xvii, 110 p. | |
dc.language | English | |
dc.relation | p. 104-109 | |
dc.rights | university | |
dc.title | Development of an image processing pipeline for the extraction of white matter from MRI | |
dc.title.alternative | ||
dc.creator.researcher | Vinurajkumar S | |
dc.subject.keyword | Blockiness | |
dc.subject.keyword | Computer Science | |
dc.subject.keyword | Computer Science Information Systems | |
dc.subject.keyword | Engineering and Technology | |
dc.subject.keyword | MRI | |
dc.subject.keyword | PMSFCA | |
dc.description.note | ||
dc.contributor.guide | Anandhavelu S | |
dc.publisher.place | Chennai | |
dc.publisher.university | Anna University | |
dc.publisher.institution | Faculty of Information and Communication Engineering | |
dc.date.registered | ||
dc.date.completed | 2022 | |
dc.date.awarded | 2022 | |
dc.format.dimensions | 21 cm. | |
dc.format.accompanyingmaterial | None | |
dc.source.university | University | |
dc.type.degree | Ph.D. | |
Appears in Departments: | Faculty of Information and Communication Engineering |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
01_title.pdf | Attached File | 23.02 kB | Adobe PDF | View/Open |
02_prelim_pages.pdf | 564.75 kB | Adobe PDF | View/Open | |
03_content.pdf | 7.6 kB | Adobe PDF | View/Open | |
04_abstract.pdf | 8.51 kB | Adobe PDF | View/Open | |
05_chapter 1.pdf | 109.71 kB | Adobe PDF | View/Open | |
06_chapter 2.pdf | 1.28 MB | Adobe PDF | View/Open | |
07_chapter 3.pdf | 2.48 MB | Adobe PDF | View/Open | |
08_chapter 4.pdf | 494.29 kB | Adobe PDF | View/Open | |
09_annexures.pdf | 65.84 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 73.88 kB | Adobe PDF | View/Open |
Items in Shodhganga are licensed under Creative Commons Licence Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0).
Altmetric Badge: