Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/522060
Title: | Study on impact of voice box changes in vocal cord |
Researcher: | Antony Sophia N |
Guide(s): | Wiselin Jiji G |
Keywords: | Computed Tomography Computer Aided Diagnosis Computer Science Computer Science Software Engineering Engineering and Technology Moth Search Algorithm |
University: | Anna University |
Completed Date: | 2023 |
Abstract: | Medical imaging plays a major role in diagnosing. Literature said that many people including singers, teachers and preachers had facing serious issues because of voice change. The voice could be changed because of the distress caused in vocal cord. Computer aided diagnosis (CAD) is also one of the challenging task. Physicians getting second opinion through CAD before the treatment process starts. Therefore, an automated statistical tool is required to identify voice change detection. This research is carried out in neck Computed Tomography (CT) images to identify and classify the vocal cord pathologies using an advanced multi-resolution algorithm (MRA). The vocal cord regions are determined using genetic k-means clustering. The pathology features are generated using the Local directional pattern (LDP) that fed for pathology classification using Moth search-rider optimization algorithm (MS-ROA). The hybrid optimization technique, integrates the standard Rider Optimization Algorithm (ROA) and Moth Search Algorithm (MS) to train Deep convolutional neural newlinenetwork (DCNN). The analysis using the real databases regarding the performance metrics revealed that the proposed pathology detection module obtained the accuracy, specificity, and sensitivity of 97.020%, 91.698%, and 96.624%. The laryngeal variation caused by Vocal cord Ulcer is determine and analyze using three dimensional Swin Transformation Volumetric Segmentation Network (3DSTVSNet) in CT images. 3D STVSNet reduces the entanglement and improves the segmentation accuracy. Volumetric quantification on Contrast Enhanced computed tomography (CECT), utilize 3D STVSNet for the extraction of shapes feature that used to evaluate the Vocal cord ulcer (VCU) severity. Evaluation results were 96.20% of sensitivity, 97.15% of accuracy and 96.16% of specificity. Thyroid nodule is common in both genders, its categories into hyper and hypo thyroid. Low Thyroxine indicates hypothyroid and High Thyroxine indicates hyperthyroid. Thyroid nodules are lumps of thyrocytes in the thy |
Pagination: | xx,155 |
URI: | http://hdl.handle.net/10603/522060 |
Appears in Departments: | Faculty of Information and Communication Engineering |
Files in This Item:
File | Description | Size | Format | |
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01_title.pdf | Attached File | 182.99 kB | Adobe PDF | View/Open |
02_prelim_pages.pdf | 3.15 MB | Adobe PDF | View/Open | |
03_content.pdf | 183.99 kB | Adobe PDF | View/Open | |
04_abstract.pdf | 282.8 kB | Adobe PDF | View/Open | |
05_chapter 1.pdf | 671.52 kB | Adobe PDF | View/Open | |
06_chapter 2.pdf | 397.02 kB | Adobe PDF | View/Open | |
07_chapter 3.pdf | 1.14 MB | Adobe PDF | View/Open | |
08_chapter 4.pdf | 1.05 MB | Adobe PDF | View/Open | |
09_chapter 5.pdf | 1.08 MB | Adobe PDF | View/Open | |
10_annexures.pdf | 258.38 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 105.32 kB | Adobe PDF | View/Open |
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