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http://hdl.handle.net/10603/338038
Title: | Efficgnt ultrasound liver image diagnosis using bio aspired algorithms |
Researcher: | Sudha S |
Guide(s): | Ezhilarasi M |
Keywords: | Engineering and Technology Engineering Engineering Biomedical ultrasound liver image |
University: | Anna University |
Completed Date: | 2019 |
Abstract: | Health is a prominent issue in human life. Among all other diseases, liver disease is a very dangerous disease faced by human beings around the world. Due to advanced technology, today s hospitals are well equipped with updated data collection and communication device, which paves the way for easy sharing of information among systems.But still the task of establishing an accurate diagnosis of a disease has been a critical task in the medical field. The liver diseases could not easily be identified at an early stage as it will be functioning normally even when it is partially amaged. Indeed, an early diagnosis of liver issues will raise the patient slife span. Numerous artificial intelligence and optimization algorithms have recently gained a lot of attraction in medical diagnosis which are utilized to diagnose the disease through the acquired data. Computer Aided Diagnostic (CAD) techniques have become important in the medical industry due to its improved efficiency. The current specialists in the developments of advanced algorithms ensure the enhanced precision of discernment and analysis of diseases. Hence, the primary issue of anticipating and diagnosing the disease at an early stage can be solved by implementing improvised algorithms. CAD-based image processing techniques include Preprocessing, feature extraction, feature selection and classification. In this CAD process, Preprocessing performs noise reduction and improves image quality, feature extraction and feature selection techniques are used to extract feature vectors, and select the best features for further classification with the optimized solution based on the type of liver disease. newline |
Pagination: | xx, 181p |
URI: | http://hdl.handle.net/10603/338038 |
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 | 164.28 kB | Adobe PDF | View/Open |
02_certificates.pdf | 148.84 kB | Adobe PDF | View/Open | |
03_vivaproceedings.pdf | 288.51 kB | Adobe PDF | View/Open | |
04_bonafidecertificate.pdf | 248.92 kB | Adobe PDF | View/Open | |
05_abstracts.pdf | 261.32 kB | Adobe PDF | View/Open | |
06_acknowledgements.pdf | 269.76 kB | Adobe PDF | View/Open | |
07_contents.pdf | 283.32 kB | Adobe PDF | View/Open | |
08_listoftables.pdf | 139.48 kB | Adobe PDF | View/Open | |
09_listoffigures.pdf | 157.44 kB | Adobe PDF | View/Open | |
10_listofabbreviations.pdf | 650.17 kB | Adobe PDF | View/Open | |
11_chapter1.pdf | 749.02 kB | Adobe PDF | View/Open | |
12_chapter2.pdf | 450.65 kB | Adobe PDF | View/Open | |
13_chapter3.pdf | 1.47 MB | Adobe PDF | View/Open | |
14_chapter4.pdf | 1.32 MB | Adobe PDF | View/Open | |
15_chapter5.pdf | 2.19 MB | Adobe PDF | View/Open | |
16_conclusion.pdf | 269.1 kB | Adobe PDF | View/Open | |
17_references.pdf | 302.31 kB | Adobe PDF | View/Open | |
18_listofpublications.pdf | 259.63 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 146.13 kB | Adobe PDF | View/Open |
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