Quantitative determination of stone fragmentation efficiency

• Main Author: Tan, Sheng Jie
• Other Authors: Zhou Yufeng
• Format: Final Year Project
• Language: English
• Published: 2017
• Subjects: DRNTU::Engineering::Mechanical engineering
• Online Access: http://hdl.handle.net/10356/72218
• Institution: Nanyang Technological University

With the increasing trend of occurrence of people being diagnosed with kidney stone disease, extra care should be taken in providing treatment to patients, due to the severity of complications that it encompasses. The absence of accurate clinical methods to assess the process of shockwave lithotripsy treatment sparks the possibility of mistreatment. Overtreatment may lead to renal and tissue injuries, while undertreatment reduces the efficiency of treatment. Investigations were conducted to seek a better detection method to increase the effectiveness of kidney stone treatment. This will be done through numerical simulations through MATLAB, to determine effective algorithms for stone detection. Time Reversal Multiple Signal Classification (TR-MUSIC) is chosen as the focus. Results are obtained and discussed. The report is then concluded and future work for improvements are stated.