Sridhar S, Kumaravel N, Easwarakumar K S
School of Computer Science and Engineering, Anna University, Chennai-600025, India.
Med Inform Internet Med. 2002 Dec;27(4):229-36. doi: 10.1080/1463923021000054217.
An algorithm proposed by Sridhar and Kumaravel is extended to include a framework for the detection of renal calculi. Calculi occur due to abnormal collection of certain chemicals like oxalate, phosphate and uric acid. These calculi can be present in the kidney, ureter or urinary bladder. Performance analysis is done to a set of five known algorithms using parameters such as success rate in calculi detection, border error metric and time. The framework is constructed by combining the best algorithm based on the performance analysis and a procedure to validate the detected calculi using the shadow it casts in ultrasound images. Ultrasound images of 37 patients are used for testing the algorithm. The detected calculi based on the framework match those determined by expert clinicians in more than 95% of the cases.
Sridhar和Kumaravel提出的一种算法被扩展,以纳入一个用于检测肾结石的框架。结石是由于草酸盐、磷酸盐和尿酸等某些化学物质的异常聚集而形成的。这些结石可能存在于肾脏、输尿管或膀胱中。使用结石检测成功率、边界误差度量和时间等参数,对一组五种已知算法进行了性能分析。该框架是通过结合基于性能分析的最佳算法以及使用结石在超声图像中投射的阴影来验证检测到的结石的程序构建而成的。37名患者的超声图像被用于测试该算法。基于该框架检测到的结石在超过95%的病例中与专家临床医生确定的结石相匹配。