Automated recognition of urinary microscopic solid particles

被引：10

作者：

Almadhoun, Mohamed D. ^{[1
]}

El-Halees, Alaa ^{[2
]}

机构：

[1] Information Technology Department, University College of Applied Sciences, Gaza, Palestine

[2] Faculty of Information Technology, Islamic University of Gaza, Gaza, Palestine

来源：

Journal of Medical Engineering and Technology | 2014年 / 38卷 / 02期

关键词：

Blood - Computer aided diagnosis - Data mining - Feature extraction - Medical computing - Medical imaging - Cells - Computer aided analysis - Classification (of information);

D O I：

10.3109/03091902.2013.863394

中图分类号：

学科分类号：

摘要：

Urine analysis reveals the presence of many problems and diseases in the human body. Manual microscopic urine analysis is time-consuming, subjective to human observation and causes mistakes. Computer aided automatic microscopic analysis can help to overcome these problems. This paper introduces a comprehensive approach for automating procedures for detecting and recognition of microscopic urine particles. Samples of red blood cells (RBC), white blood cells (WBC), calcium oxalate, triple phosphate and other undefined images were used in experiments. Image processing functions and segmentation were applied, shape and textural features were extracted and five classifiers were tested to get the best results. Repeated experiments were done for adjusting factors to produce the best evaluation results. A good performance was achieved compared with many related works. © 2014 Informa UK Ltd. All rights reserved: reproduction in whole or part not permitted.

引用

页码：104 / 110