Title :
Automated algorithm for ovarian cysts detection in ultrasonogram
Author :
Rihana, Sandy ; Moussallem, Hares ; Skaf, Chiraz ; Yaacoub, Charles
Author_Institution :
Biomed. Eng. Dept., Holy Spirit Univ. of Kaslik (USEK), Jounieh, Lebanon
Abstract :
Polycystic Ovary Syndrome (PCOS) is a female endocrine disorder which severely affects women´s health and its diagnostic requires medical treatment or even surgery. Manual analysis of PCOS diagnosis often produces errors. Recently, many automated algorithms have been studied for polycysts detection in Ultrasound images. This paper presents cysts detection and classification in the ovary ultrasound images with an accuracy that reaches 90%.
Keywords :
biomedical ultrasonics; image classification; medical disorders; medical image processing; surgery; ultrasonic therapy; PCOS diagnosis; female endocrine disorder; medical treatment; ovarian cysts detection; polycystic ovary syndrome; polycysts detection; surgery; ultrasonogram; ultrasound image classification; women health; Accuracy; Biomedical imaging; Feature extraction; Image segmentation; Shape; Standards; Ultrasonic imaging; cysts; multiscale morphological method; svm; thresholding; ultrasound medical imaging;
Conference_Titel :
Advances in Biomedical Engineering (ICABME), 2013 2nd International Conference on
Conference_Location :
Tripoli
Print_ISBN :
978-1-4799-0249-1
DOI :
10.1109/ICABME.2013.6648887
