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Title:: Study on auxiliary diagnosis system of ovarian cyst based on image detail enhancement

作者:: 郑淑婕1 ; 李保珍2 ; 郭华娟1 ; 王振华2 ; 杨少琴3△; 1.河南省开封市妇幼保健院妇科，开封 475002；2.河南省开封市妇幼保健院影像科，开封 475002；3.河南大学第二附属医院，开封 475002

Author(s):: ZHENG Shujie1 ; LI Baozhen 2 ; GUO Huajuan1 ; WANG Zhenhua2; YANG Shaoqin3; 1. Department of Gynecology, Maternal and Child Health Hospital, Kaifeng 475002,China;2. Department of Radiology, Maternal and Child Health Hospital, Kaifeng 475002;3.Second Affiliated Hospital of Henan University,Kaifeng 475002

Keywords:: Image detail enhancement; Ovarian cysts; Auxiliary diagnosis; Reading modules; Adaptive; Filter

摘要:: 为尽早诊断卵巢囊肿，设计基于影像细节增强的卵巢囊肿辅助诊断系统。系统采用卵巢囊肿影像读取模块，通过用于医学影像分割和配准的工具包（insight segmentation and registration toolkit,ITK)确定卵巢囊肿影像类型,读取卵巢囊肿影像，采用ITK中高斯低通滤波器增强影像细节；卵巢囊肿影像处理模块采用DICOM3.0协议和DSP TMS320 DM624芯片传输和增强处理卵巢囊肿影像；采用自适应滤波算法，通过影像转换、低通滤波器分频和线性组合转化影像增强卵巢囊肿影像。仿真实验结果表明，我们设计系统显著增强卵巢囊肿病变细节发生位置，有效提升卵巢囊肿疾病的辅助诊断正确率。

Abstract:: To diagnose ovarian cysts as early as possible in the early stages of the disease, we designed an assisted diagnosis system based on enhanced imaging details of ovarian cysts. The system used the ovarian cyst image reading module, determined the type of ovarian cyst image, readed the ovarian cyst image, and used the Gaussian low-pass filter in ITK to enhance the image details through the tool kit ITK used for medical image segmentation and registration.The ovarian cyst image processing module used DICOM 3.0 protocol and DSP TMS320 DM624 chip to transmit and enhanced the treatment of ovarian cyst images; Adaptive filtering algorithm was used to enhance the image of ovarian cyst by image transformation, low pass filter frequency division and linear combination transformation. Simulation results show that the system can significantly enhance the location of ovarian cyst lesions and improve the diagnostic accuracy of ovarian cyst diseases.