Research on Region Segmentation Algorithm of Hepatic Cystic Echinococcosis Ultrasonoscopy
WANG Zhengye1a, AIHEMAITINIYAZI Renaguli1a, WANG Xiaorong2, HAILATI Miwueryiti1a, YAN Chuanbo1b
1. a. School of Public Health; b. College of Medical Engineering and Technology, Xinjiang Medical University, Urumqi Xinjiang
830011, China; 2. Department of Ultrasonic Diagnosis, The First Affiliated Hospital of Xinjiang Medical University, Urumqi
Xinjiang 830011, China
Abstract：Objective To test the performance of Ostu threshold segmentation method, Markov random field segmentation method
and Poly-YOLO network model segmentation method based on deep learning in ultrasound image of hepatic cystic echinococcosis.
Methods Three segmentation methods under single scale image enhancement were respectively used to segment the fan-shaped
image area in the ultrasound image of cystic liver hydatid to remove the interference information in the image. Dice similarity
coefficient (DSC), intersection of union (IOU), true positive rate (TPR) and Hausdorff distance (HD) were used to evaluate the
efficiency of the above three algorithms. Results Poly-YOLO algorithm had good segmentation results for ultrasound images of
hepatic cystic echinococcosis. While effectively removing non-image area, the DSC was 0.80, TPR was 0.88, IOU was 0.71, and
HD was 2.11. Conclusion Compared with the Ostu threshold segmentation method based on SSR and the Markov random field
image segmentation algorithm, the Poly-YOLO network based on deep learning can better segment the fan-shaped image area of
the ultrasound image of hepatic cystic echinococcosis, remove the non-image information in the image, and lay a certain theoretical
foundation for the follow-up study of automatic classification of lesions.
王正业1a，热娜古丽·艾合麦提尼亚孜1a，王晓荣2，米吾尔依提·海拉提1a，严传波1b. 肝囊型包虫病超声图影像区域分割算法研究[J]. 中国医疗设备, 2022, 37(10): 18-23.
WANG Zhengye1a, AIHEMAITINIYAZI Renaguli1a, WANG Xiaorong2, HAILATI Miwueryiti1a, YAN Chuanbo1b. Research on Region Segmentation Algorithm of Hepatic Cystic Echinococcosis Ultrasonoscopy. China Medical Devices, 2022, 37(10): 18-23.
