Ning Guochen, Zhang Xinran, Liao Hongen
Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, 100084, People's Republic of China.
Healthc Technol Lett. 2019 Nov 26;6(6):172-175. doi: 10.1049/htl.2019.0067. eCollection 2019 Dec.
High-intensity focused ultrasound (HIFU) therapy represents an image-guided and non-invasive surgical approach to treat uterine fibroid. During the HIFU operation, it is challenging to obtain the real-time and accurate lesion contour automatically in ultrasound (US) video. The current intraoperative image processing is completed manually or semi-automatic. In this Letter, the authors propose a morphological active contour without an edge-based model to obtain accurate real-time and non-rigid US lesion contour. Firstly, a targeted image pre-processing procedure is applied to reduce the influence of inadequate image quality. Then, an improved morphological contour detection method with a customised morphological kernel is harnessed to solve the low signal-to-noise ratio of HIFU US images and obtain an accurate non-rigid lesion contour. A more reasonable lesion tracking procedure is proposed to improve tracking accuracy especially in the case of large displacement and incomplete lesion area. The entire framework is accelerated by the GPU to achieve a high frame rate. Finally, a non-rigid, real-time and accurate lesion contouring for intraoperative US video is provided to the doctor. The proposed procedure could reach a speed of more than 30 frames per second in general computer and a Dice similarity coefficient of 90.67% and Intersection over Union of 90.14%.
高强度聚焦超声（HIFU）治疗是一种用于治疗子宫肌瘤的图像引导非侵入性手术方法。在HIFU手术过程中，要在超声（US）视频中自动获取实时、准确的病变轮廓具有挑战性。当前的术中图像处理是手动或半自动完成的。在这封信中，作者提出了一种基于形态学的无边缘主动轮廓模型，以获取准确的实时非刚性US病变轮廓。首先，应用有针对性的图像预处理程序来减少图像质量不足的影响。然后，利用一种改进的带有定制形态学内核的形态学轮廓检测方法，来解决HIFU US图像信噪比低的问题，并获得准确的非刚性病变轮廓。提出了一种更合理的病变跟踪程序，以提高跟踪精度，特别是在大位移和病变区域不完整的情况下。整个框架通过GPU加速以实现高帧率。最后，为医生提供术中US视频的非刚性、实时且准确的病变轮廓描绘。所提出的程序在普通计算机上可以达到每秒30多帧的速度，骰子相似系数为90.67%，交并比为90.14%。
