Abstract
High-intensity focused ultrasound (HIFU) therapy has been used to treat uterine fibroids widely and successfully. Uterine fibroid segmentation plays an important role in positioning the target region for HIFU therapy. Presently, it is completed by physicians manually, reducing the efficiency of therapy. Thus, computer-aided segmentation of uterine fibroids benefits the improvement of therapy efficiency. Recently, most computer-aided ultrasound segmentation methods have been based on the framework of contour evolution, such as snakes and level sets. These methods can achieve good performance, although they need an initial contour that influences segmentation results. It is difficult to obtain the initial contour automatically; thus, the initial contour is always obtained manually in many segmentation methods. A split-and-merge-based uterine fibroid segmentation method, which needs no initial contour to ensure less manual intervention, is proposed in this paper. The method first splits the image into many small homogeneous regions called superpixels. A new feature representation method based on texture histogram is employed to characterize each superpixel. Next, the superpixels are merged according to their similarities, which are measured by integrating their Quadratic-Chi texture histogram distances with their space adjacency. Multi-way Ncut is used as the merging criterion, and an adaptive scheme is incorporated to decrease manual intervention further. The method is implemented using Matlab on a personal computer (PC) platform with Intel Pentium Dual-Core CPU E5700. The method is validated on forty-two ultrasound images acquired from HIFU therapy. The average running time is 9.54 s. Statistical results showed that SI reaches a value as high as 87.58%, and normHD is 5.18% on average. It has been demonstrated that the proposed method is appropriate for segmentation of uterine fibroids in HIFU pre-treatment imaging and planning.
Highlights
Uterine fibroids are one of the commonest benign tumors to occur among women, with an estimated incidence rate of 20–40% of women during their reproductive years [1]
The proposed method is validated on a data set of 42 real ultrasound images from high-intensity focused ultrasound (HIFU) therapy described in the Materials subsection
A split-and-merge-based uterine fibroid segmentation method in HIFU therapy is presented in the present study
Summary
Uterine fibroids are one of the commonest benign tumors to occur among women, with an estimated incidence rate of 20–40% of women during their reproductive years [1]. Uterine fibroids can cause significant morbidity such as heavy menstrual bleeding and pelvic pressure [2]. They seriously threaten women’s health and influence their quality of life. The two most popular methods of guidance are MRI based and ultrasound based [3] Both methods have been used in HIFU therapy for uterine fibroids, and each has its advantages and disadvantages. We focus on segmentations of uterine fibroids in ultrasound guidance images. It is significant to propose a computer-aided uterine fibroid segmentation method in HIFU therapy that can relieve physicians’ burdens and improve therapy efficiency
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