| 摘要(英) |
Accurate localization of uterine fibroids from MRI images is crucial for High-Intensity Focused Ultrasound (HIFU) treatment. However, due to significant variations in the shape and size of uterine fibroids among individuals, low contrast with adjacent organs and tissues, and the unknown number of fibroids, it is challenging to precisely extract the position and size of uterine fibroids. Currently, the main approach relies on physicians spending time and using their experience to manually label the uterine fibroid regions in software.
To address this issue, we collaborated with Dr. Lin Gi-Gin′s team from Chang Gung Hospital and provided de-identified abdominal MRI images (IRB number: 202201307B0C502) to propose an image processing method. Firstly, four different combinations of image processing techniques were used to enhance the organ tissue contrast in the MRI images, resulting in four differentiated images. These images were then subjected to K-means clustering individually. Based on the characteristics of uterine fibroid images, we identified the clustering combination that includes the classification of uterine fibroids and other organ tissues as non-uterine fibroids. Finally, a series of post-processing steps including smoothing, noise removal, separation, and fibroid determination were applied to obtain the ultimate results. This method was compared to the traditional manual labeling of uterine fibroids by Dr. Lin Gi-Gin and the radiology team, and it was validated using 30 cases. |
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