首页> 外文会议>International Conference on Computer Engineering and Technology;ICCET 2010 >Uterine Fibroid Segmentation on Multiplan MRI Using FCM, MPFCM and Morphological Operations
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Uterine Fibroid Segmentation on Multiplan MRI Using FCM, MPFCM and Morphological Operations

机译:使用FCM,MPFCM和形态学操作的多计划MRI子宫肌瘤分割

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Uterine fibroid is the most common benign tumor of the female in the world. Uterine volume measurement before and after surgery has an important role in predict and following the result of surgery. Fibroids segmentation in patient with multi fibroids is the challenging task manually. We propose tow step method for robustly segmentation of these cases. The first step results in a uterine segmentation using FCM and some morphological operations in T1 Enhanced and T1 images. In the second step by applying a new method based on FCM,PCM and information of voxels neighborhoods (Modified PFCM_MPFCM) and knowledge based image processing final segmentation created. We compared manually segmented images results with the output of our system and we obtained 79.9% average of similarity index and 68.28% Jaccard index.
机译:子宫肌瘤是世界上最常见的女性良性肿瘤。手术前后的子宫体积测量在预测和跟踪手术结果方面具有重要作用。具有多发性肌瘤的患者中的肌瘤分割是手动的挑战性任务。我们提出了拖曳方法来稳健地分割这些情况。第一步使用FCM进行子宫分割,并在T1增强和T1图像中进行一些形态学操作。第二步,应用基于FCM,PCM和体素邻域信息的新方法(修改后的PFCM_MPFCM),并创建基于知识的图像处理最终分割。我们将手动分割的图像结果与系统输出进行了比较,我们获得了79.9%的平均相似度指数和68.28%的Jaccard指数。

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