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Semi-automatic segmentation of renal cortex and medulla based on dynamic magnetic resonance images

机译:基于动态磁共振图像的肾皮质和髓质半自动分割

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Image-based functional analysis of the kidney plays an increasingly important role in the clinical application. Efficiently and accurately segment the renal cortex and the medulla in MR images will be very helpful for doctor's clinical diagnosis. This paper proposed a semi-automatic segmentation method of renal cortex and medulla based on dynamic magnetic resonance (MR) images of pigs. This segmentation method includes the 3D registration, subtraction and the amendment by using morphology method. The accuracy and precision of the segmentation method on dynamic MR images were evaluated by 11 model pigs. The correlation of renal cortex segmentation result between our method and manual method from doctor in 15 kidneys was 0.9874, while the correlation of signal intensity of the segmented result was 0.9901. Besides, it took less than 1 minute to segment three phases of renal cortex, compared to 20 minutes for manual segmentation. Moreover, by using our semi-automatic segmentation method, we can extract the renal cortex from non-contrast scan images.
机译:基于图像的肾脏功能分析在临床应用中起着越来越重要的作用。有效而准确地在MR图像中分割肾皮质和髓质将对医生的临床诊断非常有帮助。提出了一种基于猪动态磁共振图像的半自动肾皮质和延髓分割方法。这种分割方法包括3D配准,减法和使用形态学方法的修正。对11只模型猪进行了动态MR图像分割方法的准确性和准确性。我们的方法和医生的人工方法在15个肾脏中进行的肾皮质分割结果的相关性为0.9874,而分割结果的信号强度的相关性为0.9901。此外,分割肾皮质的三个阶段所需的时间少于1分钟,而手动分割所需的时间则为20分钟。此外,通过使用半自动分割方法,我们可以从非对比扫描图像中提取肾皮质。

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