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RPT誌優秀論文土井賞• Most Citation Award授賞式· 土井賞受賞講演

机译:RPT杂志杰出纸Doi奖•最佳引用奖颁奖典礼•Doi获奖演讲

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摘要

We propose an approach to supporting pre-surgical planning for the uterus by integrating medical image analysis and physical model generation based on 3D printing. With our method, we first segment the patient-specific anatomy and lesions of the uterus on MR images; then, we create a 3D physical model, an exact replica of the patient's uterus in terms of size and softness, with transparency for easy observation of the internal structures of the uterus. In our experiments, we created pre-surgical models of hysterectomy for five patients who had been diagnosed to have uterine endometrial cancer. An experienced radiologist, the surgeons, and all of the patients cooperated in our experiment for carrying out subjective evaluations of the usefulness of our model. The accuracy of the physical models was evaluated quantitatively by comparison between the MR images of the patients and the CT images of the models. The results showed that the mean values of the errors in gap ranged from 1.19 to 2.22 mm, which was satisfactory for the surgeons. The feedback from both surgeons and patients demonstrated the usefulness and convenience of the models for efficient patient explanation understanding and pre-surgical planning by surgeons.
机译:我们提出了一种通过整合医学图像分析和基于3D打印的物理模型生成来支持子宫的术前计划的方法。使用我们的方法,我们首先在MR图像上分割患者特定的解剖结构和子宫病变;然后,我们创建一个3D物理模型,根据大小和柔软度精确复制患者子宫,并具有透明性,以便于观察子宫的内部结构。在我们的实验中,我们为五名被诊断患有子宫内膜癌的患者创建了子宫切除术的术前模型。经验丰富的放射科医生,外科医生和所有患者在我们的实验中进行了合作,以对模型的实用性进行主观评估。通过比较患者的MR图像和模型的CT图像,定量评估了物理模型的准确性。结果表明,间隙误差的平均值在1.19至2.22 mm之间,这对于外科医生来说是令人满意的。来自外科医生和患者的反馈证明了该模型的有用性和便利性,可以有效地解释患者并由外科医生进行术前计划。

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