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Application of Adaptive Threshold Image Segmentation Algorithm in Orthopedic CT Imaging

机译:自适应阈值图像分割算法在骨科CT成像中的应用

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Objective: To explore the application and analysis of image segmentation in the rehabilitation of patients with bone trauma during orthopedic nursing. Methods: Sixty patients with orthopedic trauma in our hospital were enrolled. The patients were divided into observation group and control group by four weeks. The control group was the traditional observation image, and the observation group was analyzed by image segmentation technology. Therefore, the two groups of patients are provided with nursing treatment, and finally, the progress of bone trauma recovery is periodically observed. Results: The degree of recovery in the observation group was 43% in the four-week period and 30% in the control group. It can be seen that the adaptive threshold algorithm makes orthopedic care more effective in image segmentation. Discussion: In medical imaging technology, different imaging devices can provide a variety of voxel information. The bone morphology information provided by CT images can make orthopedic care more targeted. Conclusion: Image segmentation technology provides a reliable predictive treatment solution in the nursing work, which solves the actual problem of the patient in the injury and the disease, so that the patient can recover faster. However, the expected research results of medical imaging technology research have guiding significance for the doctor's clinical diagnosis and preoperative and postoperative planning.
机译:目的:探讨骨科护理期间骨创伤患者康复的应用与分析。方法:注册了我们医院骨科创伤的六十名患者。将患者分为4周的观察组和对照组。对照组是传统的观察图像,通过图像分割技术分析观察组。因此,两组患者提供护理治疗,最后,定期观察到骨创伤恢复的进展。结果:观察组的回收程度在四周期间为43%,对照组30%。可以看出,自适应阈值算法使矫形护理在图像分割中更有效。讨论:在医学成像技术中,不同的成像装置可以提供各种体素信息。 CT图像提供的骨骼形态信息可以使矫形护理更多目标。结论:图像分割技术在护理工作中提供了可靠的预测处理解决方案,其解决了患者在损伤和疾病中的实际问题,使得患者可以更快地恢复。然而,医学成像技术研究的预期研究结果对医生的临床诊断和术前和术后规划具有指导意义。

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