基于数字化可视人的医学图像融合研究

Research of medical image fusion based on data set of digital visible human

目的为数字化可视人体数据应用于临床影像设备提供完整的技术方案和程序代码。方法通过数字化可视人体分割数据与标准DICOM3.0数据格式的转换,对中国可视化人的彩色分割图像与CT图像进行融合。结果建立了一套符合临床放射治疗系统数据要求的标准DICOM3.0中国可视化人体数据源女性盆腔数据。结论为妇科肿瘤放射治疗过程中靶区勾画、治疗方案优化和剂量评估提供了具有重要器官分割特性的数字模拟计算模型,有助于数字化可视人体数据的临床推广应用。

Objective To provide integrated technical project and process code parameter for clinical application of data set of digital visible human. Methods The pelvic cavity structures of Chinese Virtual Human （CVH） data set were segmented using image transparency method and each image was smoothed by eroding and dilating, then fused successfully with CT of the same sample. Results The CVH color cross-sectional images of female pelvic cavity were transformed to DICOM 3.0 images with Amira 4.1 and Matlab software. A data set of female pelvic DICOM files from CVH was set up to apply in radiation therapy system. Conclusion The digital model of female pelvic cavity with important organs segmented can well reflect the exposure doses of patients, so it is of important value to get target therapy areas, forecast radiotherapy side effects, optimize radiotherapy plan and improve curative effect. It can help to promote clinical application of digital visible human.