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Image Retake Analysis in Digital Radiography Using DICOM Header Information

机译:使用DICOM标头信息的数字射线照相中的图像重摄取分析

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摘要

A methodology to automatically detect potential retakes in digital imaging, using the Digital Imaging and Communications in Medicine (DICOM) header information, is presented. In our hospital, neither the computed radiography workstations nor the picture archiving and communication system itself are designed to support reject analysis. A system called QCOnline, initially developed to help in the management of images and patient doses in a digital radiology department, has been used to identify those images with the same patient identification number, same modality, description, projection, date, cassette orientation, and image comments. The pilot experience lead to 6.6% and 1.9% repetition rates for abdomen and chest images. A thorough analysis has shown that the real repetitions were 3.3% and 0.9% for abdomen and chest images being the main cause of the discrepancy being the wrong image identification. The presented methodology to automatically detect potential retakes in digital imaging using DICOM header information is feasible and allows to detect deficiencies in the department performance like wrong identifications, positioning errors, wrong radiographic technique, bad image processing, equipment malfunctions, artefacts, etc. In addition, retake images automatically collected can be used for continuous training of the staff.
机译:提出了一种方法,该方法使用医学数字成像和通信(DICOM)标头信息自动检测数字成像中的潜在再摄取量。在我们医院,既没有计算机射线照相工作站,也没有设计图像存档和通信系统来支持次品分析。最初开发的名为QCOnline的系统用于在数字放射科中帮助管理图像和患者剂量,现已用于识别具有相同患者识别号,相同方式,描述,投影,日期,暗盒方向和图片评论。飞行员的经验导致腹部和胸部图像的重复率分别为6.6%和1.9%。彻底的分析表明,腹部和胸部图像的真实重复率分别为3.3%和0.9%,这是导致差异的主要原因是图像识别错误。所提出的使用DICOM标头信息自动检测数字成像中潜在重现的方法是可行的,并且可以检测部门性能方面的缺陷,例如错误的标识,定位错误,射线照相技术错误,图像处理不良,设备故障,伪影等。 ,自动收集的重拍图像可用于员工的持续培训。

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