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An automatic quantification system for MS lesions with integrated DICOM structured reporting (DICOM-SR) for implementation within a clinical environment

机译:具有集成DICOM结构报告(DICOM-SR)的MS病变的自动量化系统,用于在临床环境中实现

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Multiple Sclerosis (MS) is a common neurological disease affecting the central nervous system characterized by pathologic changes including demyelination and axonal injury. MR imaging has become the most important tool to evaluate the disease progression of MS which is characterized by the occurrence of white matter lesions. Currently, radiologists evaluate and assess the multiple sclerosis lesions manually by estimating the lesion volume and amount of lesions. This process is extremely time-consuming and sensitive to intra- and inter-observer variability. Therefore, there is a need for automatic segmentation of the MS lesions followed by lesion quantification. We have developed a fully automatic segmentation algorithm to identify the MS lesions. The segmentation algorithm is accelerated by parallel computing using Graphics Processing Units (GPU) for practical implementation into a clinical environment. Subsequently, characterized quantification of the lesions is performed. The quantification results, which include lesion volume and amount of lesions, are stored in a structured report together with the lesion location in the brain to establish a standardized representation of the disease progression of the patient. The development of this structured report in collaboration with radiologists aims to facilitate outcome analysis and treatment assessment of the disease and will be standardized based on DICOM-SR. The results can be distributed to other DICOM-compliant clinical systems that support DICOM-SR such as PACS. In addition, the implementation of a fully automatic segmentation and quantification system together with a method for storing, distributing, and visualizing key imaging and informatics data in DICOM-SR for MS lesions improves the clinical workflow of radiologists and visualizations of the lesion segmentations and will provide 3-D insight into the distribution of lesions in the brain.
机译:多发性硬化症(MS)是一种常见的神经系统,影响中枢神经系统,其特征在于病理变化,包括脱髓鞘和轴突损伤。 MR成像已成为评估MS的疾病进展的最重要的工具,其特征在于白品病变的发生。目前,放射科医生通过估计病变量和病变量来评估和评估多发性硬化病变。该过程对内部和观察者和观察者间变异性极其耗时和敏感。因此,需要对MS病变的自动分割,然后是病变量化。我们开发了一种全自动分段算法来识别MS病变。通过使用图形处理单元(GPU)的并行计算来加速分割算法,以进行实际实现在临床环境中。随后,进行表征病变的量化。包含病变体积和病变量的定量结果,与大脑中的病变位置一起储存在结构化报告中,以建立患者疾病进展的标准化表示。与放射科医生合作的这种结构化报告的发展旨在促进对疾病的结果分析和治疗评估,并将基于DICOM-SR标准化。结果可以分配给支持DICOM-SR等DICOM-SR等DICOM-SR的临床系统。另外,将完全自动分割和量化系统的实现与用于存储,分发和可视化的方法,用于MS病变的DICOM-SR中的用于存储,分发和可视化和信息学数据,提高了病变分割的放射科学家和可视化的临床工作流程和遗嘱提供3D洞察大脑病变的分布。

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