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Challenges of medical image processing

机译:医学图像处理的挑战

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In todays health care, imaging plays an important role throughout the entire clinical process from diagnostics and treatment planning to surgical procedures and follow up studies. Since most imaging modalities have gone directly digital, with continually increasing resolution, medical image processing has to face the challenges arising from large data volumes. In this paper, we discuss Kilo- to Terabyte challenges regarding (ⅰ) medical image management and image data mining, (ⅱ) bioimaging, (ⅲ) virtual reality in medical visualizations and (ⅳ) neuroimaging. Due to the increasing amount of data, image processing and visualization algorithms have to be adjusted. Scalable algorithms and advanced parallelization techniques using graphical processing units have been developed. They are summarized in this paper. While such techniques are coping with the Kilo- to Terabyte challenge, the Petabyte level is already looming on the horizon. For this reason, medical image processing remains a vital field of research.
机译:在当今的医疗保健中,从诊断和治疗计划到手术程序和后续研究,成像在整个临床过程中都起着重要作用。由于大多数成像方式已经直接数字化,并且分辨率不断提高,因此医学图像处理必须面对大数据量所带来的挑战。在本文中,我们讨论了千字节到TB的挑战,涉及(ⅰ)医学图像管理和图像数据挖掘,(ⅱ)生物成像,(ⅲ)医学可视化中的虚拟现实和(ⅳ)神经成像。由于数据量的增加,必须调整图像处理和可视化算法。已经开发了使用图形处理单元的可扩展算法和高级并行化技术。它们在本文中进行了总结。尽管此类技术可以应对千字节级至TB级的挑战,但是PB级已经迫在眉睫。因此,医学图像处理仍然是重要的研究领域。

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