Razeghi Orod, Solís-Lemus José Alonso, Lee Angela W C, Karim Rashed, Corrado Cesare, Roney Caroline H, de Vecchi Adelaide, Niederer Steven A
King's College London, London, United Kingdom.
SoftwareX. 2020 Jul 31;12:100570. doi: 10.1016/j.softx.2020.100570. eCollection 2020 Jul-Dec.
Personalised medicine is based on the principle that each body is unique and will respond to therapies differently. In cardiology, characterising patient specific cardiovascular properties would help in personalising care. One promising approach for characterising these properties relies on performing computational analysis of multimodal imaging data. An interactive cardiac imaging environment, which can seamlessly render, manipulate, derive calculations, and otherwise prototype research activities, is therefore sought-after. We developed the Cardiac Electro-Mechanics Research Group Application (CemrgApp) as a platform with custom image processing and computer vision toolkits for applying statistical, machine learning and simulation approaches to study physiology, pathology, diagnosis and treatment of the cardiovascular system. CemrgApp provides an integrated environment, where cardiac data visualisation and workflow prototyping are presented through a common graphical user interface.
个性化医疗基于这样一个原则,即每个人的身体都是独特的,对治疗的反应也会不同。在心脏病学中,描述患者特定的心血管特性将有助于实现个性化护理。一种用于描述这些特性的有前景的方法依赖于对多模态成像数据进行计算分析。因此,人们寻求一种交互式心脏成像环境,它能够无缝地呈现、操作、进行计算,并以其他方式进行研究活动的原型设计。我们开发了心脏电机械研究组应用程序(CemrgApp)作为一个平台,它带有定制的图像处理和计算机视觉工具包,用于应用统计、机器学习和模拟方法来研究心血管系统的生理学、病理学、诊断和治疗。CemrgApp提供了一个集成环境,通过一个通用的图形用户界面来呈现心脏数据可视化和工作流程原型设计。