Abstract
Cardiac health is a big concern, worldwide, with cardiovascular disease (CVD) being the most predominant cause of death, making early diagnosis a top priority in public health. The technology supporting the diagnosis of CVD, e.g., cardiac computerized tomography angiography (CTA), has been evolving at a fast pace providing a wide range of data on the anatomy and function of the heart. When developing novel processing and analysis methods to tackle this data, one important challenge concerns how to make them available for clinicians to test. The aim would be to enable full exploration of these methods in the clinical workflow, i.e., supporting all the standard image visualization and analysis features provided by clinical workstations, from early on, to foster insight over their features and usefulness to inform development. Additionally, with the advances of technology, mobile devices, beyond the traditional workstations, have gained importance, e.g., during consultation. However, they have limited processing resources. In this regard, this work explores a modular multiplatform solution to support the early deployment of cardiac analysis methods to the clinician’s office. To this effect, we define the requirements for such a platform and present a first instance of its development exploring the Open Health Imaging Foundation resources. At its current stage, we demonstrate the feasibility of the approach and the integration of simple image processing modules in the pipeline.
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Notes
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OpenCV: https://opencv.org/.
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ITK: https://itk.org/.
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MevisLab: https://www.mevislab.de/.
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PostDICOM: https://www.postdicom.com/.
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Horos: https://horosproject.org/.
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Mango: https://ric.uthscsa.edu/mango/.
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Dicom Web Viewer: https://ivmartel.github.io/dwv/.
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Cornerstone.js: https://www.cornerstonejs.org/.
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Acknowledgements
This research is supported by National Funds, through FCT, in the scope of project CAD-FACTS (PTDC/EMD-EMD/0980/2020) and by IEETA - Institute of Electronics and Informatics Engineering of Aveiro Research Unit funding (UIDB/00127/2020).
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Abrantes, J., Almeida, N., Silva, S. (2023). Exploring a Modular Approach for Deploying and Testing Cardiac Image Processing and Analysis Methods in the Clinical Workflow. In: Cunha, A., M. Garcia, N., Marx Gómez, J., Pereira, S. (eds) Wireless Mobile Communication and Healthcare. MobiHealth 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 484. Springer, Cham. https://doi.org/10.1007/978-3-031-32029-3_22
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