| Literature DB >> 30834638 |
Vibujithan Vigneshwaran1,2, Gregory B Sands1, Ian J LeGrice3, Bruce H Smaill1, Nicolas P Smith1,2.
Abstract
Building anatomically accurate models of the coronary vascular system enables potentially deeper understandings of coronary circulation. To achieve this, (a) images at different levels of vascular network-arteries, arterioles, capillaries, venules, and veins-need to be obtained through suitable imaging modalities; and (b) from images, morphological and topological information needs to be extracted using image processing techniques. While there are several modalities that enable the imaging of large vessels, microcirculation imaging-capturing vessels having diameter lesser than 100 μm-has to date been typically confined to small regions of the heart. This spatially limited microcirculatory information has often been used within cardiac models, with the potentially erroneous assumption that it is representative of the whole organ. However, with the recent advancements in imaging and image processing, it is rapidly becoming feasible to acquire, process, and quantify microcirculation data at the scale of whole organ. In this review, we summarize the progress toward this goal followed through a presentation of the current state-of-the-art imaging and image processing techniques in the context of coronary microcirculation extraction, prominently but not exclusively, from small animals.Keywords: confocal imaging; coronary vascular system; deep learning; image processing; vessel extraction
Mesh:
Year: 2019 PMID: 30834638 DOI: 10.1111/micc.12542
Source DB: PubMed Journal: Microcirculation ISSN: 1073-9688 Impact factor: 2.628