3D reconstruction of the heart
Cardiovascular disease is the leading cause of mortality worldwide, accounting for 30% of all deaths and about 17 million premature deaths annually. However, these figures are decreasing due to increased awareness, healthier lifestyle and cardiac examinations which can prevent deterioration and ...
Read MoreCoronary CT Angiography with Deep Learning
Coronary artery pathologies are a leading cause of heart failure and death in the western world. Narrowing and hardening of the vessels carrying oxygen-rich blood to the heart, due to the accumulation of plaque on the vascular walls, is a major source of atherosclerosis, a major cardiovascular di...
Read MoreStabilization in fluorescein angiography
One of the most common tests in ophthalmology is fluorescein angiography: fluorescein is injected in the blood and it moves immediately through the blood vessels to the back of the eye. Some drops might also be applied in order to make the pupil dilate. A video clip taken shortly after that, show...
Read MoreVessel Segmentation Using Deep Learning
Using Deep Neural Networks for Vessel Segmentation in Fundus Images Vessel segmentation methods based on image processing techniques have long been utilized to delineate the vascular tree in clinical imaging. Many vessel segmentation algorithms exist and have been widely demonstrated in o...
Read MoreQuantitative Coronary Analysis
Quantitative Coronary Analysis Quantitative Coronary Analysis (QCA) refers to the set of methods used to measure the diameter of arteries. The set of tools and algorithms for QCA have been developed for the purpose of lesion and stenosis detection and analysis, and promote rational clinical decis...
Read MoreCoronary CT Angiography
RSIP Vision created coronary CT angiography software which automatically tracks arteries, locating blockages without the need for cardiac catheterization.
Read More3D Reconstruction of the Heart
RSIP Vision builds accurate 3D reconstructions of the heart increasing efficiency of therapy and lowering patient risk.
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