Background Vascular surgeons face complex decisions regarding revascularization of lower limbs of patients, for which there is no decision support solution yet available. Objective …
Vascular surgeons take decisions on the revascularization technics when surgery is needed for patients with Lower Extremities Arterial Disease (LEAD). This decision requires …
Background and Objective: Automatic segmentation of myocardial infarction is of great clinical interest for the quantitative evaluation of myocardial infarction (MI). Late …
Accurately and robustly segmenting myocardial infarction (MI) is crucial for clinical diagnosis of cardiac diseases, treatment and planning. In this study, we propose a novel deep …
Objectives The development of computerized medical records (CMR) allows all healthcare professionals to gather the necessary information to manage a patient. However, while data …
How do you help a vascular surgeon choose the best revascularization strategy when a technique's success is hard to predict? A multidisciplinary clinical project that turns …
Classic Random Regression Forests (RRFs) used for multi-organ localization describe the random process of multivariate regression by storing the histograms of offset vectors along …
Co-supervision of Prasad Samarakoon's PhD (2016): lighter, more robust regression forests to automatically locate organs in CT images, within the LPR project. My first turn toward …
The article presents the use of an improved random regression forest method to localize multiple organs in Computed Tomography (CT) images. The method was trained using 50 CT …