ROP: Retinopathy of Prematurity
Retinopathy of prematurity (ROP) is a leading cause of blindness in infants. ROP (or Terry syndrome) is a disease of the eye affecting prematurely-born, low
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Eyelid Drooping – Blepharoptosis
Blepharoptosis, also known as ptosis, is a drooping of the upper eyelid causing a narrowing of the palpebral fissure (or palpebral aperture), which is the
CT Segmentation in orthopedic surgery
CT image segmentation is a typical phase of orthopedic surgeries in which a visualization system is called to visually support the surgeon’s task. This system
Retinal Detachment Detection
Retinal detachment occurs when part of the retina detaches itself from the pigmented cell layer of the RPE, depriving itself of blood and nutrition: this
Geographic Atrophy (GA)
Geographic Atrophy (generally called GA) is a case of advanced Dry AMD (Age-related Macular Degeneration) which might lead to vision loss. As a consequence of
Automatic semantic tagging of images
Sites containing huge amounts of content must necessarily recommend only a narrow and relevant list to users. Recommender systems can be seen as tool to automatically generate personalized search preferences, with the purpose of keeping the balance between monetized targeted suggestions and satisfactory user experience. Automatic semantic tagging helps them do just this.
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Cardiac Left Ventricle Segmentation
Cardiac MRI is used to assess the status of patients suffering from heart diseases like cardiac masses and thrombi, aortic and/or different kinds of congenital cardiac diseases. Cardiac MRI is minimally invasive, does not involve radiation and it generally delivers excellent images for diagnostics. However, automatic segmentation of the left ventricle on MRI images faces challenging difficulties, like locating the left ventricle and overcoming the lack of edge information. We propose a method providing a very robust input for daily clinical application.
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Live cells tracking
Manual cell inspection is limited to tracking a relatively small number of cells in short periods of time and it is prone to human errors. On the other hand, computer vision algorithms can be used to perform fast scanning, segmentation and tracking of large cell populations over long periods of time. Taking advantage of our experience in segmentation, microscopy and machine learning, this procedure helps saving both labor and time, hence enabling more timely diagnostic and therapy.
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