Medical imaging also establishes a database of normal anatomy and physiology to make it possible to identify abnormalities. Medical imaging is often perceived to designate the set of techniques that noninvasively produce images of the internal aspect of the body.In this limited sense, medicinal ...
diabetic retinopathy; diabetic macular edema; medical imaging; deep learning; retinal images1. Introduction Diabetes is a disorder in which the glucose level of patients is higher than the normal level. Diabetes victims are at risk of various eye diseases, such as diabetic retinopathy (DR), ...
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The average age of the cohort is 65.2 years, with the majority being male (69%). The data also reveals a high prevalence of cardiovascular risk factors, such as diabetes (38%), hypertension (63%), and chronic kidney disease (23%). Table 2 Descriptive characteristics of the dataset used ...
The Region of Interest (ROI) extraction is applied to both the training and testing dataset. The final recognition result is obtained from the ensemble of the different probabilities (P) of five different CNNs. 4.1.1. Datasets The utilized dataset was released in the medical imaging challenge,...
She works on other clinical trials in collaboration with other institutes within NIH such as the Actions to Control Cardiovascular Risk in Diabetes (ACCORD) Trial and she chairs the ACCORD Eye Study. She directs the clinical portion of the international study, Macular Telangiectasia Project....
Positron Emission Tomography (PET) is a Nuclear Medicine technique with a wide range of applications, particularly on Oncology. The imminent clinical introduction of Long Axial Field-of-View (LAFOV) scanners has raised the interest of the community, due to its enhanced sensitivity and lower doses...
Thus, the repeated image acquisition for eye abnormality-associate-poor-quality leads to a waste of time, manpower, and medical resource. For the second option, even though researchers have successfully investigated and developed artificial methods to eliminate artefacts, they found that images with ...
Data extraction and visualization of 3D medical images of ocular blood vessels are performed by geometric transformation algorithm, which first performs random resonance response in a global sense to achieve detection of high-contrast coarse blood vessels and then redefines the input signal as a local...
Medical image segmentation Retinal images 1Introduction Several pathologies affecting the retinal vascular structures due to diabetic retinopathy can be found in retinal images. Blood vessel segmentation from retinal images plays a crucial role for diagnosing complications due to hypertension, diabetes, arteri...