Stenosis detection in coronary angiography images using deep learning models

The emergence of deep learning has caused its massive application to different fields in industry and research, among which is the clinical field, especially in those where the data is structured in the form of images or video. The present proposal intends to develop a coronary angiography image analysis system based on artificial intelligence. These images are radiocontrast X-ray images of the coronary arteries. The proposed system will be able to analyze these coronary angiography images of patients with no obstructive coronary lesions to detect and characterize smooth and irregular coronary arteries and predict the presence of cardiovascular events during follow-up. Deep learning convolutional artificial neural networks will support the algorithmic basis of the proposed system.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Deep learning for coronary artery disease severity classification

Medical imaging evaluations are one of the fields where computed-aid diagnosis could improve the efficiency of diagnosis supporting physician decisions. Cardiovascular Artery Disease (CAD) is diagnosed using the gold standard, Invasive Coronary Angiography (ICA). In this work, performance analysis for binary classification of ICA images considering the severity ranges separately is reported, evaluating how performance is affected depending on the degree of lesions considered. For this purpose, an annotated dataset of ICA images was employed, which contains the ground truth, the location and the category of lesions into seven possible ranges: <20 %, [20 %, 49 %], [50 %, 69 %], [70 %, 89 %], [90 %, 98 %], 99 %, and 100 %. The ICA images were pre-processed, divided into patches and balanced by downsampling and data augmentation. In this study, four known pre-trained CNN architectures were trained using different categories of lesion degree as input, whose F-measures are computed. Results report that the F-measures showed a behavior dependent on the narrow presents of the image, being lesions with more than 50 % severity were better classified, achieving an F-measure of 75%.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Innovations that empower teachers: the case of i-Spring to design tailor-made learning materials.

Organizations must acknowledge the necessity of change and adopt diverse management strategies to swiftly adapt to the evolving technology and the new knowledge landscape. In the context of educational changes, an increasing value is placed nowadays on identifying renewed and effective approaches to teaching as the safest way to bring about not just students’ learning but growth, development and/or evolution. The strengthened emphasis on innovation as key to progress in today’s world has resulted in a widespread encouragement for teachers to pursue innovative initiatives that, in turn, will empower them. So, innovation practices will help those teaching practitioners who implement them to become increasingly empowered, and teacher empowerment is an essential tool for carrying out educational innovations. Notwithstanding this, each innovation, whatever the generation it belongs to, requires new knowledge, understanding, and skills and can therefore be perceived as demanding or even a bit intimidating, particularly technology-based ones.Plan Propio Integral de Docencia de la Universidad de Málaga. Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech