LEARNING ENVIRONMENTS IN THE CONTEXT OF A MASTER DEGREE IN ANIMATION AND ILLUSTRATION

This paper aims to describe the processes of teaching illustration and animation, together, in the context of a masters degree program. In Portugal, until very recently, illustration and animation higher education courses, were very scarce and only provided by a few private universities, which offered separated programs - either illustration or animation. The MA in Illustration and Animation (MIA) based in the Instituto Politécnico do Cávado e Ave in Portugal, dared to join these two creative areas in a common learning model and is already starting it’s third edition with encouraging results and will be supported by the first international conference on illustration and animation (CONFIA). This masters program integrates several approaches and techniques (in illustration and animation) and integrates and encourages creative writing and critique writing. This paper describes the iterative process of construction, and implementation of the program as well as the results obtained on the initial years of existence in terms of pedagogic and learning conclusions. In summary, we aim to compare pedagogic models of animation or illustration teaching in higher education opposed to a more contemporary and multidisciplinary model approach that integrates the two - on an earlier stage - and allows them to be developed separately – on the second part of the program. This is based on the differences and specificities of animation (from classic techniques to 3D) and illustration (drawing the illustration) and the intersection area of these two subjects within the program structure focused on the students learning and competencies acquired to use in professional or authorial projects.

Improving The Robustness Of Interventional 4D Ultrasound Segmentation Through The Use Of Personalized Shape Priors

While fluoroscopy is still the most widely used imaging modality to guide cardiac interventions, the fusion of pre-operative Magnetic Resonance Imaging (MRI) with real-time intra-operative ultrasound (US) is rapidly gaining clinical acceptance as a viable, radiation-free alternative. In order to improve the detection of the left ventricular (LV) surface in 4D ultrasound, we propose to take advantage of the pre-operative MRI scans to extract a realistic geometrical model representing the patients cardiac anatomy. This could serve as prior information in the interventional setting, allowing to increase the accuracy of the anatomy extraction step in US data. We have made use of a real-time 3D segmentation framework used in the recent past to solve the LV segmentation problem in MR and US data independently and we take advantage of this common link to introduce the prior information as a soft penalty term in the ultrasound segmentation algorithm. We tested the proposed algorithm in a clinical dataset of 38 patients undergoing both MR and US scans. The introduction of the personalized shape prior improves the accuracy and robustness of the LV segmentation, as supported by the error reduction when compared to core lab manual segmentation of the same US sequences.