Virtual poster abstracts Results: 16/25 (64.0%) of the gynecologists were IOTA-certified. The IOTA template was used in 83/90 (92.2%) cases. 58/83 (69.9%) descriptions used IOTA terms correctly with adequate information. Conflicting use of IOTA terms were seen in 15/83 (18.1%) cases; with misclassification of uni-/multilocular lesions with solid components being the most frequent pitfall. 10/83 (12.0%) contained inadequate measures only. All 7/90 (7.8%) cases not using the IOTA template lacked information on morphology, colour score, and measures. 39/90 (43.3%) images did not document the findings described (colour score (n = 18) and lesion measures (n = 15) mostly missing). In 25/90 (27.8%) patients, the two external reviewers disagreed with the examinating gynecologist on lesion classification (n = 11), cystic content (n = 8), regularity (n = 11), and shadowing (n = 3). There was no significant association between IOTA-certification status and disagreement by reviewers (22.7% in IOTA-certified vs. 29.2% in non-certified, p = 0.193). Conclusions: Essential pitfalls in using the IOTA terms and definitions were relatively frequent, despite IOTA certification. To perform optimal evaluation and implementation of the IOTA diagnostic tools, methods to maintain IOTA competencies must be developed. VP61.05 Efficient and customised use of IOTA ADNEX model as a clinical management tool in a tailor-made treatment of adnexal tumour suspected of malignancy
Image super-resolution (SR) is a process that enhances the resolution of an image or a set of images beyond the resolution of the imaging sensor. Although there are several superresolution methods, fusion super-resolution techniques are well suited for real-time implementations. In fusion super-resolution, the high-resolution images are reconstructed using different low-resolution-observed images, thereby increasing the high-frequency information and decreasing the degradation caused by the low-resolution sampling process. In terms of color reconstruction, standard reconstruction algorithms usually perform a bilinear interpolation of each color. This reconstruction performs a strong low-pass filtering, removing most of the aliasing present in the luminance signal. In this chapter, a novel way of color reconstruction is presented by using super-resolution in order to reconstruct the missing colors.
Educational robotics has come to the classrooms and is here to stay. STEAM (Science, Technology, Engineering, Arts and Mathematics) learning has put the use of robots in classrooms in vogue, though these are mostly closed products and at a high price. The educational innovation project “Design, implementation and tests of a modular low-cost educational robotics platform” from the University of Las Palmas de Gran Canaria, expects to design an open, modular and low-cost educational robot to make robotics more accessible. One of the challenges which the project hopes to accomplish is for this robot to be able to adapt to any educational level, thanks to its modularity, from pre-school to university levels. This study analyzes the Industrial Design and Product Development Engineering degree students’ level of acceptance. Therefore, an analysis of the currently most used educational robots at any level has been made, comparing them to the project design. Moreover, a survey was passed to a total 78 students from several degrees to compare the level of acceptance, concluding that students show a general interest in the proposal, but not so among those of the study group, probably due to the lack of robotics knowledge.
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