Hyperspectral imaging techniques (HSI) do not require contact with patients and are non-ionizing as well as non-invasive. As a consequence, they have been extensively applied in the medical field. HSI is being combined with machine learning (ML) processes to obtain models to assist in diagnosis. In particular, the combination of these techniques has proven to be a reliable aid in the differentiation of healthy and tumor tissue during brain tumor surgery. ML algorithms such as support vector machine (SVM), random forest (RF) and convolutional neural networks (CNN) are used to make predictions and provide in-vivo visualizations that may assist neurosurgeons in being more precise, hence reducing damages to healthy tissue. In this work, thirteen in-vivo hyperspectral images from twelve different patients with high-grade gliomas (grade III and IV) have been selected to train SVM, RF and CNN classifiers. Five different classes have been defined during the experiments: healthy tissue, tumor, venous blood vessel, arterial blood vessel and dura mater. Overall accuracy (OACC) results vary from 60% to 95% depending on the training conditions. Finally, as far as the contribution of each band to the OACC is concerned, the results obtained in this work are 3.81 times greater than those reported in the literature.
High Efficiency Video Coding (HEVC) is a new video coding standard created by the JCT-VC group within ISO/IEC and ITU-T. HEVC is targeted to provide the same quality as H.264 at about half of the bit-rate and will replace soon to its predecessor in multimedia consumer applications. Up to now, only a few decoder implementations have been reported, most of them oriented to carry out a complexity analysis. In this paper, a DSP-based implementation of the HEVC HM9.0 decoder is presented. Up to the best of our knowledge, it is the first DSP-based implementation shown in the scientific literature. Several tests have been carried out to measure the decoder performance and the computational load distribution among its functional blocks. These results have been compared with the ones obtained with the decoder implementations reported up to date. Finally, based on the results obtained in previous works regarding software optimization of DSP-based decoders, realtime could be achieved for SD formats with a single DSP after optimizing our HEVC decoder. For HD formats, multi-DSP technology will be needed. 1
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