This paper presents results from an experiment using electroencephalography to measure neurophysiological activations of mechanical engineers and industrial designers when designing and problem-solving. In this study, we adopted and then extended the tasks described in a previous functional magnetic resonance imaging study reported in the literature. The block experiment consists of a sequence of three tasks: problem-solving, basic design and open design using a physical interface. The block is preceded by a familiarizing pre-task and then extended to a fourth open design task using free-hand sketching. This paper presents the neurophysiological results from 36 experimental sessions of mechanical engineers and industrial designers. Results indicate significant differences in activations between the problem-solving and the open design tasks. The paper focuses on the two prototypical tasks of problem-solving layout and open design sketching and presents results for both aggregate and temporal activations across participants within each domain and across domains.

New tools from neuroscience allow design researchers to explore design neurocognition. By taking the advantage of EEG's temporal resolution we give up spatial resolution to focus on the performance of time-related design tasks. This paper presents results from an experiment using EEG to measure brain activation to study mechanical engineers and architects to compare their design neurocognition. In this study, we adopted and extended the tasks described in a previous fMRI study of design neurocognition reported in the literature. The block experiment consists of a sequence of 3 tasks: problem solving, basic design and open design using a physical interface. The block is preceded by a familiarizing pre-task using the physical interface and then extended to a fourth task using free-hand sketching. Brainwaves were collected from both mechanical engineers and architects. Results comparing 36 mechanical engineers and architects while designing were produced. These results indicate design cognition differences between the two domains in task-related power between the problem-solving task and the design tasks, in temporal resolution and transformed power.

This paper presents results from an experiment to determine brain activation differences between problem-solving and designing of mechanical engineers. The study is part of a research project whose goal is to correlate design cognition with brain behavior across design domains. The study adopted and extended the tasks described in a fMRI study of design cognition and measured brain activation using EEG. By taking the advantage of EEG’s temporal resolution we focus on time-related neural responses during problem-solving compared to design tasks. Statistical analyses indicate increased activation when designing compared to problem-solving. Results of time-related neural responses connected to Brodmann areas cognitive functions, contribute to a better understanding of mechanical engineers’ cognition in open design tasks.

Creativity is recognized as essential for changing the design space from constrained to open spaces. This study compares the neurophysiological activations of 18 professional industrial designers in two prototypical tasks, a problem-solving constrained layout task and an open design task. The analysis focused on measuring the cognitive demand in three stages of designing in constrained and open design spaces, namely: reading, problem-solving/reflection and layout/sketching. Results indicate significant differences in activations between the constrained task and the design task. Significant differences in activations involved in design reading, reflecting and sketching in open design tasks can be found in the left prefrontal cortex, temporal and occipital cortices. In particular, reading open or constrained requests evoked different levels of conceptual expansion prompting designers to change their design space, while reflecting evoked visual imagination and associative reasoning modes and hemispheric differences from problem-solving leading to expanded activation in sketching, which translates in higher activation in the open design task. These results show significantly different brain activations when designing in constrained and open design spaces.

We present results from an EEG experiment EEG to measure neurophysiological activation to study novice and experienced designers when designing and problem-solving. We adopted and extended the tasks described in a previous fMRI study. The block experiment consists of 3 tasks: problem-solving, basic design, and open layout design. The block is preceded by a familiarizing pre-task and extended to an open design sketching task. Results from 36 sessions of mechanical engineers and industrial designers indicate significant differences in activations between the problem-solving and the design tasks.

Early detection of liver cancer, whether from primary occurrence or from metastization is highly important to establish informed treatment decisions. Accurate delineation of the liver tissues of interest facilitates quantitative assessment of the regions of interest, treatment application, and prognosis. Segmentation of the liver in Computer Tomography (CT) images allows the extraction of the three-dimensional (3D) structure of the liver tissues in which the observation of their relative position to one another is particularly important in treatment scenarios of radiation therapy or interventional surgery planning. The adequate receptive field for the segmentation of such a big organ in CT images, from the remaining neighbouring organs was very successfully improved by the use of the state-of-the-art Convolutional Neural Networks (CNN) algorithms, however, certain issues still arise and are highly dependent of pre-or post-processing methods to refine the final segmentations. Here, the effects of Dilated Convolutional Networks is proposed, for the purpose of improving segmentation of liver tissues in CT. The introduction of a dilation module allowed the concatenation of feature maps with a richer contextual information. The hierarchical learning process given by different dilated convolutional layers is analysed quantitatively. Experiments on the MICCAI Lits challenge dataset are described achieving segmentations with a mean Dice coefficients of 95.57% and 59.36% for the liver and liver tumour, using a total number 30 CT test volumes.

Quantification of the anatomic and functional aspects of the tongue is pertinent to analyse the mechanisms involved in speech production. Speech requires dynamic and complex articulation of the vocal tract organs, and the tongue is one of the main articulators during speech production.Magnetic Resonance (MR) imaging has been widely used in speech related studies. Moreover, the segmentation of such images of speech organs is required to extract reliable statistical data.However, standards solutions to analyse a large set of articulatory images have not yet been established. Therefore, this article presents an approach to segment the tongue in 2D MR images and statistically model the segmented tongue shapes. The proposed approach assesses the articulator morphology based on an Active Shape Model, which captures the shape variability of the tongue during speech production. To validate this new approach, a dataset of mid-sagittal MR images acquired from four subjects was used, and key aspects of the shape of the tongue during the vocal production of relevant European Portuguese (EP) vowels were evaluated.

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