Search results for " Vision"
showing 10 items of 2709 documents
Altered EEG Oscillatory Brain Networks During Music-Listening in Major Depression
2021
To examine the electrophysiological underpinnings of the functional networks involved in music listening, previous approaches based on spatial independent component analysis (ICA) have recently been used to ongoing electroencephalography (EEG) and magnetoencephalography (MEG). However, those studies focused on healthy subjects, and failed to examine the group-level comparisons during music listening. Here, we combined group-level spatial Fourier ICA with acoustic feature extraction, to enable group comparisons in frequency-specific brain networks of musical feature processing. It was then applied to healthy subjects and subjects with major depressive disorder (MDD). The music-induced oscil…
E-Fairs: a Cyber-Physical System for Aggregation and Economy of Scale in e-Commerce
2018
In recent years, the e-commerce arena has deeply changed because of the advent of new business models and the growing weight of huge global actors like Amazon. Some business models create competition between users, and the product price tends to rise (e.g., online auctions); other models, including group-buying, make users cooperate, and the price tends to go down. The present study extends the group-buying model and proposes a cyber-physical system called e-fair, in which both sellers and buyers are grouped to negotiate on a specific product or service. E-fairs minimize the global purchase price and the shipping resources respectively with the aggregation of demand and supply as well as or…
Behavioural thresholds of blue tit colour vision and the effect of background chromatic complexity
2020
Vision is a vital attribute to foraging, navigation, mate selection and social signalling in animals, which often have a very different colour perception in comparison to humans. For understanding how animal colour perception works, vision models provide the smallest colour difference that animals of a given species are assumed to detect. To determine the just-noticeable-difference, or JND, vision models use Weber fractions that set discrimination thresholds of a stimulus compared to its background. However, although vision models are widely used, they rely on assumptions of Weber fractions since the exact fractions are unknown for most species. Here, we test; i) which Weber fractions in lo…
Automated approach for indirect immunofluorescence images classification based on unsupervised clustering method
2018
Autoimmune diseases (ADs) are a collection of many complex disorders of unknown aetiology resulting in immune responses to self-antigens and are thought to result from interactions between genetic and environmental factors. ADs collectively are amongst the most prevalent diseases in the U.S., affecting at least 7% of the population. The diagnosis of ADs is very complex, the standard screening methods provides seeking and recognizing of Antinuclear Antibodies (ANA) by Indirect ImmunoFluorescence (IIF) based on HEp-2 cells. In this paper an automatic system able to identify and classify the Centromere pattern is presented. The method is based on the grouping of centromeres present on the cell…
Data from: An aposematic colour-polymorphic moth seen through the eyes of conspecifics and predators - sensitivity and colour discrimination in a tig…
2019
1. Although predation is commonly thought to exert the strongest selective pressure on colouration in aposematic species, sexual selection may also influence colouration. Specifically, polymorphism in aposematic species cannot be explained by natural selection alone. 2. Males of the aposematic wood tiger moth (Arctia plantaginis) are polymorphic for hindwing colouration throughout most of their range. In Scandinavia, they display either white or yellow hindwings. Female hindwing colouration varies continuously from bright orange to red. Redder females and yellow males suffer least from bird predation. 3. White males often have higher mating success than yellow males. Therefore, we ask wheth…
Artificial Neural Network Based Abdominal Organ Segmentations: A Review
2015
There are many neural network based abdominal organ segmentation approaches from medical images. Computed tomography images were mostly used in these approaches. Applied techniques are usually based on prior information regarding position, shape, and size of organs in these methods. In the literature, there are only a few neural network based techniques that were implemented to segment abdominal organs from magnetic resonance based images. In this paper, we present these methods and their results.
Comparative assessment of brain activity during depth perception of stereoscopic and volumetric images
2020
Recent advancements in visualization systems have triggered a growing demand for the objective and accurate comparison of user cognitive requirements when perceiving three-dimensional images demonstrated in different ways. In this work, we present the first comparative assessment of brain activity in subjects viewing stereoscopic images and volumetric images. Electroencephalography was employed to assess the short-term changes in event related potentials and neural oscillations which were further interpreted in terms of cognitive requirements for relative depth judgments. As a result, considerably higher activity have been registered in the beta band and gamma band in case of judging relati…
Segmentation of Positron Emission Tomography Images Using Multi-atlas Anatomical Magnetic Resonance Imaging (MRI)
2021
Positron emission tomography (PET), is a medical imaging technique, it provides information about the body’s cellular function rather than its anatomy. However, due to the functional nature of PET images, locating the anatomical structures in such an image remains a challenging task, indeed, PET images only provide very little anatomical information. Segmentation of PET images, therefore, requires the intervention of a medical expert. The expert proceeds to a manual segmentation of a volume slice by slice, which turns out to be very tedious and costly in terms of time. In this article, we present, evaluate, and make available a multi-atlas approach for automatically segmenting human brain P…
Exploring Frequency-dependent Brain Networks from ongoing EEG using Spatial ICA during music listening
2019
AbstractRecently, exploring brain activity based on functional networks during naturalistic stimuli especially music and video represents an attractive challenge because of the low signal-to-noise ratio in collected brain data. Although most efforts focusing on exploring the listening brain have been made through functional magnetic resonance imaging (fMRI), sensor-level electro- or magnetoencephalography (EEG/MEG) technique, little is known about how neural rhythms are involved in the brain network activity under naturalistic stimuli. This study exploited cortical oscillations through analysis of ongoing EEG and musical feature during free-listening to music. We used a data-driven method t…
Hybrid segmentation and virtual bronchoscopy based on CT images1
2004
Rationale and objectives Introduction of combination of the segmentation tool SegoMeTex and the virtual endoscopy system VIVENDI to perform virtual endoscopic inspections of the human lung. This virtual bronchoscopy system enables visualization of the tracheobronchial tree down to seventh generation. Furthermore, the modified virtual system visualizes hidden structures such as segmented vascular system or tumors. Materials and methods The segmentation is based on image data acquired by a multislice computed tomography scanner. SegoMeTex is used to segment the tracheobronchial tree by a hybrid system with minimal user action. Similarly, the complementary pulmonary arterial can be segmented, …