Search results for "computer.software_genre"
showing 10 items of 3858 documents
Adaptive frequency decomposition of EEG with subsequent expert system analysis.
2001
We present a hybrid system for automatic analysis of clinical routine EEG, comprising a spectral analysis and an expert system. EEG raw data are transformed into the time-frequency domain by the so-called adaptive frequency decomposition. The resulting frequency components are converted into pseudo-linguistic facts via fuzzification. Finally, an expert system applies symbolic rules formulated by the neurologist to evaluate the extracted EEG features. The system detects artefacts, describes alpha rhythm by frequency, amplitude, and stability and after artefact rejection detects pathologic slow activity. All results are displayed as linguistic terms, numerical values and maps of temporal exte…
Effectance and control as determinants of video game enjoyment
2007
This article explores video game enjoyment originated by games' key characteristic, interactivity. An online experiment (N = 500) tested experiences of effectance (perceived influence on the game world) and of being in control as mechanisms that link interactivity to enjoyment. A video game was manipulated to either allow normal play, reduce perceived effectance, or reduce perceived control. Enjoyment ratings suggest that effectance is an important factor in video game enjoyment but that the relationship between control of the game situation and enjoyment is more complex. © 2007 Mary Ann Liebert, Inc.
A finite element-based machine learning approach for modeling the mechanical behavior of the breast tissues under compression in real-time
2017
[EN] This work presents a data-driven method to simulate, in real-time, the biomechanical behavior of the breast tissues in some image-guided interventions such as biopsies or radiotherapy dose delivery as well as to speed up multimodal registration algorithms. Ten real breasts were used for this work. Their deformation due to the displacement of two compression plates was simulated off-line using the finite element (FE) method. Three machine learning models were trained with the data from those simulations. Then, they were used to predict in real-time the deformation of the breast tissues during the compression. The models were a decision tree and two tree-based ensemble methods (extremely…
Dynamic image denoising for voxel-wise quantification with Statistical Parametric Mapping in molecular neuroimaging.
2018
Purpose PET and SPECT voxel kinetics are highly noised. To our knowledge, no study has determined the effect of denoising on the ability to detect differences in binding at the voxel level using Statistical Parametric Mapping (SPM). Methods In the present study, groups of subject-images with a 10%- and 20%- difference in binding of [123I]iomazenil (IMZ) were simulated. They were denoised with Factor Analysis (FA). Parametric images of binding potential (BPND) were produced with the simplified reference tissue model (SRTM) and the Logan non-invasive graphical analysis (LNIGA) and analyzed using SPM to detect group differences. FA was also applied to [123I]IMZ and [11C]flumazenil (FMZ) clinic…
MAGIC-5: an Italian mammographic database of digitised images for research
2008
The implementation of a database of digitised mammograms is discussed. The digitised images were collected beginning in 1999 by a community of physicists in collaboration with radiologists in several Italian hospitals as a first step in developing and implementing a computer-aided detection (CAD) system. All 3,369 mammograms were collected from 967 patients and classified according to lesion type and morphology, breast tissue and pathology type. A dedicated graphical user interface was developed to visualise and process mammograms to support the medical diagnosis directly on a high-resolution screen. The database has been the starting point for developing other medical imaging applications,…
A deep learning framework for automatic diagnosis of unipolar depression.
2019
Abstract Background and purpose In recent years, the development of machine learning (ML) frameworks for automatic diagnosis of unipolar depression has escalated to a next level of deep learning frameworks. However, this idea needs further validation. Therefore, this paper has proposed an electroencephalographic (EEG)-based deep learning framework that automatically discriminated depressed and healthy controls and provided the diagnosis. Basic procedures In this paper, two different deep learning architectures were proposed that utilized one dimensional convolutional neural network (1DCNN) and 1DCNN with long short-term memory (LSTM) architecture. The proposed deep learning architectures au…
Electrochemotherapy in the treatment of cutaneous malignancy: Outcomes and subgroup analysis from the cumulative results from the pan-European Intern…
2020
Electrochemotherapy (ECT) is a treatment for both primary and secondary cutaneous tumours. The international Network for sharing practices on ECT group investigates treatment outcomes after ECT using a common database with defined parameters.Twenty-eight centres across Europe prospectively uploaded data over an 11-year period. Response rates were investigated in relation to primary diagnosis, tumour size, choice of electrode type, route of bleomycin administration, electrical parameters recorded and previous irradiation in the treated field.Nine hundred eighty-seven patients, with 2482 tumour lesions were included in analysis. The overall response (OR) rate was 85% (complete response [CR]: …
Similarities and differences between eating disorders and obese patients in a virtual environment for normalizing eating patterns.
2016
Virtual reality has demonstrated promising results in the treatment of eating disorders (ED); however, few studies have examined its usefulness in treating obesity. The aim of this study was to compare ED and obese patients on their reality judgment of a virtual environment (VE) designed to normalize their eating pattern. A second objective was to study which variables predicted the reality of the experience of eating a virtual forbidden-fattening food. ED patients, obese patients, and a non-clinical group (N = 62) experienced a non-immersive VE, and then completed reality judgment and presence measures. All participants rated the VE with similar scores for quality, interaction, engagement,…
The shape of personal space.
2019
The notion of a personal space surrounding one's ego-center is time-honored. However, few attempts have been made to measure the shape of this space. With increasing use of virtual environments, the question has arisen if real-world aspects, such as gender-effects or the shape of personal space, translate to virtual setups. We conducted two experiments, one with real people matched according to body height and level of acquaintance in a large laboratory setting, and one where subjects faced a virtual character, likewise matched to their body height. The first experiment also used a mannequin in place of the second human observer. The second experiment additionally manipulated the perspectiv…
A new set of 299 pictures for psycholinguistic studies : French norms for name agreement, image agreement, conceptual familiarity, visual complexity,…
2003
Pictures are often used as stimuli in studies of perception, language, and memory. Since performances on different sets of pictures are generally contrasted, stimulus selection requires the use of standardized material to match pictures across different variables. Unfortunately, the number of standardized pictures available for empirical research is rather limited. The aim of the present study is to provide French normative data for a new set of 299 black-and-white drawings. Alario and Ferrand (1999) were closely followed in that the pictures were standardized on six variables: name agreement, image agreement, conceptual familiarity, visual complexity, image variability, and age of acquisit…