1000 resultados para localisation test


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Language deficits are frequently reported in studies of patients with schizophrenia. The present study sought to test the hypothesis that such deficits are related to callosal function in this group. The FAS test of verbal fluency and Perin's Spoonerisms test of phonological processing were the tests of language. Callosal function was assessed using a Crossed Finger Localisation Test (CFLT), which is a measure of the interhemispheric transfer of somatosensory information. Patients with schizophrenia performed less well than controls on measures of language function. as well as on the CFLT. Significant positive correlations between CFLT performance and language function were present in the patient group, but not the control group. These findings extend on previous studies that report functional abnormalities of the corpus callosum in schizophrenia and are consistent with the hypothesis that language deficits in schizophrenia are related to impaired callosal functioning in this group. However, other explanations cannot be ruled Out.

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Ambisonics is a scalable spatial audio technique that attempts to present a sound scene to listeners over as large an area as possi- ble. A localisation experiment was carried out to investigate the performance of a first and third order system at three listening positions - one in the centre and two off-centre. The test used a reverse target-pointer adjustment method to determine the error, both signed and absolute, for each combination of listening posi- tion and system. The signed error was used to indicate the direc- tion and magnitude of the shifts in panning angle introduced for the off-centre listening positions. The absolute error was used as a measure of the performance of the listening position and systems combinations for a comparison of their overall performance. A comparison was made between the degree of image shifting be- tween the two systems and the robustness of their off-centre per- formance.

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This paper describes the current state of RatSLAM, a Simultaneous Localisation and Mapping (SLAM) system based on models of the rodent hippocampus. RatSLAM uses a competitive attractor network to fuse visual and odometry information. Energy packets in the network represent pose hypotheses, which are updated by odometry and can be enhanced or inhibited by visual input. This paper shows the effectiveness of the system in real robot tests in unmodified indoor environments using a learning vision system. Results are shown for two test environments; a large corridor loop and the complete floor of an office building.

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Aims: To develop clinical protocols for acquiring PET images, performing CT-PET registration and tumour volume definition based on the PET image data, for radiotherapy for lung cancer patients and then to test these protocols with respect to levels of accuracy and reproducibility. Method: A phantom-based quality assurance study of the processes associated with using registered CT and PET scans for tumour volume definition was conducted to: (1) investigate image acquisition and manipulation techniques for registering and contouring CT and PET images in a radiotherapy treatment planning system, and (2) determine technology-based errors in the registration and contouring processes. The outcomes of the phantom image based quality assurance study were used to determine clinical protocols. Protocols were developed for (1) acquiring patient PET image data for incorporation into the 3DCRT process, particularly for ensuring that the patient is positioned in their treatment position; (2) CT-PET image registration techniques and (3) GTV definition using the PET image data. The developed clinical protocols were tested using retrospective clinical trials to assess levels of inter-user variability which may be attributed to the use of these protocols. A Siemens Somatom Open Sensation 20 slice CT scanner and a Philips Allegro stand-alone PET scanner were used to acquire the images for this research. The Philips Pinnacle3 treatment planning system was used to perform the image registration and contouring of the CT and PET images. Results: Both the attenuation-corrected and transmission images obtained from standard whole-body PET staging clinical scanning protocols were acquired and imported into the treatment planning system for the phantom-based quality assurance study. Protocols for manipulating the PET images in the treatment planning system, particularly for quantifying uptake in volumes of interest and window levels for accurate geometric visualisation were determined. The automatic registration algorithms were found to have sub-voxel levels of accuracy, with transmission scan-based CT-PET registration more accurate than emission scan-based registration of the phantom images. Respiration induced image artifacts were not found to influence registration accuracy while inadequate pre-registration over-lap of the CT and PET images was found to result in large registration errors. A threshold value based on a percentage of the maximum uptake within a volume of interest was found to accurately contour the different features of the phantom despite the lower spatial resolution of the PET images. Appropriate selection of the threshold value is dependant on target-to-background ratios and the presence of respiratory motion. The results from the phantom-based study were used to design, implement and test clinical CT-PET fusion protocols. The patient PET image acquisition protocols enabled patients to be successfully identified and positioned in their radiotherapy treatment position during the acquisition of their whole-body PET staging scan. While automatic registration techniques were found to reduce inter-user variation compared to manual techniques, there was no significant difference in the registration outcomes for transmission or emission scan-based registration of the patient images, using the protocol. Tumour volumes contoured on registered patient CT-PET images using the tested threshold values and viewing windows determined from the phantom study, demonstrated less inter-user variation for the primary tumour volume contours than those contoured using only the patient’s planning CT scans. Conclusions: The developed clinical protocols allow a patient’s whole-body PET staging scan to be incorporated, manipulated and quantified in the treatment planning process to improve the accuracy of gross tumour volume localisation in 3D conformal radiotherapy for lung cancer. Image registration protocols which factor in potential software-based errors combined with adequate user training are recommended to increase the accuracy and reproducibility of registration outcomes. A semi-automated adaptive threshold contouring technique incorporating a PET windowing protocol, accurately defines the geometric edge of a tumour volume using PET image data from a stand alone PET scanner, including 4D target volumes.

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Ambisonics and higher order ambisonics (HOA) technologies aim at reproducing sound field either synthesised or previously recorded with dedicated microphones. Based on a spherical harmonic decomposition, the sound field is more precisely described when higher-order components are used. The presented study evaluated the perceptual and objective localisation accuracy of the sound field encoded with four microphones of order one to four and decoded over a ring of loudspeakers. A perceptual test showed an improvement of the localisation with higher order ambisonic microphones. Reproduced localisation indices were estimated for the four microphones and the respective synthetic systems of order one to four. The perceptual and objective analysis revealed the same conclusions. The localisation accuracy depends on the ambisonic order as well as the source incidence. Furthermore, impairments linked to the microphones were highlighted.

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Ambisonics and Higher Order Ambisonics (HOA) are scalable spatial audio techniques that attempt to present a sound scene to listeners over as large an area as possible. A localisation experiment was carried out to investigate the performance of a first and third order system at three listening positions - one in the centre and two off-centre - using a 5 m radius loudspeaker array. The results are briefly presented and compared to those of an earlier experiment on a 2.2 m loudspeaker array. In both experiments the off-centre listeners were placed such that the ratio of distance from the centre to the array radius was constant in both experiments. The test used a reverse target-pointer adjustment method to determine the error, both signed and absolute, for each combination of listening position and system. The results for both arrays were found to be very similar, suggesting that the relative amplitude of the loudspeakers, which were the same in both cases, was more dominant for localisation than the arrival time differences, which differed between array sizes.

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Dans le cadre de l’évaluation pré-chirurgicale de patients épileptiques, il est impératif de déterminer la spécialisation hémisphérique du langage, ainsi que de localiser les aires du langage au sein de cet hémisphère. De nouvelles méthodes d’évaluation non- invasives doivent être mises au point afin de diminuer les risques associés aux méthodes plus invasives telles que le test à l’amobarbital intracarotidien (TAI). L’objectif principal de cette thèse est donc de développer un protocole d’évaluation pré-chirurgicale alternatif et non-invasif à l’aide de la magnétoencéphalographie (MEG) pour la latéralisation et la localisation du langage, incluant la mémoire verbale qui serait éventuellement accessible à une population pédiatrique francophone épileptique. L’article 1 présente une recension de la littérature résumant les différentes études en MEG ayant pour objectif l’évaluation pré-chirurgicale du langage. Trente-sept articles en MEG ont été analysés pour déterminer quelles tâches permettaient d’obtenir les meilleurs résultats de latéralisation intrahémisphérique et de localisation du langage pour l’évaluation du langage réceptif et expressif chez des sujets neurologiquement sains et épileptiques. Parmi les tests retenus, l’épreuve de reconnaissance de mots permet d’évaluer le langage réceptif et la mémoire verbale, tandis que des épreuves de fluence verbale telles que la génération de verbes permettent d’évaluer le langage expressif de façon à obtenir de très bons résultats. L’article 2 a permis de valider un protocole auprès de sujets neurologiquement sains à l’aide des épreuves identifiées dans l’article 1. Le protocole utilisé comprend une tâche de langage réceptif et de mémoire verbale (une épreuve de reconnaissance de mots) et une tâche de langage expressif (une épreuve de fluence verbale). Suite à la validation du protocole à l’aide d’analyses par composantes principales, les épreuves ont été administrées à un groupe de patients épileptiques. Les index de latéralité et les analyses de sources i révèlent que la MEG permet de localiser et de latéraliser les fonctions langagières et pourrait donc être utilisée comme méthode d'évaluation du langage lors de l'évaluation pré- chirurgicale auprès de patients épileptiques. Toutefois, alors que l’épreuve de mémoire verbale a permis d’obtenir les meilleurs résultats auprès de l’ensemble des participants, l’épreuve de fluence verbale n’a fourni des informations supplémentaires que chez un seul patient et chez aucun participant neurologiquement sain. En résumé, les deux articles de cette thèse démontrent le potentiel clinique de la MEG pour l’évaluation pré-chirurgicale de patients souffrant d’une épilepsie réfractaire.

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This paper presents a system that employs random forests to formulate a method for subcellular localisation of proteins. A random forest is an ensemble learner that grows classification trees. Each tree produces a classification decision, and an integrated output is calculated. The system classifies the protein-localisation patterns within fluorescent microscope images. 2D images of HeLa cells that include all major classes of subcellular structures, and the associated feature set are used. The performance of the developed system is compared against that of the support vector machine and decision tree approaches. Three experiments are performed to study the influence of the training and test set size on the performance of the examined methods. The calculated classification errors and execution times are presented and discussed. The lowest classification error (2.9%) has been produced by the developed system.