Effect of age, ethnicity, sex, cognitive status and APOE genotype on amyloid load and the threshold for amyloid positivity.

The threshold for amyloid positivity by visual assessment on PET has been validated by comparison to amyloid load measured histopathologically and biochemically at post mortem. As such, it is now feasible to use qualitative visual assessment of amyloid positivity as an in-vivo gold standard to determine those factors which can modify the quantitative threshold for amyloid positivity. We calculated quantitative amyloid load, measured as Standardized Uptake Value Ratios (SUVRs) using [18-F]florbetaben PET scans, for 159 Hispanic and non-Hispanic participants, who had been classified clinically as Cognitively Normal (CN), Mild Cognitive Impairment (MCI) or Dementia (DEM). PET scans were visually rated as amyloid positive (A+) or negative (A-), and these judgments were used as the gold standard with which to determine (using ROC analyses) the SUVR threshold for amyloid positivity considering factors such as age, ethnicity (Hispanic versus non-Hispanic), gender, cognitive status, and apolipoprotein E ε4 carrier status. Visually rated scans were A+ for 11% of CN, 39.0% of MCI and 70% of DEM participants. The optimal SUVR threshold for A+ among all participants was 1.42 (sensitivity = 94%; specificity = 92.5%), but this quantitative threshold was higher among E4 carriers (SUVR = 1.52) than non-carriers (SUVR = 1.31). While mean SUVRs did not differ between Hispanic and non-Hispanic participants;, a statistically significant interaction term indicated that the effect of E4 carrier status on amyloid load was greater among non-Hispanics than Hispanics. Visual assessment, as the gold standard for A+, facilitates determination of the effects of various factors on quantitative thresholds for amyloid positivity. A continuous relationship was found between amyloid load and global cognitive scores, suggesting that any calculated threshold for the whole group, or a subgroup, is artefactual and that the lowest calculated threshold may be optimal for the purposes of early diagnosis and intervention.

Comparative reliability analysis of publicly available software packages for automatic intracranial volume estimation.

Intracranial volume is an important measure in brain research often used as a correction factor in inter subject studies. The current study investigates the resulting outcome in terms of the type of software used for automatically estimating ICV measure. Five groups of 70 subjects are considered, including adult controls (AC) (n=11), adult with dementia (AD) (n=11), pediatric controls (PC) (n=18) and two groups of pediatric epilepsy subjects (PE1.5 and PE3) (n=30) using 1.5 T and 3T scanners, respectively. Reference measurements were calculated for each subject by manually tracing intracranial cavity without sub-sampling. Four publicly available software packages (AFNI, Freesurfer, FSL, and SPM) were examined in their ability to automatically estimate ICV across the five groups. Linear regression analyses suggest that reference measurement discrepancy could be explained best by SPM [R(2)= 0.67;p <; 0.01] for the AC group, Freesurfer [R(2) = 0.46; p = 0.02] for the AD group, AFNI [R(2)=0.97;p<; 0.01] for the PC group and FSL [R(2) = 0.6; p = 0.1] for the PE1.5 and [R(2) = 0.6; p <; 0.01] for PE3 groups. The study demonstrates that the choice of the automated software for ICV estimation is dependent on the population under consideration and whether the software used is atlas-based or not.

Thermal imaging as a biometrics approach to facial signature authentication.

A new thermal imaging framework with unique feature extraction and similarity measurements for face recognition is presented. The research premise is to design specialized algorithms that would extract vasculature information, create a thermal facial signature and identify the individual. The proposed algorithm is fully integrated and consolidates the critical steps of feature extraction through the use of morphological operators, registration using the Linear Image Registration Tool and matching through unique similarity measures designed for this task. The novel approach at developing a thermal signature template using four images taken at various instants of time ensured that unforeseen changes in the vasculature over time did not affect the biometric matching process as the authentication process relied only on consistent thermal features. Thirteen subjects were used for testing the developed technique on an in-house thermal imaging system. The matching using the similarity measures showed an average accuracy of 88.46% for skeletonized signatures and 90.39% for anisotropically diffused signatures. The highly accurate results obtained in the matching process clearly demonstrate the ability of the thermal infrared system to extend in application to other thermal imaging based systems. Empirical results applying this approach to an existing database of thermal images proves this assertion.

Relating induced changes in EEG signals to orientation of visual stimuli using the ESI-256 machine.

The focus of this study is to investigate the relations that exist between changes in the orientation of simple visual stimuli displayed to a subject and the induced changes in brain activity recorded as EEG signals. These signals are recorded using the Electric Source Imaging with 256 electrodes (ESI-256). The 256-channel EEG signals of four subjects were measured monopolarly. Each subject was stimulated visually for approximately 7.5 minutes. The stimuli consisted of a series of 300 images depicting four basic orientations of a simple graphical element: a white bar on a black background, with each one of the four orientations (horizontal, vertical, +45 degrees and -45 degrees) shown a total of 75 times in a random order. The notion of missing information under certain orientations is not addressed at this juncture. The EEG signals produced by each subject were recorded in a continuous mode using a sampling rate of 1 kHz. Pre-processing of the raw EEG data obtained consisted of epoching, exclusion of faulty electrodes, and reduction of electro-oculogram (EOG) noise due to eye blinks. Topographical maps displaying brain activities and their individual electrode recordings are used as two different means for assessing these changes. It is important to note that the simplicity of the visual stimuli was considered in view of the massive data collected for interpretation. Our goal is to observe and determine new measures that would allow for the quantification and interpretation of such EEG brain activities. Such findings might prove useful for the later use of more complex stimuli and the potential development of size and orientation independent algorithms in image processing.

Decreased 3D-sound spatialization accuracy caused by speech bandwidth limitation over commodity audio components.

This paper studies the accuracy achievable in spatialized speech signals due to their limited bandwidth, in systems based on generic Head-Related Transfer Functions (HRTFs). The accuracy in the perception of sounds spatialized through HRTFs to emulate nine sound locations around the listener, at 0 elevation, are investigated. The tests contrast the localization accuracy for a speech segment and that for broadband noise, as perceived by two independent groups of 10 normal-hearing volunteers each. The sound localization perceived and reported by each subject is compared to the HRTF-emulated location, to define a localization error, in each case. The results are analyzed through a repeated measures, mixed-factorial design Analysis of Variance (ANOVA). The emulated source locations and the type of sounds are the independent variables, and the average perceived localization error for each case, the dependent variable. Since the spectrum of speech signals drive only sections of the complete HRTF frequency response for each location, the initial expectation is that they benefit less from the spectral-shaping process implemented by the HRTFs, thus resulting in a lower spatialization efficiency than the one for a full-spectrum noise signal. We study the measurement of these effects when 3D-sounds are delivered over commodity audio components, because of their widespread use in practical systems.

A practical EMG-based human-computer interface for users with motor disabilities.

In line with the mission of the Assistive Technology Act of 1998 (ATA), this study proposes an integrated assistive real-time system which "affirms that technology is a valuable tool that can be used to improve the lives of people with disabilities." An assistive technology device is defined by the ATA as "any item, piece of equipment, or product system, whether acquired commercially, modified, or customized, that is used to increase, maintain, or improve the functional capabilities of individuals with disabilities." The purpose of this study is to design and develop an alternate input device that can be used even by individuals with severe motor disabilities. This real-time system design utilizes electromyographic (EMG) biosignals from cranial muscles and electroencephalographic (EEG) biosignals from the cerebrum's occipital lobe, which are transformed into controls for two-dimensional (2-D) cursor movement, the left-click (Enter) command, and an ON/OFF switch for the cursor-control functions. This HCI system classifies biosignals into "mouse" functions by applying amplitude thresholds and performing power spectral density (PSD) estimations on discrete windows of data. Spectral power summations are aggregated over several frequency bands between 8 and 500 Hz and then compared to produce the correct classification. The result is an affordable DSP-based system that, when combined with an on-screen keyboard, enables the user to fully operate a computer without using any extremities.

A directional clustering technique for random data classification.

This paper introduces a new clustering technique for random data classification based on an enhanced version of the Voronoi diagram. This technique is optimized to deal in the best way possible with data distributions which in their spatial representations experience overlap. A mathematical framework is given in view of this enhanced analysis and provides insight to key issues involving (a) the use of a correction process to complement the traditional Voronoi diagram and (b) the introduction of directional vectors in Gaussian and elliptical data distributions for enhanced data clustering. The computational requirements of the proposed approach are provided, and the computer results involving both randomly generated and real-world data prove the soundness of this clustering technique.

A similarity measure for stereo feature matching.

An approach to stereo feature matching is presented with the introduction of a similarity measure for evaluating and confirming a stereo match. The contributions of this study are reflected in (1) the development of a similarity measure which evaluates a stereo match based on feature locality and gray-level gradient associated with the feature; and (2) the use of a matching procedure that integrates local and global matching strategies based on matching first those features with the highest similarity measure among the set of all highest similarities found locally under confined search spaces, ensuring that each feature is matched with a high degree of certainty. A left-to-right and right-to-left consistency check is used for each feature to comply with the uniqueness constraint and to confirm if a potential match can be declared a correct match.

An augmented computer vision approach for enhanced image understanding.

This paper addresses the design concept of a spatially and spectrally augmented computer vision approach toward enhanced image analysis and understanding. The concept of spatially augmented computer vision refers to the inclusion of the stereo disparity measure (1/2-D) along with the two-dimensional (2-D) spatial coordinates of the images, together yielding the augmented (2 1/2-D) representation. The concept of spectrally augmented computer vision refers to the implementation of the multiresolution concept of the wavelet theory to analyze and assess in detail the local properties of the 2-D images. The principal objective in applying this augmented, and more revealing, computer vision approach is to provide the added dimension in spatial and spectral resolutions for the enhanced understanding of images. To this end, imaging techniques are developed to exploit, in an optimal fashion, the information acquired by the camera system to yield useful descriptions of the viewed scenes. Experimental results are provided in support of this research direction.

A man-machine vision interface for sensing the environment.

This study describes a computer vision approach for sensing the environment with the intent of helping people with a visual impairment. The principal goal in applying computer vision is to exploit, in an optimal fashion, the information acquired by the camera(s) to yield useful descriptions of the viewed environment. The objective is to seek efficient and reliable guidance cues in order to improve the mobility needs of individuals with a visual impairment. In this research direction, the following problems are identified and addressed: 1) the vision system design; 2) establishment of the mapping principles between the two-dimensional (2-D) camera images and the three-dimensional (3-D) real world; 3) development of appropriate imaging techniques for the interpretation of the 2-D images; and, 4) establishment of a communication link between the vision system and the user. The soundness of this research direction is assessed by means of a theoretical framework and experimental evaluations.