Longitudinal testing of visual perception in dementia with Lewy bodies and Alzheimer's disease

Visuo-perceptual abnormalities are a prominent feature in dementia with Lewy bodies (DLB) and also occur in Alzheimer's disease (AD) to a lesser extent. We studied the progression of visuo-perceptual abnormalities over a 12-month period in DLB and AD by using a novel computerised test battery.

The identification of cerebral volume changes in treated growth hormone-deficient adults using serial 3D MR image processing

A pilot study to detect volume changes of cerebral structures in growth hormone (GH)-deficient adults treated with GH using serial 3D MR image processing and to assess need for segmentation prior to registration was conducted.

The Topology of Auditory and Visual Perception, Linguistic Communication, and Interactive Written Discourse

In this article, it is shown that IWD incorporates topological perceptual characteristics of both spoken and written language, and it is argued that these characteristics should not be ignored or given up when synchronous textual CMC is technologically developed and upgraded.

Testing visual perception in dementia with Lewy bodies and Alzheimer disease

OBJECTIVE Visuoperceptual deficits are common in dementia with Lewy bodies (DLB) and Alzheimer disease (AD). Testing visuoperception in dementia is complicated by decline in other cognitive domains and extrapyramidal features. To overcome these issues, we developed a computerized test, the Newcastle visuoperception battery (NEVIP), which is independent of motor function and has minimal cognitive load.We aimed to test its utility to identify visuoperceptual deficits in people with dementia. PARTICIPANTS AND MEASUREMENTS We recruited 28 AD and 26 DLB participants with 35 comparison participants of similar age and education. The NEVIP was used to test angle, color, and form discrimination along with motion perception to obtain a composite visuoperception score. RESULTS Those with DLB performed significantly worse than AD participants on the composite visuoperception score (Mann-Whitney U = 142, p = 0.01). Visuoperceptual deficits (defined as 2 SD below the performance of comparisons) were present in 71% of the DLB group and 40% of the AD group. Performance was not significantly correlated with motor impairment, but was significantly related to global cognitive impairment in DLB (rs = -0.689, p <0.001), but not in AD. CONCLUSION Visuoperceptual deficits can be detected in both DLB and AD participants using the NEVIP, with the DLB group performing significantly worse than AD. Visuoperception scores obtained by the NEVIP are independent of participant motor deficits and participants are able to comprehend and perform the tasks.

Morphology–elasticity relationships using decreasing fabric information of human trabecular bone from three major anatomical locations

With improving clinical CT scanning technology, the accuracy of CT-based finite element (FE) models of the human skeleton may be ameliorated by an enhanced description of apparent level bone mechanical properties. Micro-finite element (μFE) modeling can be used to study the apparent elastic behavior of human cancellous bone. In this study, samples from the femur, radius and vertebral body were investigated to evaluate the predictive power of morphology–elasticity relationships and to compare them across different anatomical regions. μFE models of 701 trabecular bone cubes with a side length of 5.3 mm were analyzed using kinematic boundary conditions. Based on the FE results, four morphology–elasticity models using bone volume fraction as well as full, limited or no fabric information were calibrated for each anatomical region. The 5 parameter Zysset–Curnier model using full fabric information showed excellent predictive power with coefficients of determination ( r2adj ) of 0.98, 0.95 and 0.94 of the femur, radius and vertebra data, respectively, with mean total norm errors between 14 and 20%. A constant orthotropy model and a constant transverse isotropy model, where the elastic anisotropy is defined by the model parameters, yielded coefficients of determination between 0.90 and 0.98 with total norm errors between 16 and 25%. Neglecting fabric information and using an isotropic model led to r2adj between 0.73 and 0.92 with total norm errors between 38 and 49%. A comparison of the model regressions revealed minor but significant (p<0.01) differences for the fabric–elasticity model parameters calibrated for the different anatomical regions. The proposed models and identified parameters can be used in future studies to compute the apparent elastic properties of human cancellous bone for homogenized FE models.

Effect of irradiation distance on image contrast in epi-optoacoustic imaging of human volunteers

In combined clinical optoacoustic (OA) and ultrasound (US) imaging, epi-mode irradiation and detection integrated into one single probe offers flexible imaging of the human body. The imaging depth in epi-illumination is, however, strongly affected by clutter. As shown in previous phantom experiments, the location of irradiation plays an important role in clutter generation. We investigated the influence of the irradiation geometry on the local image contrast of clinical images, by varying the separation distance between the irradiated area and the acoustic imaging plane of a linear ultrasound transducer in an automated scanning setup. The results for different volunteers show that the image contrast can be enhanced on average by 25% and locally by more than a factor of two, when the irradiated area is slightly separated from the probe. Our findings have an important impact on the design of future optoacoustic probes for clinical application.

How need for cognition affects the processing of achievement-related information

The present article analyzed, how need for cognition (NFC) influences the formation of performance expectancies. When processing information, individuals with lower NFC often rely on salient information and shortcuts compared to individuals higher in NFC. We assume that these preferences of processing will also make individuals low in NFC more responsive to salient achievement-related cues because the processing of salient cues is cognitively less demanding than the processing of non-salient cues. Therefore, individuals lower in NFC should tend to draw wider ranging inferences from salient achievement-related information. In a sample of N = 197 secondary school students, achievement-related feedback (grade on an English examination) affected changes in expectancies in non-corresponding academic subjects (e.g., expectation of final grade in mathematics or history) when NFC was lower, whereas for students with higher NFC, changes in expectancies in non-corresponding academic subjects were not affected.

Visual Perception and Acuity of Hand Surgeons Using Loupes.

PURPOSE To assess the visual performance of Swiss hand surgeons in an environment similar to their workplace. The influence of Galilean (lenses only) and Keplerian loupes (lenses and prisms), the surgeon's age, and the credibility of a self-assessment of his or her own optical performance were evaluated. METHODS Sixty-three hand surgeons between 29 and 68 years of age with 70 loupes were included in the study (Galilean n = 35, Keplerian n = 35). The visual performance as surgeons was self-assessed on a modified visual analog scale and objectively measured with miniaturized visual tests in a simulated clinical setting. We evaluated the influence of the optical device by comparing Galilean and Keplerian loupes and the influence of the surgeon's age by comparing 2 subgroups: < 40 years and ≥ 40 years. RESULTS The correlation between self-assessment and objective visual performance was weak, with a Spearman rank correlation coefficient of 0.25. The near visual acuity with habitual optical aids showed considerable variability, with a range of 300% in the dimension of the smallest detected structure. The near visual acuity was significantly lower in the older group ≥ 40 years than in the younger group < 40 years with both Galilean and Keplerian loupes. Keplerian loupes allowed a significantly higher visual performance than Galilean loupes. Surgeons 40 years or older using Keplerian loupes had a similar visual acuity to surgeons younger than 40 years with Galilean loupes. CONCLUSIONS The magnified near vision of hand surgeons showed an important individual variability. Self-assessment was not a valuable instrument for surgeons to estimate their own near vision. Hand surgeons older than 40 years should use higher magnification loupes. TYPE OF STUDY/LEVEL OF EVIDENCE Diagnostic III.

A self-adaptive image processing application based on evolvable and scalable hardware

Evolvable Hardware (EH) is a technique that consists of using reconfigurable hardware devices whose configuration is controlled by an Evolutionary Algorithm (EA). Our system consists of a fully-FPGA implemented scalable EH platform, where the Reconfigurable processing Core (RC) can adaptively increase or decrease in size. Figure 1 shows the architecture of the proposed System-on-Programmable-Chip (SoPC), consisting of a MicroBlaze processor responsible of controlling the whole system operation, a Reconfiguration Engine (RE), and a Reconfigurable processing Core which is able to change its size in both height and width. This system is used to implement image filters, which are generated autonomously thanks to the evolutionary process. The system is complemented with a camera that enables the usage of the platform for real time applications.

Some relations between visual perception and non-linear photonic structures

The main objective of this work is to present a way to emulate some functions of the mammalian visual system and a model to analyze subjective sensations and visual illusions

Aplicación de técnicas de inteligencia artificial para contribuir en la detección de microcalcificaciones en mamografía digitalizada

A nivel mundial, el cáncer de mama es el tipo de cáncer más frecuente además de una de las principales causas de muerte entre la población femenina. Actualmente, el método más eficaz para detectar lesiones mamarias en una etapa temprana es la mamografía. Ésta contribuye decisivamente al diagnóstico precoz de esta enfermedad que, si se detecta a tiempo, tiene una probabilidad de curación muy alta. Uno de los principales y más frecuentes hallazgos en una mamografía, son las microcalcificaciones, las cuales son consideradas como un indicador importante de cáncer de mama. En el momento de analizar las mamografías, factores como la capacidad de visualización, la fatiga o la experiencia profesional del especialista radiólogo hacen que el riesgo de omitir ciertas lesiones presentes se vea incrementado. Para disminuir dicho riesgo es importante contar con diferentes alternativas como por ejemplo, una segunda opinión por otro especialista o un doble análisis por el mismo. En la primera opción se eleva el coste y en ambas se prolonga el tiempo del diagnóstico. Esto supone una gran motivación para el desarrollo de sistemas de apoyo o asistencia en la toma de decisiones. En este trabajo de tesis se propone, se desarrolla y se justifica un sistema capaz de detectar microcalcificaciones en regiones de interés extraídas de mamografías digitalizadas, para contribuir a la detección temprana del cáncer demama. Dicho sistema estará basado en técnicas de procesamiento de imagen digital, de reconocimiento de patrones y de inteligencia artificial. Para su desarrollo, se tienen en cuenta las siguientes consideraciones: 1. Con el objetivo de entrenar y probar el sistema propuesto, se creará una base de datos de imágenes, las cuales pertenecen a regiones de interés extraídas de mamografías digitalizadas. 2. Se propone la aplicación de la transformada Top-Hat, una técnica de procesamiento digital de imagen basada en operaciones de morfología matemática. La finalidad de aplicar esta técnica es la de mejorar el contraste entre las microcalcificaciones y el tejido presente en la imagen. 3. Se propone un algoritmo novel llamado sub-segmentación, el cual está basado en técnicas de reconocimiento de patrones aplicando un algoritmo de agrupamiento no supervisado, el PFCM (Possibilistic Fuzzy c-Means). El objetivo es encontrar las regiones correspondientes a las microcalcificaciones y diferenciarlas del tejido sano. Además, con la finalidad de mostrar las ventajas y desventajas del algoritmo propuesto, éste es comparado con dos algoritmos del mismo tipo: el k-means y el FCM (Fuzzy c-Means). Por otro lado, es importante destacar que en este trabajo por primera vez la sub-segmentación es utilizada para detectar regiones pertenecientes a microcalcificaciones en imágenes de mamografía. 4. Finalmente, se propone el uso de un clasificador basado en una red neuronal artificial, específicamente un MLP (Multi-layer Perceptron). El propósito del clasificador es discriminar de manera binaria los patrones creados a partir de la intensidad de niveles de gris de la imagen original. Dicha clasificación distingue entre microcalcificación y tejido sano. ABSTRACT Breast cancer is one of the leading causes of women mortality in the world and its early detection continues being a key piece to improve the prognosis and survival. Currently, the most reliable and practical method for early detection of breast cancer is mammography.The presence of microcalcifications has been considered as a very important indicator ofmalignant types of breast cancer and its detection and classification are important to prevent and treat the disease. However, the detection and classification of microcalcifications continue being a hard work due to that, in mammograms there is a poor contrast between microcalcifications and the tissue around them. Factors such as visualization, tiredness or insufficient experience of the specialist increase the risk of omit some present lesions. To reduce this risk, is important to have alternatives such as a second opinion or a double analysis for the same specialist. In the first option, the cost increases and diagnosis time also increases for both of them. This is the reason why there is a great motivation for development of help systems or assistance in the decision making process. This work presents, develops and justifies a system for the detection of microcalcifications in regions of interest extracted fromdigitizedmammographies to contribute to the early detection of breast cancer. This systemis based on image processing techniques, pattern recognition and artificial intelligence. For system development the following features are considered: With the aim of training and testing the system, an images database is created, belonging to a region of interest extracted from digitized mammograms. The application of the top-hat transformis proposed. This image processing technique is based on mathematical morphology operations. The aim of this technique is to improve the contrast betweenmicrocalcifications and tissue present in the image. A novel algorithm called sub-segmentation is proposed. The sub-segmentation is based on pattern recognition techniques applying a non-supervised clustering algorithm known as Possibilistic Fuzzy c-Means (PFCM). The aim is to find regions corresponding to the microcalcifications and distinguish them from the healthy tissue. Furthermore,with the aim of showing themain advantages and disadvantages this is compared with two algorithms of same type: the k-means and the fuzzy c-means (FCM). On the other hand, it is important to highlight in this work for the first time the sub-segmentation is used for microcalcifications detection. Finally, a classifier based on an artificial neural network such as Multi-layer Perceptron is used. The purpose of this classifier is to discriminate froma binary perspective the patterns built from gray level intensity of the original image. This classification distinguishes between microcalcifications and healthy tissue.

A Dynamically Adaptable Image Processing Application Trading Off Between High Performance, Consumption and Dependability in Real Time

As embedded systems evolve, problems inherent to technology become important limitations. In less than ten years, chips will exceed the maximum allowed power consumption affecting performance, since, even though the resources available per chip are increasing, frequency of operation has stalled. Besides, as the level of integration is increased, it is difficult to keep defect density under control, so new fault tolerant techniques are required. In this demo work, a new dynamically adaptable virtual architecture (ARTICo3) to allow dynamic and context-aware use of resources is implemented in a high performance Wireless Sensor node (HiReCookie) to perform an image processing application.

A study of feature combination for vehicle detection based on image processing

Video analytics play a critical role in most recent traffic monitoring and driver assistance systems. In this context, the correct detection and classification of surrounding vehicles through image analysis has been the focus of extensive research in the last years. Most of the pieces of work reported for image-based vehicle verification make use of supervised classification approaches and resort to techniques, such as histograms of oriented gradients (HOG), principal component analysis (PCA), and Gabor filters, among others. Unfortunately, existing approaches are lacking in two respects: first, comparison between methods using a common body of work has not been addressed; second, no study of the combination potentiality of popular features for vehicle classification has been reported. In this study the performance of the different techniques is first reviewed and compared using a common public database. Then, the combination capabilities of these techniques are explored and a methodology is presented for the fusion of classifiers built upon them, taking into account also the vehicle pose. The study unveils the limitations of single-feature based classification and makes clear that fusion of classifiers is highly beneficial for vehicle verification.

A rhodopsin-guanylyl cyclase gene fusion functions in visual perception in a fungus

Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.