The relationship between fusion, suppression, and diplopia in amblyopia

Purpose: Traditionally, it has been thought that no binocular combination occurs in amblyopia. However, there is a growing body of evidence that there are intact binocular mechanisms in amblyopia rendered inactive under normal viewing conditions due to imbalanced monocular inputs. Georgeson and Wallis (2014) recently introduced a novel method to investigate fusion, suppression and diplopia in normal population. We have modified this method to assess binocular interactions in amblyopia. Methods: Ten amblyopic and ten control subjects viewed briefly-presented (200 ms) pairs of dichoptically separated horizontal Gaussian blurred edges. Subjects reported one central edge, one offset edge, or a double edge as the vertical disparity was manipulated. The experiment was conducted at a range of spatial scales (blur widths of 4, 8, 16, and 32 arc min) and contrasts. Our model, based Georgeson and Wallis (2014), converted subjects’ responses into probabilities of fusion, suppression, and diplopia. Results: When the normal participants were presented equal contrast to each eye the probability of fusion gradually decreased with increasing disparity, as the probability of diplopia gradually increased. In only a small proportion of the trials, normal participants experienced suppression. The pattern was consistent across all edge blurs. Interestingly, the majority of amblyopes had a comparable pattern of fusion, i.e. decreasing probability with increasing disparity. However, with increasing disparity the amblyopes tended to suppress the amblyopic eye, experiencing diplopia only in a small proportion of trials particularly at large blurs. Increasing the interocular contrast offset favouring the amblyopic eye normalized the pattern of data in a way similar to normal participants. There were some interesting exceptions: strong suppressors for which our contrast range was inadequate and one case in which diplopia dominated. Conclusions: This task is suitable for assessing binocular interactions in amblyopic participants and providing a way to quantify the relationship between fusion, suppression and diplopia. In agreement with previous studies, our data indicate the presence of binocular mechanisms in amblyopia. A contrast offset favouring the amblyopic eye normalizes the measured binocular interactions in the amblyopic visual system.

Primary pulmonary myxoid sarcoma with EWSR1-CREB1 fusion: a new tumor entity.

We present clinicopathologic data on 10 pulmonary myxoid sarcomas, which are defined by distinctive histomorphologic features and characterized by a recurrent fusion gene, that appear to represent a distinct tumor entity at this site. The patients [7 female, 3 male; aged 27 to 67 y (mean, 45 y)] presented with local or systemic symptoms (n=5), symptoms from cerebral metastasis (1), or incidentally (2). Follow-up of 6 patients showed that 1 with brain metastasis died shortly after primary tumor resection, 1 developed a renal metastasis but is alive and well, and 4 are disease free after 1 to 15 years. All tumors involved pulmonary parenchyma, with a predominant endobronchial component in 8 and ranged from 1.5 to 4 cm. Microscopically, they were lobulated and composed of cords of polygonal, spindle, or stellate cells within myxoid stroma, morphologically reminiscent of extraskeletal myxoid chondrosarcoma. Four cases showed no or minimal atypia, 6 showed focal pleomorphism, and 5 had necrosis. Mitotic indices varied, with most tumors not exceeding 5/10 high-power fields. Tumors were immunoreactive for only vimentin and weakly focal for epithelial membrane antigen. Of 9 tumors, 7 were shown to harbor a specific EWSR1-CREB1 fusion by reverse transcription-polymerase chain reaction and direct sequencing, with 7 of 10 showing EWSR1 rearrangement by fluorescence in situ hybridization. This gene fusion has been described previously in 2 histologically and behaviorally different sarcomas: clear cell sarcoma-like tumors of the gastrointestinal tract and angiomatoid fibrous histiocytomas; however, this is a novel finding in tumors with the morphology we describe and that occur in the pulmonary region.

Data Science Seminar: Generic Big Data Processing for Advancing Situation Awareness and Decision-Support

The generation of heterogeneous big data sources with ever increasing volumes, velocities and veracities over the he last few years has inspired the data science and research community to address the challenge of extracting knowledge form big data. Such a wealth of generated data across the board can be intelligently exploited to advance our knowledge about our environment, public health, critical infrastructure and security. In recent years we have developed generic approaches to process such big data at multiple levels for advancing decision-support. It specifically concerns data processing with semantic harmonisation, low level fusion, analytics, knowledge modelling with high level fusion and reasoning. Such approaches will be introduced and presented in context of the TRIDEC project results on critical oil and gas industry drilling operations and also the ongoing large eVacuate project on critical crowd behaviour detection in confined spaces.

Information fusion in the immune system

Biologically-inspired methods such as evolutionary algorithms and neural networks are proving useful in the field of information fusion. Artificial immune systems (AISs) are a biologically-inspired approach which take inspiration from the biological immune system. Interestingly, recent research has shown how AISs which use multi-level information sources as input data can be used to build effective algorithms for realtime computer intrusion detection. This research is based on biological information fusion mechanisms used by the human immune system and as such might be of interest to the information fusion community. The aim of this paper is to present a summary of some of the biological information fusion mechanisms seen in the human immune system, and of how these mechanisms have been implemented as AISs.

STORM - a novel information fusion and cluster interpretation technique

Analysis of data without labels is commonly subject to scrutiny by unsupervised machine learning techniques. Such techniques provide more meaningful representations, useful for better understanding of a problem at hand, than by looking only at the data itself. Although abundant expert knowledge exists in many areas where unlabelled data is examined, such knowledge is rarely incorporated into automatic analysis. Incorporation of expert knowledge is frequently a matter of combining multiple data sources from disparate hypothetical spaces. In cases where such spaces belong to different data types, this task becomes even more challenging. In this paper we present a novel immune-inspired method that enables the fusion of such disparate types of data for a specific set of problems. We show that our method provides a better visual understanding of one hypothetical space with the help of data from another hypothetical space. We believe that our model has implications for the field of exploratory data analysis and knowledge discovery.

POSE ESTIMATION AND 3D RECONSTRUCTION USING SENSOR FUSION

A camera maps 3-dimensional (3D) world space to a 2-dimensional (2D) image space. In the process it loses the depth information, i.e., the distance from the camera focal point to the imaged objects. It is impossible to recover this information from a single image. However, by using two or more images from different viewing angles this information can be recovered, which in turn can be used to obtain the pose (position and orientation) of the camera. Using this pose, a 3D reconstruction of imaged objects in the world can be computed. Numerous algorithms have been proposed and implemented to solve the above problem; these algorithms are commonly called Structure from Motion (SfM). State-of-the-art SfM techniques have been shown to give promising results. However, unlike a Global Positioning System (GPS) or an Inertial Measurement Unit (IMU) which directly give the position and orientation respectively, the camera system estimates it after implementing SfM as mentioned above. This makes the pose obtained from a camera highly sensitive to the images captured and other effects, such as low lighting conditions, poor focus or improper viewing angles. In some applications, for example, an Unmanned Aerial Vehicle (UAV) inspecting a bridge or a robot mapping an environment using Simultaneous Localization and Mapping (SLAM), it is often difficult to capture images with ideal conditions. This report examines the use of SfM methods in such applications and the role of combining multiple sensors, viz., sensor fusion, to achieve more accurate and usable position and reconstruction information. This project investigates the role of sensor fusion in accurately estimating the pose of a camera for the application of 3D reconstruction of a scene. The first set of experiments is conducted in a motion capture room. These results are assumed as ground truth in order to evaluate the strengths and weaknesses of each sensor and to map their coordinate systems. Then a number of scenarios are targeted where SfM fails. The pose estimates obtained from SfM are replaced by those obtained from other sensors and the 3D reconstruction is completed. Quantitative and qualitative comparisons are made between the 3D reconstruction obtained by using only a camera versus that obtained by using the camera along with a LIDAR and/or an IMU. Additionally, the project also works towards the performance issue faced while handling large data sets of high-resolution images by implementing the system on the Superior high performance computing cluster at Michigan Technological University.

High body mass index is not a barrier to physical activity: Analysis of international rugby players' anthropometric data

Recent data indicate that levels of overweight and obesity are increasing at an alarming rate throughout the world. At a population level (and commonly to assess individual health risk), the prevalence of overweight and obesity is calculated using cut-offs of the Body Mass Index (BMI) derived from height and weight. Similarly, the BMI is also used to classify individuals and to provide a notional indication of potential health risk. It is likely that epidemiologic surveys that are reliant on BMI as a measure of adiposity will overestimate the number of individuals in the overweight (and slightly obese) categories. This tendency to misclassify individuals may be more pronounced in athletic populations or groups in which the proportion of more active individuals is higher. This differential is most pronounced in sports where it is advantageous to have a high BMI (but not necessarily high fatness). To illustrate this point we calculated the BMIs of international professional rugby players from the four teams involved in the semi-finals of the 2003 Rugby Union World Cup. According to the World Health Organisation (WHO) cut-offs for BMI, approximately 65% of the players were classified as overweight and approximately 25% as obese. These findings demonstrate that a high BMI is commonplace (and a potentially desirable attribute for sport performance) in professional rugby players. An unanswered question is what proportion of the wider population, classified as overweight (or obese) according to the BMI, is misclassified according to both fatness and health risk? It is evident that being overweight should not be an obstacle to a physically active lifestyle. Similarly, a reliance on BMI alone may misclassify a number of individuals who might otherwise have been automatically considered fat and/or unfit.