Sensory and conceptual representations in memory: Motor images which cannot be imaged

The paper argues for a distinction between sensory-and conceptual-information storage in the human information-processing system. Conceptual information is characterized as meaningful and symbolic, while sensory information may exist in modality-bound form. Furthermore, it is assumed that sensory information does not contribute to conscious remembering and can be used only in data-driven process reptitions, which can be accompanied by a kind of vague or intuitive feeling. Accordingly, pure top-down and willingly controlled processing, such as free recall, should not have any access to sensory data. Empirical results from different research areas and from two experiments conducted by the authors are presented in this article to support these theoretical distinctions. The experiments were designed to separate a sensory-motor and a conceptual component in memory for two-digit numbers and two-letter items, when parts of the numbers or items were imaged or drawn on a tablet. The results of free recall and recognition are discussed in a theoretical framework which distinguishes sensory and conceptual information in memory.

Multi-modal glioblastoma segmentation: man versus machine

BACKGROUND AND PURPOSE Reproducible segmentation of brain tumors on magnetic resonance images is an important clinical need. This study was designed to evaluate the reliability of a novel fully automated segmentation tool for brain tumor image analysis in comparison to manually defined tumor segmentations. METHODS We prospectively evaluated preoperative MR Images from 25 glioblastoma patients. Two independent expert raters performed manual segmentations. Automatic segmentations were performed using the Brain Tumor Image Analysis software (BraTumIA). In order to study the different tumor compartments, the complete tumor volume TV (enhancing part plus non-enhancing part plus necrotic core of the tumor), the TV+ (TV plus edema) and the contrast enhancing tumor volume CETV were identified. We quantified the overlap between manual and automated segmentation by calculation of diameter measurements as well as the Dice coefficients, the positive predictive values, sensitivity, relative volume error and absolute volume error. RESULTS Comparison of automated versus manual extraction of 2-dimensional diameter measurements showed no significant difference (p = 0.29). Comparison of automated versus manual segmentation of volumetric segmentations showed significant differences for TV+ and TV (p<0.05) but no significant differences for CETV (p>0.05) with regard to the Dice overlap coefficients. Spearman's rank correlation coefficients (ρ) of TV+, TV and CETV showed highly significant correlations between automatic and manual segmentations. Tumor localization did not influence the accuracy of segmentation. CONCLUSIONS In summary, we demonstrated that BraTumIA supports radiologists and clinicians by providing accurate measures of cross-sectional diameter-based tumor extensions. The automated volume measurements were comparable to manual tumor delineation for CETV tumor volumes, and outperformed inter-rater variability for overlap and sensitivity.

Little evidence for release from herbivores as a driver of plant invasiveness from a multi-species herbivore-removal experiment

Enemy release is frequently posed as a main driver of invasiveness of alien species. However, an experimental multi-species test examining performance and herbivory of invasive alien, non-invasive alien and native plant species in the presence and absence of natural enemies is lacking. In a common garden experiment in Switzerland, we manipulated exposure of seven alien invasive, eight alien non-invasive and fourteen native species from six taxonomic groups to natural enemies (invertebrate herbivores), by applying a pesticide treatment under two different nutrient levels. We assessed biomass production, herbivore damage and the major herbivore taxa on plants. Across all species, plants gained significantly greater biomass under pesticide treatment. However, invasive, non-invasive and native species did not differ in their biomass response to pesticide treatment at either nutrient level. The proportion of leaves damaged on invasive species was significantly lower compared to native species, but not when compared to non-invasive species. However, the difference was lost when plant size was accounted for. There were no differences between invasive, non-invasive and native species in herbivore abundance. Our study offers little support for invertebrate herbivore release as a driver of plant invasiveness, but suggests that future enemy release studies should account for differences in plant size among species.

Landmark Detection for Fusion of Fundus and MRI Towards a Patient-Specific Multi-Modal Eye Model

Ophthalmologists typically acquire different image modalities to diagnose eye pathologies. They comprise e.g., Fundus photography, Optical Coherence Tomography (OCT), Computed Tomography (CT) and Magnetic Resonance Imaging (MRI). Yet, these images are often complementary and do express the same pathologies in a different way. Some pathologies are only visible in a particular modality. Thus, it is beneficial for the ophthalmologist to have these modalities fused into a single patient-specific model. The presented article’s goal is a fusion of Fundus photography with segmented MRI volumes. This adds information to MRI which was not visible before like vessels and the macula. This article’s contributions include automatic detection of the optic disc, the fovea, the optic axis and an automatic segmentation of the vitreous humor of the eye.

Optical Tolerance Analysis of the Multi-Beam Limb Viewing Instrument STEAMR

In this paper, we report on an optical tolerance analysis of the submillimeter atmospheric multi-beam limb sounder, STEAMR. Physical optics and ray-tracing methods were used to quantify and separate errors in beam pointing and distortion due to reflector misalignment and primary reflector surface deformations. Simulations were performed concurrently with the manufacturing of a multi-beam demonstrator of the relay optical system which shapes and images the beams to their corresponding receiver feed horns. Results from Monte Carlo simulations show that the inserts used for reflector mounting should be positioned with an overall accuracy better than 100 μm (~ 1/10 wavelength). Analyses of primary reflector surface deformations show that a deviation of magnitude 100 μm can be tolerable before deployment, whereas the corresponding variations should be less than 30 μm during operation. The most sensitive optical elements in terms of misalignments are found near the focal plane. This localized sensitivity is attributed to the off-axis nature of the beams at this location. Post-assembly mechanical measurements of the reflectors in the demonstrator show that alignment better than 50 μm could be obtained.

Professionalisation of sport federations. A multi-level framework for analysing forms, causes and consequences

Research question: International and national sport federations as well as their member organisations (usually sport clubs) are key actors within the sport system and have a wide range of relationships outside the sport system (e.g. with the state, sponsors, and the media). They are currently facing major challenges such as growing competition in top-level sports, democratisation of sports with “sports for all” and sports as the answer to social problems (integration, education, health, unemployment, etc.). In this context, professionalising sport organisations seems to be an appropriate strategy to face these challenges and solve current problems. We define the professionalisation of sport organisations as an organisational process of transformation leading towards organisational rationalisation, efficiency and business-like management. This has led to a profound organisational change, particularly within sport federations, characterised by the strengthening of institutional management (managerialism) and the implementation of efficiency-based management instruments and paid staff. Research methods: The goal of this article is to review the international literature and establish a global understanding of and theoretical framework for how sport organisations professionalise and what consequences this may have. Results and Findings: Our multi-level approach based on the social theory of action integrates the current concepts for analysing professionalisation in sport federations. We specify the framework for the following research perspectives: (1) forms, (2) causes and (3) consequences, and discuss the reciprocal relations between sport federations and their member organisations in this context. Implications: Finally, we derive general methodological consequences for the investigation of professionalisation processes in sport organisations.

Is complex signal processing for bone conduction hearing aids useful?

OBJECTIVES To establish whether complex signal processing is beneficial for users of bone anchored hearing aids. METHODS Review and analysis of two studies from our own group, each comparing a speech processor with basic digital signal processing (either Baha Divino or Baha Intenso) and a processor with complex digital signal processing (either Baha BP100 or Baha BP110 power). The main differences between basic and complex signal processing are the number of audiologist accessible frequency channels and the availability and complexity of the directional multi-microphone noise reduction and loudness compression systems. RESULTS Both studies show a small, statistically non-significant improvement of speech understanding in quiet with the complex digital signal processing. The average improvement for speech in noise is +0.9 dB, if speech and noise are emitted both from the front of the listener. If noise is emitted from the rear and speech from the front of the listener, the advantage of the devices with complex digital signal processing as opposed to those with basic signal processing increases, on average, to +3.2 dB (range +2.3 … +5.1 dB, p ≤ 0.0032). DISCUSSION Complex digital signal processing does indeed improve speech understanding, especially in noise coming from the rear. This finding has been supported by another study, which has been published recently by a different research group. CONCLUSIONS When compared to basic digital signal processing, complex digital signal processing can increase speech understanding of users of bone anchored hearing aids. The benefit is most significant for speech understanding in noise.

Reducing CT radiation dose with iterative reconstruction algorithms: the influence of scan and reconstruction parameters on image quality and CTDIvol

OBJECTIVES In this phantom CT study, we investigated whether images reconstructed using filtered back projection (FBP) and iterative reconstruction (IR) with reduced tube voltage and current have equivalent quality. We evaluated the effects of different acquisition and reconstruction parameter settings on image quality and radiation doses. Additionally, patient CT studies were evaluated to confirm our phantom results. METHODS Helical and axial 256 multi-slice computed tomography scans of the phantom (Catphan(®)) were performed with varying tube voltages (80-140kV) and currents (30-200mAs). 198 phantom data sets were reconstructed applying FBP and IR with increasing iterations, and soft and sharp kernels. Further, 25 chest and abdomen CT scans, performed with high and low exposure per patient, were reconstructed with IR and FBP. Two independent observers evaluated image quality and radiation doses of both phantom and patient scans. RESULTS In phantom scans, noise reduction was significantly improved using IR with increasing iterations, independent from tissue, scan-mode, tube-voltage, current, and kernel. IR did not affect high-contrast resolution. Low-contrast resolution was also not negatively affected, but improved in scans with doses <5mGy, although object detectability generally decreased with the lowering of exposure. At comparable image quality levels, CTDIvol was reduced by 26-50% using IR. In patients, applying IR vs. FBP resulted in good to excellent image quality, while tube voltage and current settings could be significantly decreased. CONCLUSIONS Our phantom experiments demonstrate that image quality levels of FBP reconstructions can also be achieved at lower tube voltages and tube currents when applying IR. Our findings could be confirmed in patients revealing the potential of IR to significantly reduce CT radiation doses.

Anamorphic pixels for multi-channel superresolution

Superresolution from plenoptic cameras or camera arrays is usually treated similarly to superresolution from video streams. However, the transformation between the low-resolution views can be determined precisely from camera geometry and parallax. Furthermore, as each low-resolution image originates from a unique physical camera, its sampling properties can also be unique. We exploit this option with a custom design of either the optics or the sensor pixels. This design makes sure that the sampling matrix of the complete system is always well-formed, enabling robust and high-resolution image reconstruction. We show that simply changing the pixel aspect ratio from square to anamorphic is sufficient to achieve that goal, as long as each camera has a unique aspect ratio. We support this claim with theoretical analysis and image reconstruction of real images. We derive the optimal aspect ratios for sets of 2 or 4 cameras. Finally, we verify our solution with a camera system using an anamorphic lens.

Computer Vision-Based Carbohydrate Estimation for Type 1 Diabetic Patients Using Smartphones

Background: Individuals with type 1 diabetes (T1D) have to count the carbohydrates (CHOs) of their meal to estimate the prandial insulin dose needed to compensate for the meal’s effect on blood glucose levels. CHO counting is very challenging but also crucial, since an error of 20 grams can substantially impair postprandial control. Method: The GoCARB system is a smartphone application designed to support T1D patients with CHO counting of nonpacked foods. In a typical scenario, the user places a reference card next to the dish and acquires 2 images with his/her smartphone. From these images, the plate is detected and the different food items on the plate are automatically segmented and recognized, while their 3D shape is reconstructed. Finally, the food volumes are calculated and the CHO content is estimated by combining the previous results and using the USDA nutritional database. Results: To evaluate the proposed system, a set of 24 multi-food dishes was used. For each dish, 3 pairs of images were taken and for each pair, the system was applied 4 times. The mean absolute percentage error in CHO estimation was 10 ± 12%, which led to a mean absolute error of 6 ± 8 CHO grams for normal-sized dishes. Conclusion: The laboratory experiments demonstrated the feasibility of the GoCARB prototype system since the error was below the initial goal of 20 grams. However, further improvements and evaluation are needed prior launching a system able to meet the inter- and intracultural eating habits.

Multi-Environment Model Estimation for Motility Analysis of Caernorhabditis elegans

The nematode Caenorhabditis elegans is a well-known model organism used to investigate fundamental questions in biology. Motility assays of this small roundworm are designed to study the relationships between genes and behavior. Commonly, motility analysis is used to classify nematode movements and characterize them quantitatively. Over the past years, C. elegans' motility has been studied across a wide range of environments, including crawling on substrates, swimming in fluids, and locomoting through microfluidic substrates. However, each environment often requires customized image processing tools relying on heuristic parameter tuning. In the present study, we propose a novel Multi-Environment Model Estimation (MEME) framework for automated image segmentation that is versatile across various environments. The MEME platform is constructed around the concept of Mixture of Gaussian (MOG) models, where statistical models for both the background environment and the nematode appearance are explicitly learned and used to accurately segment a target nematode. Our method is designed to simplify the burden often imposed on users; here, only a single image which includes a nematode in its environment must be provided for model learning. In addition, our platform enables the extraction of nematode ‘skeletons’ for straightforward motility quantification. We test our algorithm on various locomotive environments and compare performances with an intensity-based thresholding method. Overall, MEME outperforms the threshold-based approach for the overwhelming majority of cases examined. Ultimately, MEME provides researchers with an attractive platform for C. elegans' segmentation and ‘skeletonizing’ across a wide range of motility assays.

Visualization and quantification of air embolism structure by processing postmortem MSCT data.

Venous air embolism (VAE) is an often occurring forensic finding in cases of injury to the head and neck. Whenever found, it has to be appraised in its relation to the cause of death. While visualization and quantification is difficult at traditional autopsy, Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) offer a new potential in the diagnosis of VAE. This paper reports the findings of VAE in four cases of massive head injury examined postmortem by Multislice Computed Tomography (MSCT) prior to autopsy. MSCT data of the thorax were processed using 3D air structure reconstruction software to visualize air embolism within the vascular system. Quantification of VAE was done by multiplying air containing areas on axial 2D images by their reconstruction intervals and then by summarizing the air volumes. Excellent 3D visualization of the air within the vascular system was obtained in all cases, and the intravascular gas volume was quantified.

Streak detection algorithm for space debris detection on optical images.

Any image processing object detection algorithm somehow tries to integrate the object light (Recognition Step) and applies statistical criteria to distinguish objects of interest from other objects or from pure background (Decision Step). There are various possibilities how these two basic steps can be realized, as can be seen in the different proposed detection methods in the literature. An ideal detection algorithm should provide high recognition sensitiv ity with high decision accuracy and require a reasonable computation effort . In reality, a gain in sensitivity is usually only possible with a loss in decision accuracy and with a higher computational effort. So, automatic detection of faint streaks is still a challenge. This paper presents a detection algorithm using spatial filters simulating the geometrical form of possible streaks on a CCD image. This is realized by image convolution. The goal of this method is to generate a more or less perfect match between a streak and a filter by varying the length and orientation of the filters. The convolution answers are accepted or rejected according to an overall threshold given by the ackground statistics. This approach yields as a first result a huge amount of accepted answers due to filters partially covering streaks or remaining stars. To avoid this, a set of additional acceptance criteria has been included in the detection method. All criteria parameters are justified by background and streak statistics and they affect the detection sensitivity only marginally. Tests on images containing simulated streaks and on real images containing satellite streaks show a very promising sensitivity, reliability and running speed for this detection method. Since all method parameters are based on statistics, the true alarm, as well as the false alarm probability, are well controllable. Moreover, the proposed method does not pose any extraordinary demands on the computer hardware and on the image acquisition process.

Fully Automatic Segmentation of Hip CT Images

Automatic segmentation of the hip joint with pelvis and proximal femur surfaces from CT images is essential for orthopedic diagnosis and surgery. It remains challenging due to the narrowness of hip joint space, where the adjacent surfaces of acetabulum and femoral head are hardly distinguished from each other. This chapter presents a fully automatic method to segment pelvic and proximal femoral surfaces from hip CT images. A coarse-to-fine strategy was proposed to combine multi-atlas segmentation with graph-based surface detection. The multi-atlas segmentation step seeks to coarsely extract the entire hip joint region. It uses automatically detected anatomical landmarks to initialize and select the atlas and accelerate the segmentation. The graph based surface detection is to refine the coarsely segmented hip joint region. It aims at completely and efficiently separate the adjacent surfaces of the acetabulum and the femoral head while preserving the hip joint structure. The proposed strategy was evaluated on 30 hip CT images and provided an average accuracy of 0.55, 0.54, and 0.50 mm for segmenting the pelvis, the left and right proximal femurs, respectively.

Professionalisation of sports federations – A multi-level framework for analysing forms, causes and consequences

Introduction: International and national sports federations as well as their member organisations (usually sports clubs) are key actors within the sports system and have a wide range of relationships outside the sports system (e.g. with the state, sponsors, and the media). They are currently facing major challenges such as growing competition in top-­‐level sports, democratisation of sports with “sports for all” and sports as the answer to social problems (integration, education, health, unemployment, etc.). In this context, professionalising sports organisations seems to be an appropriate strategy to face these challenges and solve current problems. This has led to a profound organisational change, particularly within sports federations, characterised by the strengthening of institutional management (managerialism) and the implementation of efficiency-­‐based management instruments and paid staff. In this context the questions arise how sports organisations professionalise and what consequences this may have. Theoretical framework: The goal of our presentation is to review the international literature and develop an appropriate concept of professionalisation in sport federations. Our multi-­‐level approach based on social theory of action integrates the current concepts and perspectives for analysing professionalisation in sports federations. We specify the framework for the following research perspectives: (1) forms, (2) causes and mechanisms, (3) consequences and (4) dynamics, and discuss the reciprocal relations between sports federations and their member organisations in this context. When analysing these different research perspectives, it is important to select or elaborate appropriate theoretical concepts to match the general multi-­‐level framework Discussion: The elaborated multi-­‐level framework for analysing professionalisation in sports federations is able to integrate most of the existing theoretical concepts and therefore, the broad range of endogenous as well as exogenous factors that might influence the professionalisation of sports organisations. Based on the theoretical framework, we can identify several consequences for the methodological design of studies intending to analyse the different perspectives of professionalisation in sports organisations: Data have to be collected on the different levels. Not only the forms of professionalisation and relevant structures of the organisations should be taken into account but also important characteristics of the environment (macro level) as well as members or member organisations, particularly key actors who might play a crucial role in gaining an understanding of professionalisation processes in sports organisations. In order to carry out a complex organisational research design, it seems necessary to focus on case studies – an approach that has become increasingly important in organisational research. Different strategies and methods of data collection have to be used within the case studies (e.g. interviews with experts within the organisations, questionnaire for selected people in the organisation, document analysis). Therefore, qualitative and quantitative research strategies have to be combined.