Visual parameter optimisation for biomedical image processing

Background: Biomedical image processing methods require users to optimise input parameters to ensure high quality output. This presents two challenges. First, it is difficult to optimise multiple input parameters for multiple input images. Second, it is difficult to achieve an understanding of underlying algorithms, in particular, relationships between input and output. Results: We present a visualisation method that transforms users’ ability to understand algorithm behaviour by integrating input and output, and by supporting exploration of their relationships. We discuss its application to a colour deconvolution technique for stained histology images and show how it enabled a domain expert to identify suitable parameter values for the deconvolution of two types of images, and metrics to quantify deconvolution performance. It also enabled a breakthrough in understanding by invalidating an underlying assumption about the algorithm. Conclusions: The visualisation method presented here provides analysis capability for multiple inputs and outputs in biomedical image processing that is not supported by previous analysis software. The analysis supported by our method is not feasible with conventional trial-and-error approaches

The Role of Body Size and Shape in Understanding Competitive Interactions within a Community of Neotropical Dung Beetles

Geometric morphometrics is helpful for understanding how body size and body shape influence the strength of inter-specific competitive interactions in a community. Dung beetles, characterized by their use of decomposing organic material, provide a useful model for understanding the structuring of ecological communities and the role of competition based on their size and morphology. The relationship between body size and shape in a dung beetle community from the Atlantic Forest in Serra do Japi, Brazil was analyzed for 39 species. Fifteen anatomical landmarks on three-dimensional Cartesian coordinates were used to describe both the shape and the size of the body of each species on the basis of the centroid located along homologous points in all of the species. The first vector of a principal components analysis explained 38.5% of the morphological variation among species, and represents a gradient of body shape from elongated, flattened bodies with narrow abdomen to rounded or convex bodies. The second component explained 17.8% of the remaining variation in body shape, which goes from species with an abdomen that is larger than the elytra to species with constricted abdomens and large elytra. The relationship between body size and shape was analyzed separately for diurnal and nocturnal species. In both guilds not only were there differences in body size, but also in body shape, suggesting a reduction in their level of competition

Visual Performance Fields: Frames of Reference

Performance in most visual discrimination tasks is better along the horizontal than the vertical meridian (Horizontal-Vertical Anisotropy, HVA), and along the lower than the upper vertical meridian (Vertical Meridian Asymmetry, VMA), with intermediate performance at intercardinal locations. As these inhomogeneities are prevalent throughout visual tasks, it is important to understand the perceptual consequences of dissociating spatial reference frames. In all studies of performance fields so far, allocentric environmental references and egocentric observer reference frames were aligned. Here we quantified the effects of manipulating head-centric and retinotopic coordinates on the shape of visual performance fields. When observers viewed briefly presented radial arrays of Gabors and discriminated the tilt of a target relative to homogeneously oriented distractors, performance fields shifted with head tilt (Experiment 1), and fixation (Experiment 2). These results show that performance fields shift in-line with egocentric referents, corresponding to the retinal location of the stimulus

What scans we will read: imaging instrumentation trends in clinical oncology

Oncological diseases account for a significant portion of the burden on public healthcare systems with associated costs driven primarily by complex and long-lasting therapies. Through the visualization of patient-specific morphology and functional-molecular pathways, cancerous tissue can be detected and characterized non- invasively, so as to provide referring oncologists with essential information to support therapy management decisions. Following the onset of stand-alone anatomical and functional imaging, we witness a push towards integrating molecular image information through various methods, including anato-metabolic imaging (e.g., PET/ CT), advanced MRI, optical or ultrasound imaging. This perspective paper highlights a number of key technological and methodological advances in imaging instrumentation related to anatomical, functional, molecular medicine and hybrid imaging, that is understood as the hardware-based combination of complementary anatomical and molecular imaging. These include novel detector technologies for ionizing radiation used in CT and nuclear medicine imaging, and novel system developments in MRI and optical as well as opto-acoustic imaging. We will also highlight new data processing methods for improved non-invasive tissue characterization. Following a general introduction to the role of imaging in oncology patient management we introduce imaging methods with well-defined clinical applications and potential for clinical translation. For each modality, we report first on the status quo and point to perceived technological and methodological advances in a subsequent status go section. Considering the breadth and dynamics of these developments, this perspective ends with a critical reflection on where the authors, with the majority of them being imaging experts with a background in physics and engineering, believe imaging methods will be in a few years from now. Overall, methodological and technological medical imaging advances are geared towards increased image contrast, the derivation of reproducible quantitative parameters, an increase in volume sensitivity and a reduction in overall examination time. To ensure full translation to the clinic, this progress in technologies and instrumentation is complemented by progress in relevant acquisition and image-processing protocols and improved data analysis. To this end, we should accept diagnostic images as “data”, and – through the wider adoption of advanced analysis, including machine learning approaches and a “big data” concept – move to the next stage of non-invasive tumor phenotyping. The scans we will be reading in 10 years from now will likely be composed of highly diverse multi- dimensional data from multiple sources, which mandate the use of advanced and interactive visualization and analysis platforms powered by Artificial Intelligence (AI) for real-time data handling by cross-specialty clinical experts with a domain knowledge that will need to go beyond that of plain imaging

A review of characterisation requirements for in-line prefermenters : Paper 1 : Wastewater characterisation

The impact of wastewater prefermentation cannot be evaluated in isolation, based only on the local prefermenter biodegradable organic matter production rate, as represented by the volatile fatty acids concentration increase across the prefermenter. The nutrients ratio changes and solids removal variations from the raw to the settled sewage must be taken into account when considering the suitability of the prefermented wastewater for downstream biological nutrient removal processes. The raw and settled wastewater must, therefore, be characterised according to component nutrients and solids fractions. This paper reviews related wastewater characteristics required for in-line prefermenters, to establish simple strategies on which in-line prefermenter evaluations could be based. WaterSA Vol.27(3) 2001: 405-41

A review of characterisation requirements for in-line prefermenters : Paper 2 : Process characterisation

The operational factors having a significant effect on in-line prefermentation efficiency include the sludge recycle rate and the subsequent sludge elutriation rate, solids concentrations and retention times. The prefermenter configuration employed is a determining factor, which allows for some degree of operational flexibility. Side-stream and multiple tank systems are superior in this regard and outnumber the use of in-line single tank prefermenters, which are mainly employed due to lower space and capital cost requirements. This paper reviews the basic design and monitoring requirements for in-line prefermenters, to establish simple strategies on which prefermenter evaluations could be based. WaterSA Vol.27(3) 2001: 413-42

Spectrophotometric determination of pKa values for fluorescein using activity coefficient corrections

The absorbance of the organic water tracer compound fluorescein is known to be pH dependent but differences between the reported PKa values make it difficult to predict these absorbance changes. A new pKa determination method, which incorporated activity corrections, was used to calculate the pKa values of fluorescein. Several published pKa values were re-evaluated and were in agreement once activity corrections were applied. WaterSA Vol.28(4) 2002: 395-40

The conservative behaviour of fluorescein

Failure to account for fluorescein absorbance changes with pH may be responsible for some of the apparent non-conservative behaviour of this easily detectable tracer compound. While it is possible to calculate an accurate absorptivity value for fluorescein at every pH, this calculation is not necessary if the sample pH is increased above pH 9 before measuring the absorbance. Intense sunlight degrades fluorescein quickly but even hot samples are stable if kept in the dark. WaterSA Vol.28(4) 2002: 403-40