Techniques for augmenting the visualisation of dynamic raster surfaces

Despite their aesthetic appeal and condensed nature, dynamic raster surface representations such as a temporal series of a landform and an attribute series of a socio-economic attribute of an area, are often criticised for the lack of an effective information delivery and interactivity.In this work, we readdress some of the earlier raised reasons for these limitations -information-laden quality of surface datasets, lack of spatial and temporal continuity in the original data, and a limited scope for a real-time interactivity. We demonstrate with examples that the use of four techniques namely the re-expression of the surfaces as a framework of morphometric features, spatial generalisation, morphing, graphic lag and brushing can augment the visualisation of dynamic raster surfaces in temporal and attribute series

Quality of Radiomic Features in Glioblastoma Multiforme: Impact of Semi-Automated Tumor Segmentation Software.

ObjectiveThe purpose of this study was to evaluate the reliability and quality of radiomic features in glioblastoma multiforme (GBM) derived from tumor volumes obtained with semi-automated tumor segmentation software.Materials and methodsMR images of 45 GBM patients (29 males, 16 females) were downloaded from The Cancer Imaging Archive, in which post-contrast T1-weighted imaging and fluid-attenuated inversion recovery MR sequences were used. Two raters independently segmented the tumors using two semi-automated segmentation tools (TumorPrism3D and 3D Slicer). Regions of interest corresponding to contrast-enhancing lesion, necrotic portions, and non-enhancing T2 high signal intensity component were segmented for each tumor. A total of 180 imaging features were extracted, and their quality was evaluated in terms of stability, normalized dynamic range (NDR), and redundancy, using intra-class correlation coefficients, cluster consensus, and Rand Statistic.ResultsOur study results showed that most of the radiomic features in GBM were highly stable. Over 90% of 180 features showed good stability (intra-class correlation coefficient [ICC] ≥ 0.8), whereas only 7 features were of poor stability (ICC < 0.5). Most first order statistics and morphometric features showed moderate-to-high NDR (4 > NDR ≥1), while above 35% of the texture features showed poor NDR (< 1). Features were shown to cluster into only 5 groups, indicating that they were highly redundant.ConclusionThe use of semi-automated software tools provided sufficiently reliable tumor segmentation and feature stability; thus helping to overcome the inherent inter-rater and intra-rater variability of user intervention. However, certain aspects of feature quality, including NDR and redundancy, need to be assessed for determination of representative signature features before further development of radiomics

A Comparative Study for 2D and 3D Computer-aided Diagnosis Methods for Solitary Pulmonary Nodules

Many computer-aided diagnosis (CAD) methods, including 2D and 3D approaches, have been proposed for solitary pulmonary nodules (SPNs). However, the detection and diagnosis of SPNs remain challenging in many clinical circumstances. One goal of this work is to investigate the relative diagnostic accuracy of 2D and 3D methods. An additional goal is to develop a two-stage approach that combines the simplicity of 2D and the accuracy of 3D methods. The experimental results show statistically significant differences between the diagnostic accuracy of 2D and 3D methods. The results also show that with a very minor drop in diagnostic performance the two-stage approach can significantly reduce the number of nodules needed to be processed by the 3D method, streamlining the computational demand

A morphometric analysis of the genus Terschellingia (nematoda, Linhomoeidae) with redefinition of the genus and key to the species

The cosmopolitan and often ecologically dominant genus Terschellingia (Nematoda, Linhomoeidae), with 37 nominal species, is taxonomically a problematic taxon. Its species show high morphological plasticity, possess few diagnostic morphological characters and identification keys are lacking. A revision of the genus was carried out based on morphological and morphometric data from the literature and from light and electron microscopic observations of specimens collected in Cienfuegos Bay, Caribbean Sea, Cuba. The diagnosis of the genus Terschellingia is emended. Of the current 37 nominal species, 15 are considered as valid species based on morphological characters related to size and position of amphidial fovea, presence/position of cephalic and cervical setae, presence/ size/ shape of oesophageal bulb, shape of spicular apparatus and shape of tail. Tabular and pictorial keys were provided based on these characters. Three sympatric species: T. communis, T. gourbaultae, and T. longicaudata were redescribed based on recently collected Cuban specimens. Each of them showed relatively large differences in body size in comparison with the respective type specimens, suggesting possible variation due to local environmental differences. The highest intraspecific variation pertains for the most widely spread cosmopolitan species T. longicaudata, suggesting that morphological plasticity enhanced adaptation to different environmental conditions. The notable taxonomic inflation within the genus (13 species inquirendae, 9 junior synonyms), probably also present in other highly specious genera of marine nematodes, can lead to an overestimation of the alpha-diversity for some taxa

Investigating the suitability of high content image analysis as a tool to assess the reversibility of foamy alveolar macrophage phenotypes in vitro.

Many potential inhaled medicines fail during development due to the induction of a highly vacuolated or “foamy” alveolar macrophage phenotype response in pre-clinical studies. There is limited understanding if this response to an inhaled stimulus is adverse or adaptive, and additionally if it is a transient or irreversible process. The aim of this study was to evaluate whether high content image analysis could distinguish between different drug-induced foamy macrophage phenotypes and to determine the extent of the reversibility of the foamy phenotypes by assessing morphological changes over time. Alveolar-like macrophages derived from the human monocyte cell line U937 were exposed for 24 h to compounds known to induce a foamy macrophage phenotype (amiodarone, staurosporine) and control compounds that are not known to cause a foamy macrophage phenotype in vitro (fluticasone and salbutamol). Following drug stimulation, the cells were rested in drug-free media for the subsequent 24 or 48 h. Cell morphometric parameters (cellular and nuclear area, vacuoles numbers and size) and phospholipid content were determined using high content image analysis. The foamy macrophage recovery was dependent on the mechanism of action of the inducer compound. Amiodarone toxicity was associated with phospholipid accumulation and morphometric changes were reversed when the stimulus was removed from culture environment. Conversely cells were unable to recover from exposure to staurosporine which initiates the apoptosis pathway. This study shows that high content analysis can discriminate between different phenotypes of foamy macrophages and may contribute to better decision making in the process of new drug development.Peer reviewedFinal Published versio

Highlighting broad-scale morphometric diversity of the seabed using geomorphons

Morphometric diversity is an important component of overall seabed geodiversity. Automated methods for classification of morphometric features (ridges, peaks, valleys etc.) provide a convenient way of classifying large volumes of data in a consistent and repeatable way and a basis for assessing morphometric diversity. Here, we apply ‘geomorphons’, a pattern recognition approach to morphometric feature classification, to 100 m resolution multibeam bathymetry data in the Barents and Norwegian Seas, Norway. The study area spans depths from a few metres to nearly 6000 m across several geological settings. Ten unique morphometric features are delineated by the geomorphon analysis. From these results, we compute the variety of features per 10 km2. This simple ‘geomorphon richness’ measure highlights broad-scale morphometric diversity across the study area. We compare the richness results with terrain attributes and across physiographic regions. Our results provide new regional insights, which together with more detailed information will help guide follow-up surveys as well as identifying diversity hotspots, which may require special management