Multi-scale colorectal tumour segmentation using a novel coarse to fine strategy

This paper addresses the problem of colorectal tumour segmentation in complex real world imagery. For efficient segmentation, a multi-scale strategy is developed for extracting the potentially cancerous region of interest (ROI) based on colour histograms while searching for the best texture resolution. To achieve better segmentation accuracy, we apply a novel bag-of-visual-words method based on rotation invariant raw statistical features and random projection based l2-norm sparse representation to classify tumour areas in histopathology images. Experimental results on 20 real world digital slides demonstrate that the proposed algorithm results in better recognition accuracy than several state of the art segmentation techniques.

Challenging assumptions of future coastal habitat development around the UK

One habitat management requirement forced by 21st century relative sea-level rise (RSLR), will be the need to re-comprehend the dimensions of long-term transgressive behaviour of coastal systems being forced by such RSLR. Fresh approaches to the conceptual modelling and subsequent implementation of new coastal and peri-marine habitats will be required. There is concern that existing approaches to forecasting coastal systems development (and by implication their associated scarce coastal habitats) over the next century depend on a certain premise of orderly spatial succession of habitats. This assumption is shown to be questionable given the possible future rates of RSLR, magnitude of shoreline retreat and the lack of coastal sediment to maintain the protective morphologies to low-energy coastal habitats. Of these issues, sediment deficiency is regarded as one of the major problem for future habitat development. Examples of contemporary behaviour of UK coasts show evidence of coastal sediment starvation resulting from relatively stable RSLR, anthropogenic sealing of coastal sources, and intercepted coastal sediment pathways, which together force segmentation of coastal systems. From these examples key principles are deduced which may prejudice the existence of future habitats: accelerated future sediment demand due to RSLR may not be met by supply and, if short- to medium-term hold-the-line policies predominate, long-term strategies for managed realignment and habitat enhancement may prove impossible goals. Methods of contemporary sediment husbandry may help sustain some habitats in place but otherwise, instead of integrated coastal organization, managers may need to consider coastal breakdown, segmentation and habitat reduction as the basis of 21st century coastal evolution and planning.

Observational Evidence for Mode Coupling in the Chromospheric Network

Oscillations in network bright points (NBPs) are studied at a variety of chromospheric heights. In particular, the three-dimensional variation of NBP oscillations is studied using image segmentation and cross-correlation analysis between images taken in light of Ca II K3, Ha core, Mg I b2, and Mg I b1-0.4 Å. Wavelet analysis is used to isolate wave packets in time and to search for height-dependent time delays that result from upward- or downward-directed traveling waves. In each NBP studied, we find evidence for kink-mode waves (1.3, 1.9 mHz), traveling up through the chromosphere and coupling with sausage-mode waves (2.6, 3.8 mHz). This provides a means for depositing energy in the upper chromosphere. We also find evidence for other upward- and downward-propagating waves in the 1.3-4.6 mHz range. Some oscillations do not correspond to traveling waves, and we attribute these to waves generated in neighboring regions.

Transparency Proposals for European Sovereign Bond Markets

The debate over the possible extension of transparency regulation in Europe to include sovereign bonds has opened up a number of other issues in need of serious consideration. One such issue is the appropriateness of the entire infrastructure supporting the trading of European sovereign bonds. In recent years sovereign issuers have supported the development of an electronic inter-dealer market but have remained unconcerned with the opacity of dealer-to-customer trading. The degree of segmentation in this market is high relative to what exists in nearly all other financial markets. This paper explores why European sovereign bond markets have developed in such a segmented way and considers how this structure could be altered to improve transparency without adversely affecting liquidity, efficiency or the benefits enjoyed by primary dealers and issuers. It is suggested that the structure of the market could be improved greatly if the largest and most active investors were permitted access to the inter-dealer electronic trading platforms. This would solve a number of market imperfections and increase the proportion of market activity that is conducted in a transparent way. The paper argues that sovereign issuers in Europe have the means to provide incentives that would influence dealers to support reduced segmentation. Some practical examples of how this could be achieved are provided and the potential benefits are outlined.

An FPGA Based Coprocessor for GLCM and Haralick Texture Features and Their Application in Prostate Cancer Classification

Grey Level Co-occurrence Matrix (GLCM), one of the best known tool for texture analysis, estimates image properties related to second-order statistics. These image properties commonly known as Haralick texture features can be used for image classification, image segmentation, and remote sensing applications. However, their computations are highly intensive especially for very large images such as medical ones. Therefore, methods to accelerate their computations are highly desired. This paper proposes the use of programmable hardware to accelerate the calculation of GLCM and Haralick texture features. Further, as an example of the speedup offered by programmable logic, a multispectral computer vision system for automatic diagnosis of prostatic cancer has been implemented. The performance is then compared against a microprocessor based solution.

Non-stationary variogram models for geostatistical sampling optimisation: An empirical investigation using elevation data

A problem with use of the geostatistical Kriging error for optimal sampling design is that the design does not adapt locally to the character of spatial variation. This is because a stationary variogram or covariance function is a parameter of the geostatistical model. The objective of this paper was to investigate the utility of non-stationary geostatistics for optimal sampling design. First, a contour data set of Wiltshire was split into 25 equal sub-regions and a local variogram was predicted for each. These variograms were fitted with models and the coefficients used in Kriging to select optimal sample spacings for each sub-region. Large differences existed between the designs for the whole region (based on the global variogram) and for the sub-regions (based on the local variograms). Second, a segmentation approach was used to divide a digital terrain model into separate segments. Segment-based variograms were predicted and fitted with models. Optimal sample spacings were then determined for the whole region and for the sub-regions. It was demonstrated that the global design was inadequate, grossly over-sampling some segments while under-sampling others.

Radiowave propagation from a tissue-implanted source at 418 MHz and 916.5 MHz

Tissue-implanted ultra-high frequency (UHF) radio devices are being employed in both humans and animals for telemetry and telecommand applications, This paper describes the experimental measurement and electromagnetic modeling of propagation from 418-MHz and 916.5-MHz sources placed in the human vagina. Whole-body homogeneous and semi-segmented software models were constructed using data from the Visible Human Project. Bodyworn radiation efficiencies for a vaginally placed 418-MHz source were calculated using finite-difference time-domain and ranged between 1.6% and 3.4% (corresponding to net body losses of between 14.7 and 18.0 dB), Greater losses were encountered at 916.5 MHz, with efficiencies between 0.36% and 0.46% (net body loss ranging between 23.4 and 24.4 dB), Practical measurements were in good agreement with simulations, to within 2 dB at 418 MHz and 3 dB at 916.5 MHz. The degree of tissue-segmentation for whole-body models was found to have a minimal effect on calculated azimuthal radiation patterns and bodyworn radiation efficiency, provided the region surrounding the implanted source was sufficiently detailed.

Assisted Diagnosis of Cervical Intraepithelial Neoplasia (CIN)

This paper introduces an automated computer- assisted system for the diagnosis of cervical intraepithelial neoplasia (CIN) using ultra-large cervical histological digital slides. The system contains two parts: the segmentation of squamous epithelium and the diagnosis of CIN. For the segmentation, to reduce processing time, a multiresolution method is developed. The squamous epithelium layer is first segmented at a low (2X) resolution. The boundaries are further fine tuned at a higher (20X) resolution. The block-based segmentation method uses robust texture feature vectors in combination with support vector machines (SVMs) to perform classification. Medical rules are finally applied. In testing, segmentation using 31 digital slides achieves 94.25% accuracy. For the diagnosis of CIN, changes in nuclei structure and morphology along lines perpendicular to the main axis of the squamous epithelium are quantified and classified. Using multi-category SVM, perpendicular lines are classified into Normal, CIN I, CIN II, and CIN III. The robustness of the system in term of regional diagnosis is measured against pathologists' diagnoses and inter-observer variability between two pathologists is considered. Initial results suggest that the system has potential as a tool both to assist in pathologists' diagnoses, and in training.

Robust Extraction of Text from Camera Images using Colour and Spatial Information Simultaneously

The importance and use of text extraction from camera based coloured scene images is rapidly increasing with time. Text within a camera grabbed image can contain a huge amount of meta data about that scene. Such meta data can be useful for identification, indexing and retrieval purposes. While the segmentation and recognition of text from document images is quite successful, detection of coloured scene text is a new challenge for all camera based images. Common problems for text extraction from camera based images are the lack of prior knowledge of any kind of text features such as colour, font, size and orientation as well as the location of the probable text regions. In this paper, we document the development of a fully automatic and extremely robust text segmentation technique that can be used for any type of camera grabbed frame be it single image or video. A new algorithm is proposed which can overcome the current problems of text segmentation. The algorithm exploits text appearance in terms of colour and spatial distribution. When the new text extraction technique was tested on a variety of camera based images it was found to out perform existing techniques (or something similar). The proposed technique also overcomes any problems that can arise due to an unconstraint complex background. The novelty in the works arises from the fact that this is the first time that colour and spatial information are used simultaneously for the purpose of text extraction.

Language-universal Sensory Deficits in Developmental Dyslexia: English, Spanish, and Chinese

Studies in sensory neuroscience reveal the critical importance of accurate sensory perception for cognitive development. There is considerable debate concerning the possible sensory correlates of phonological processing, the primary cognitive risk factor for developmental dyslexia. Across languages, children with dyslexia have a specific difficulty with the neural representation of the phonological structure of speech. The identification of a robust sensory marker of phonological difficulties would enable early identification of risk for developmental dyslexia and early targeted intervention. Here, we explore whether phonological processing difficulties are associated with difficulties in processing acoustic cues to speech rhythm. Speech rhythm is used across languages by infants to segment the speech stream into words and syllables. Early difficulties in perceiving auditory sensory cues to speech rhythm and prosody could lead developmentally to impairments in phonology. We compared matched samples of children with and without dyslexia, learning three very different spoken and written languages, English, Spanish, and Chinese. The key sensory cue measured was rate of onset of the amplitude envelope (rise time), known to be critical for the rhythmic timing of speech. Despite phonological and orthographic differences, for each language, rise time sensitivity was a significant predictor of phonological awareness, and rise time was the only consistent predictor of reading acquisition. The data support a language-universal theory of the neural basis of developmental dyslexia on the basis of rhythmic perception and syllable segmentation. They also suggest that novel remediation strategies on the basis of rhythm and music may offer benefits for phonological and linguistic development.

A TMA De-Arraying Method for High Throughput Biomarker Discovery in Tissue Research

Background: Tissue MicroArrays (TMAs) represent a potential high-throughput platform for the analysis and discovery of tissue biomarkers. As TMA slides are produced manually and subject to processing and sectioning artefacts, the layout of TMA cores on the final slide and subsequent digital scan (TMA digital slide) is often disturbed making it difficult to associate cores with their original position in the planned TMA map. Additionally, the individual cores can be greatly altered and contain numerous irregularities such as missing cores, grid rotation and stretching. These factors demand the development of a robust method for de-arraying TMAs which identifies each TMA core, and assigns them to their appropriate coordinates on the constructed TMA slide.

Methodology: This study presents a robust TMA de-arraying method consisting of three functional phases: TMA core segmentation, gridding and mapping. The segmentation of TMA cores uses a set of morphological operations to identify each TMA core. Gridding then utilises a Delaunay Triangulation based method to find the row and column indices of each TMA core. Finally, mapping correlates each TMA core from a high resolution TMA whole slide image with its name within a TMAMap.

Conclusion: This study describes a genuine robust TMA de-arraying algorithm for the rapid identification of TMA cores from digital slides. The result of this de-arraying algorithm allows the easy partition of each TMA core for further processing. Based on a test group of 19 TMA slides (3129 cores), 99.84% of cores were segmented successfully, 99.81% of cores were gridded correctly and 99.96% of cores were mapped with their correct names via TMAMaps. The gridding of TMA cores were also extensively tested using a set of 113 pseudo slide (13,536 cores) with a variety of irregular grid layouts including missing cores, rotation and stretching. 100% of the cores were gridded correctly.