Experiments with a novel CCD stellar polarimeter

Experiments and observations have been undertaken with "bread-board" equipment to explore the potential of a "ring" stellar polarimeter with a CCD camera, rather than photographic plates used in Treanor's (1968) original instrument. By spreading the polarimetric signal over a large number of pixels on the detector, design prediction suggests that the polarimetric accuracy could be ~Δρ±0.00001 or ±0.001% per frame or even better. Although the photon accumulations suggest that this was achieved, instabilities in the employed crude modulator system provided frame to frame measurements with a greater than expected scatter. Software was developed to reduce the data in a simple way. With a design using more professional components and perhaps with more sophisticated reduction procedures, the full potential of the method should be achievable with the prospect of high precision polarimetry of the brighter stars. As an experimental bonus, the employed CCD chip was found to be free from any measurable polarizational sensitivity

John Berridge: an early evangelical: an examination of his life and works.

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Digital pathology in clinical use: where are we now and what is holding us back?

Whole slide imaging is being used increasingly in research applications and in frozen section, consultation and external quality assurance practice. Digital pathology, when integrated with other digital tools such as barcoding, specimen tracking and digital dictation, can be integrated into the histopathology workflow, from specimen accession to report sign-out. These elements can bring about improvements in the safety, quality and efficiency of a histopathology department. The present paper reviews the evidence for these benefits. We then discuss the challenges of implementing a fully digital pathology workflow, including the regulatory environment, validation of whole slide imaging and the evidence for the design of a digital pathology workstation

A Novel Approach for the Colour Deconvolution of Multiple Histological Stains

Colour Deconvolution (CD) is a commonly used tool in histological medical image analysis that separates histochemical or immunohistochemical stains into their component parts. Traditional CD uses matrix inversion to change the Red, Green and Blue (RGB) channels of an image into a new domain that is representative of reference colours but this limits the total number of stains that can be separated. This is problematic for histological staining protocols that use more than three stains, such as FAST staining. This limitation has restricted the use of multicolour staining in light microscopy. To address this issue, this paper evaluates the use of Non Negative Matrix Factorisation (NNMF) and Non Negative Least Squares (NNLS) to enable the decomposition of multistained histological sections into its source components. It will be shown that NNLS is better suited to imaging modalities such as Whole Slide Image (WSI) scanners and that the multiple staining metrics produced from a single sample are analogous to those generated by applying single reagents to contiguous tissue sections

Stain guided mean-shift filtering in automatic detection of human tissue nuclei

Background: As a critical technique in a digital pathology laboratory, automatic nuclear detection has been investigated for more than one decade. Conventional methods work on the raw images directly whose color/intensity homogeneity within tissue/cell areas are undermined due to artefacts such as uneven staining, making the subsequent binarization process prone to error. This paper concerns detecting cell nuclei automatically from digital pathology images by enhancing the color homogeneity as a pre-processing step. Methods: Unlike previous watershed based algorithms relying on post-processing of the watershed, we present a new method that incorporates the staining information of pathological slides in the analysis. This pre-processing step strengthens the color homogeneity within the nuclear areas as well as the background areas, while keeping the nuclear edges sharp. Proof of convergence for the proposed algorithm is also provided. After pre-processing, Otsu's threshold is applied to binarize the image, which is further segmented via watershed. To keep a proper compromise between removing overlapping and avoiding over-segmentation, a naive Bayes classifier is designed to refine the splits suggested by the watershed segmentation. Results: The method is validated with 10 sets of 1000 × 1000 pathology images of lymphoma from one digital slide. The mean precision and recall rates are 87% and 91%, corresponding to a mean F-score equal to 89%. Standard deviations for these performance indicators are 5.1%, 1.6% and 3.2% respectively. Conclusion: The precision/recall performance obtained indicates that the proposed method outperforms several other alternatives. In particular, for nuclear detection, stain guided mean-shift (SGMS) is more effective than the direct application of mean-shift in pre-processing. Our experiments also show that pre-processing the digital pathology images with SGMS gives better results than conventional watershed algorithms. Nevertheless, as only one type of tissue is tested in this paper, a further study is planned to enhance the robustness of the algorithm so that other types of tissues/stains can also be processed reliably

Leveraging wall-sized high-resolution displays for comparative genomics analyses of copy number variation

The scale of comparative genomics data frequently overwhelms current data visualization methods on conventional (desktop) displays. This paper describes two types of solution that take advantage of wall-sized high-resolution displays (WHirDs), which have orders of magnitude more display real estate (i.e., pixels) than desktop displays. The first allows users to view detailed graphics of copy number variation (CNV) that were output by existing software. A WHirD's resolution allowed a 10× increase in the granularity of bioinformatics output that was feasible for users to visually analyze, and this revealed a pattern that had previously been smoothed out from the underlying data. The second involved interactive visualization software that was innovative because it uses a music score metaphor to lay out CNV data, overcomes a perceptual distortion caused by amplification/deletion thresholds, uses filtering to reduce graphical data overload, and is the first comparative genomics visualization software that is designed to leverage a WHirD's real estate. In a field evaluation, a clinical user discovered a fundamental error in the way their data had been processed, and established confidence in the software by using it to 'find' known genetic patterns in hepatitis C-driven hepatocellular cancer

A 3D Primary Vessel Reconstruction Framework with Serial Microscopy Images

Three dimensional microscopy images present significant potential to enhance biomedical studies. This paper presents an automated method for quantitative analysis of 3D primary vessel structures with histology whole slide images. With registered microscopy images, we identify primary vessels with an improved variational level set framework at each 2D slide. We propose a Vessel Directed Fitting Energy (VDFE) to provide prior information on vessel wall probability in an energy minimization paradigm. We find the optimal vessel cross-section associations along the image sequence with a two-stage procedure. Vessel mappings are first found between each pair of adjacent slides with a similarity function for four association cases. These bi-slide vessel components are further linked by Bayesian Maximum A Posteriori (MAP) estimation where the posterior probability is modeled as a Markov chain. The efficacy of the proposed method is demonstrated with 54 whole slide microscopy images of sequential sections from a human liver

Liver whole slide image analysis for 3D vessel reconstruction

The emergence of digital pathology has enabled numerous quantitative analyses of histopathology structures. However, most pathology image analyses are limited to two-dimensional datasets, resulting in substantial information loss and incomplete interpretation. To address this, we have developed a complete framework for three-dimensional whole slide image analysis and demonstrated its efficacy on 3D vessel structure analysis with liver tissue sections. The proposed workflow includes components on image registration, vessel segmentation, vessel cross-section association, object interpolation, and volumetric rendering. For 3D vessel reconstruction, a cost function is formulated based on shape descriptors, spatial similarity and trajectory smoothness by taking into account four vessel association scenarios. An efficient entropy-based Relaxed Integer Programming (eRIP) method is proposed to identify the optimal inter-frame vessel associations. The reconstructed 3D vessels are both quantitatively and qualitatively validated. Evaluation results demonstrate high efficiency and accuracy of the proposed method, suggesting its promise to support further 3D vessel analysis with whole slide images

Histological 3D reconstruction and in vivo lineage tracing of the human endometrium

Regular menstrual shedding and repair of the endometrial functionalis is unique to humans and higher‐order primates. The current consensus postulates endometrial glands to have a single‐tubular architecture, where multi‐potential stem cells reside in the blind‐ending glandular‐bases. Utilising fixed samples from patients, we have studied the three‐dimensional (3D) micro‐architecture of the human endometrium. We demonstrate that some non‐branching, single, vertical functionalis glands originate from a complex horizontally interconnecting network of basalis glands. The existence of a multipotent endometrial epithelial stem cell capable of regenerating the entire complement of glandular lineages was demonstrated by in vivo lineage tracing, using naturally occurring somatic mitochondrial DNA mutations as clonal markers. Vertical tracking of mutated clones showed that at least one stem‐cell population resides in the basalis glands. These novel findings provide insight into the efficient and scar‐less regenerative potential of the human endometrium