Utility of multispectral imaging for nuclear classification of routine clinical histopathology imagery

<p>Abstract</p> <p>Background</p> <p>We present an analysis of the utility of multispectral versus standard RGB imagery for routine H&E stained histopathology images, in particular for pixel-level classification of nuclei. Our multispectral imagery has 29 spectral bands, spaced 10 nm within the visual range of 420–700 nm. It has been hypothesized that the additional spectral bands contain further information useful for classification as compared to the 3 standard bands of RGB imagery. We present analyses of our data designed to test this hypothesis.</p> <p>Results</p> <p>For classification using all available image bands, we find the best performance (equal tradeoff between detection rate and false alarm rate) is obtained from either the multispectral or our "ccd" RGB imagery, with an overall increase in performance of 0.79% compared to the next best performing image type. For classification using single image bands, the single best multispectral band (in the red portion of the spectrum) gave a performance increase of 0.57%, compared to performance of the single best RGB band (red). Additionally, red bands had the highest coefficients/preference in our classifiers. Principal components analysis of the multispectral imagery indicates only two significant image bands, which is not surprising given the presence of two stains.</p> <p>Conclusion</p> <p>Our results indicate that multispectral imagery for routine H&E stained histopathology provides minimal additional spectral information for a pixel-level nuclear classification task than would standard RGB imagery.</p

Towards Machine Wald

The past century has seen a steady increase in the need of estimating and predicting complex systems and making (possibly critical) decisions with limited information. Although computers have made possible the numerical evaluation of sophisticated statistical models, these models are still designed \emph{by humans} because there is currently no known recipe or algorithm for dividing the design of a statistical model into a sequence of arithmetic operations. Indeed enabling computers to \emph{think} as \emph{humans} have the ability to do when faced with uncertainty is challenging in several major ways: (1) Finding optimal statistical models remains to be formulated as a well posed problem when information on the system of interest is incomplete and comes in the form of a complex combination of sample data, partial knowledge of constitutive relations and a limited description of the distribution of input random variables. (2) The space of admissible scenarios along with the space of relevant information, assumptions, and/or beliefs, tend to be infinite dimensional, whereas calculus on a computer is necessarily discrete and finite. With this purpose, this paper explores the foundations of a rigorous framework for the scientific computation of optimal statistical estimators/models and reviews their connections with Decision Theory, Machine Learning, Bayesian Inference, Stochastic Optimization, Robust Optimization, Optimal Uncertainty Quantification and Information Based Complexity.Comment: 37 page

Microsome-associated proteome modifications of Arabidopsis seedlings grown on board the International Space Station reveal the possible effect on plants of space stresses other than microgravity

11p.-2 fig.-6 tab.Growing plants in space for using them in bioregenerative life support systems during long-term human spaceflights needs improvement of our knowledge in how plants can adapt to space growth conditions. In a previous study performed on board the International Space Station (GENARA A experiment STS-132) we evaluate the global changes that microgravity can exert on the membrane proteome of Arabidopsis seedlings. Here we report additional data from this space experiment, taking advantage of the availability in the EMCS of a centrifuge to evaluate the effects of cues other than microgravity on the relative distribution of membrane proteins. Among the 1484 membrane proteins quantified, 227 proteins displayed no abundance differences between µ g and 1 g in space, while their abundances significantly differed between 1 g in space and 1 g on ground. A majority of these proteins (176) were over-represented in space samples and mainly belong to families corresponding to protein synthesis, degradation, transport, lipid metabolism, or ribosomal proteins. In the remaining set of 51 proteins that were under-represented in membranes, aquaporins and chloroplastic proteins are majority. These sets of proteins clearly appear as indicators of plant physiological processes affected in space by stressful factors others than microgravity.The authors would like to thank the National Aeronautics and Space Administration (NASA) who successfully performed the spaceflight experiment; they also thank the astronauts for performing the required tasks on board the ISS. We acknowledge the Norwegian User Support and Operations Center team (NUSOC) for the ground and space preparation of the GENARA-A experiment and we thank the European Aeronautic Defense and Space Company (Astrium EADS) for the design and building of the hardware. We also thank the European Space Agency (ESA) and the Centre National d’Etudes Spatiales(CNES) for their scientific and financial support.Peer reviewe

Segmentation of epidermal tissue with histopathological damage in images of haematoxylin and eosin stained human skin.

Background: Digital image analysis has the potential to address issues surrounding traditional histological techniques including a lack of objectivity and high variability, through the application of quantitative analysis. A key initial step in image analysis is the identification of regions of interest. A widely applied methodology is that of segmentation. This paper proposes the application of image analysis techniques to segment skin tissue with varying degrees of histopathological damage. The segmentation of human tissue is challenging as a consequence of the complexity of the tissue structures and inconsistencies in tissue preparation, hence there is a need for a new robust method with the capability to handle the additional challenges materialising from histopathological damage.Methods: A new algorithm has been developed which combines enhanced colour information, created following a transformation to the L*a*b* colourspace, with general image intensity information. A colour normalisation step is included to enhance the algorithm's robustness to variations in the lighting and staining of the input images. The resulting optimised image is subjected to thresholding and the segmentation is fine-tuned using a combination of morphological processing and object classification rules. The segmentation algorithm was tested on 40 digital images of haematoxylin & eosin (H&E) stained skin biopsies. Accuracy, sensitivity and specificity of the algorithmic procedure were assessed through the comparison of the proposed methodology against manual methods.Results: Experimental results show the proposed fully automated methodology segments the epidermis with a mean specificity of 97.7%, a mean sensitivity of 89.4% and a mean accuracy of 96.5%. When a simple user interaction step is included, the specificity increases to 98.0%, the sensitivity to 91.0% and the accuracy to 96.8%. The algorithm segments effectively for different severities of tissue damage.Conclusions: Epidermal segmentation is a crucial first step in a range of applications including melanoma detection and the assessment of histopathological damage in skin. The proposed methodology is able to segment the epidermis with different levels of histological damage. The basic method framework could be applied to segmentation of other epithelial tissues

Ces voyages qui ont changé le monde

International audienc

Diversity and taxonomy of the fern genus Vandenboschia Copel. (Hymenophyllaceae, Polypodiidae) in the Afro-Malagasy region and description of a new species

International audienceVandenboschia radicans (supposedly Neotropical and African), V. speciosa (supposedly European and Macaronesian) and V. gigantea (supposedly from western Indian Ocean) are morphologically close species and often confused in collections and in floras. Moreover, the status of African populations is still strongly debated. We undertook to combine morphological, morphometrics and molecular phylogenetic analyses, on these three species, by also including the Neotropical V. collariata, morphologically close to V. radicans, to try to discriminate putative geographical lineages and discuss their taxonomic status. Our results show that V. collariata is distinct from the other species, and that V. radicans, V. speciosa, V. gigantea and the African specimens remain morphologically and morphometrically indistinguishable. Nevertheless, the Neotropical specimens of V. radicans, V. speciosa and V. gigantea are each genetically strongly distinct and are thus clearly supported as distinct species. African specimens are all grouped into a distinct clade sister to V. gigantea and are distinguished by the presence of a well-developed wing on the stipe, lacking in V. gigantea. Taking into account this stipe feature as well as genetic differences, we describe here Vandenboschia confusa as a new species corresponding to the African populations. The origin of this species in the region is discussed, in addition to the complex taxonomy of European-Macaronesian V. speciosa

Functional alterations of root meristematic cells of Arabidopsis thaliana induced by a simulated microgravity environment

Environmental gravity modulates plant growth and development, and these processes are influenced by the balance between cell proliferation and differentiation in meristems. Meristematic cells are characterized by the coordination between cell proliferation and cell growth, that is, by the accurate regulation of cell cycle progression and the optimal production of biomass for the viability of daughter cells after division. Thus, cell growth is correlated with the rate of ribosome biogenesis and protein synthesis. We investigated the effects of simulated microgravity on cellular functions of the root meristem in a sequential study. Seedlings were grown in a clinostat, a device producing simulated microgravity, for periods between 3 and 10 days. In a complementary study, seedlings were grown in a Random Positioning Machine (RPM) and sampled sequentially after similar periods of growth. Under these conditions, the cell proliferation rate and the regulation of cell cycle progression showed significant alterations, accompanied by a reduction of cell growth. However, the overall size of the root meristem did not change. Analysis of cell cycle phases by flow cytometry showed changes in their proportion and duration, and the expression of the cyclin B1 gene, a marker of entry in mitosis, was decreased, indicating altered cell cycle regulation. With respect to cell growth, the rate of ribosome biogenesis was reduced under simulated microgravity, as shown by morphological and morphometric nucleolar changes and variations in the levels of the nucleolar protein nucleolin. Furthermore, in a nucleolin mutant characterized by disorganized nucleolar structure, the microgravity treatment intensified disorganization. These results show that, regardless of the simulated microgravity device used, a great disruption of meristematic competence was the first response to the environmental alteration detected at early developmental stages. However, longer periods of exposure to simulated microgravity do not produce an intensification of the cellular damages or a detectable developmental alteration in seedlings analyzed at further stages of their growth. This suggests that the secondary response to the gravity alteration is a process of adaptation, whose mechanism is still unknown, which eventually results in viable adult plants

STATISTIQUE Directeur de thèse: Jean-Philippe Vert

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