Uncertainty quantification in medical image segmentation with normalizing flows

Medical image segmentation is inherently an ambiguous task due to factors such as partial volumes and variations in anatomical definitions. While in most cases the segmentation uncertainty is around the border of structures of interest, there can also be considerable inter-rater differences. The class of conditional variational autoencoders (cVAE) offers a principled approach to inferring distributions over plausible segmentations that are conditioned on input images. Segmentation uncertainty estimated from samples of such distributions can be more informative than using pixel level probability scores. In this work, we propose a novel conditional generative model that is based on conditional Normalizing Flow (cFlow). The basic idea is to increase the expressivity of the cVAE by introducing a cFlow transformation step after the encoder. This yields improved approximations of the latent posterior distribution, allowing the model to capture richer segmentation variations. With this we show that the quality and diversity of samples obtained from our conditional generative model is enhanced. Performance of our model, which we call cFlow Net, is evaluated on two medical imaging datasets demonstrating substantial improvements in both qualitative and quantitative measures when compared to a recent cVAE based model.Comment: 12 pages. Accepted to be presented at 11th International Workshop on Machine Learning in Medical Imaging. Source code will be updated at https://github.com/raghavian/cFlo

Quantification and analysis of icebergs in a tidewater glacier fjord using an object-based approach

Tidewater glaciers are glaciers that terminate in, and calve icebergs into, the ocean. In addition to the influence that tidewater glaciers have on physical and chemical oceanography, floating icebergs serve as habitat for marine animals such as harbor seals (Phoca vitulina richardii). The availability and spatial distribution of glacier ice in the fjords is likely a key environmental variable that influences the abundance and distribution of selected marine mammals; however, the amount of ice and the fine-scale characteristics of ice in fjords have not been systematically quantified. Given the predicted changes in glacier habitat, there is a need for the development of methods that could be broadly applied to quantify changes in available ice habitat in tidewater glacier fjords. We present a case study to describe a novel method that uses object-based image analysis (OBIA) to classify floating glacier ice in a tidewater glacier fjord from high-resolution aerial digital imagery. Our objectives were to (i) develop workflows and rule sets to classify high spatial resolution airborne imagery of floating glacier ice; (ii) quantify the amount and fine-scale characteristics of floating glacier ice; (iii) and develop processes for automating the object-based analysis of floating glacier ice for large number of images from a representative survey day during June 2007 in Johns Hopkins Inlet (JHI), a tidewater glacier fjord in Glacier Bay National Park, southeastern Alaska. On 18 June 2007, JHI was comprised of brash ice ([Formula: see text] = 45.2%, SD = 41.5%), water ([Formula: see text] = 52.7%, SD = 42.3%), and icebergs ([Formula: see text] = 2.1%, SD = 1.4%). Average iceberg size per scene was 5.7 m2 (SD = 2.6 m2). We estimate the total area (± uncertainty) of iceberg habitat in the fjord to be 455,400 ± 123,000 m2. The method works well for classifying icebergs across scenes (classification accuracy of 75.6%); the largest classification errors occur in areas with densely-packed ice, low contrast between neighboring ice cover, or dark or sediment-covered ice, where icebergs may be misclassified as brash ice about 20% of the time. OBIA is a powerful image classification tool, and the method we present could be adapted and applied to other ice habitats, such as sea ice, to assess changes in ice characteristics and availability

Production of phi mesons at mid-rapidity in sqrt(s_NN) = 200 GeV Au+Au collisions at RHIC

We present the first results of meson production in the K^+K^- decay channel from Au+Au collisions at sqrt(s_NN) = 200 GeV as measured at mid-rapidity by the PHENIX detector at RHIC. Precision resonance centroid and width values are extracted as a function of collision centrality. No significant variation from the PDG accepted values is observed. The transverse mass spectra are fitted with a linear exponential function for which the derived inverse slope parameter is seen to be constant as a function of centrality. These data are also fitted by a hydrodynamic model with the result that the freeze-out temperature and the expansion velocity values are consistent with the values previously derived from fitting single hadron inclusive data. As a function of transverse momentum the collisions scaled peripheral.to.central yield ratio RCP for the is comparable to that of pions rather than that of protons. This result lends support to theoretical models which distinguish between baryons and mesons instead of particle mass for explaining the anomalous proton yield.Comment: 326 authors, 24 pages text, 23 figures, 6 tables, RevTeX 4. To be submitted to Physical Review C as a regular article. Plain text data tables for the points plotted in figures for this and previous PHENIX publications are (or will be) publicly available at http://www.phenix.bnl.gov/papers.htm

A Genome-Wide Association Study Identifies Novel Alleles Associated with Hair Color and Skin Pigmentation

We conducted a multi-stage genome-wide association study of natural hair color in more than 10,000 men and women of European ancestry from the United States and Australia. An initial analysis of 528,173 single nucleotide polymorphisms (SNPs) genotyped on 2,287 women identified IRF4 and SLC24A4 as loci highly associated with hair color, along with three other regions encompassing known pigmentation genes. We confirmed these associations in 7,028 individuals from three additional studies. Across these four studies, SLC24A4 rs12896399 and IRF4 rs12203592 showed strong associations with hair color, with p = 6.0×10−62 and p = 7.46×10−127, respectively. The IRF4 SNP was also associated with skin color (p = 6.2×10−14), eye color (p = 6.1×10−13), and skin tanning response to sunlight (p = 3.9×10−89). A multivariable analysis pooling data from the initial GWAS and an additional 1,440 individuals suggested that the association between rs12203592 and hair color was independent of rs1540771, a SNP between the IRF4 and EXOC2 genes previously found to be associated with hair color. After adjustment for rs12203592, the association between rs1540771 and hair color was not significant (p = 0.52). One variant in the MATP gene was associated with hair color. A variant in the HERC2 gene upstream of the OCA2 gene showed the strongest and independent association with hair color compared with other SNPs in this region, including three previously reported SNPs. The signals detected in a region around the MC1R gene were explained by MC1R red hair color alleles. Our results suggest that the IRF4 and SLC24A4 loci are associated with human hair color and skin pigmentation

Convergent genetic linkage and associations to language, speech and reading measures in families of probands with Specific Language Impairment

We analyzed genetic linkage and association of measures of language, speech and reading phenotypes to candidate regions in a single set of families ascertained for SLI. Sib-pair and family-based analyses were carried out for candidate gene loci for Reading Disability (RD) on chromosomes 1p36, 3p12-q13, 6p22, and 15q21, and the speech-language candidate region on 7q31 in a sample of 322 participants ascertained for Specific Language Impairment (SLI). Replication or suggestive replication of linkage was obtained in all of these regions, but the evidence suggests that the genetic influences may not be identical for the three domains. In particular, linkage analysis replicated the influence of genes on chromosome 6p for all three domains, but association analysis indicated that only one of the candidate genes for reading disability, KIAA0319, had a strong effect on language phenotypes. The findings are consistent with a multiple gene model of the comorbidity between language impairments and reading disability and have implications for neurocognitive developmental models and maturational processes

Interleukin-17A Mediates Acquired Immunity to Pneumococcal Colonization

Although anticapsular antibodies confer serotype-specific immunity to pneumococci, children increase their ability to clear colonization before these antibodies appear, suggesting involvement of other mechanisms. We previously reported that intranasal immunization of mice with pneumococci confers CD4+ T cell–dependent, antibody- and serotype-independent protection against colonization. Here we show that this immunity, rather than preventing initiation of carriage, accelerates clearance over several days, accompanied by neutrophilic infiltration of the nasopharyngeal mucosa. Adoptive transfer of immune CD4+ T cells was sufficient to confer immunity to naïve RAG1−/− mice. A critical role of interleukin (IL)-17A was demonstrated: mice lacking interferon-γ or IL-4 were protected, but not mice lacking IL-17A receptor or mice with neutrophil depletion. In vitro expression of IL-17A in response to pneumococci was assayed: lymphoid tissue from vaccinated mice expressed significantly more IL-17A than controls, and IL-17A expression from peripheral blood samples from immunized mice predicted protection in vivo. IL-17A was elicited by pneumococcal stimulation of tonsillar cells of children or adult blood but not cord blood. IL-17A increased pneumococcal killing by human neutrophils both in the absence and in the presence of antibodies and complement. We conclude that IL-17A mediates pneumococcal immunity in mice and probably in humans; its elicitation in vitro could help in the development of candidate pneumococcal vaccines

J/psi production from proton-proton collisions at sqrt(s) = 200 GeV

J/psi production has been measured in proton-proton collisions at sqrt(s)= 200 GeV over a wide rapidity and transverse momentum range by the PHENIX experiment at RHIC. Distributions of the rapidity and transverse momentum, along with measurements of the mean transverse momentum and total production cross section are presented and compared to available theoretical calculations. The total J/psi cross section is 3.99 +/- 0.61(stat) +/- 0.58(sys) +/- 0.40(abs) micro barns. The mean transverse momentum is 1.80 +/- 0.23(stat) +/- 0.16(sys) GeV/c.Comment: 326 authors, 6 pages text, 4 figures, 1 table, RevTeX 4. To be submitted to PRL. Plain text data tables for the points plotted in figures for this and previous PHENIX publications are (or will be) publicly available at http://www.phenix.bnl.gov/papers.htm

Measurement of Single Electron Event Anisotropy in Au+Au Collisions at sqrt(s_NN) = 200 GeV

The transverse momentum dependence of the azimuthal anisotropy parameter v_2, the second harmonic of the azimuthal distribution, for electrons at mid-rapidity (|eta| < 0.35) has been measured with the PHENIX detector in Au+Au collisions at sqrt(s_NN) = 200 GeV. The measurement was made with respect to the reaction plane defined at high rapidities (|eta| = 3.1 -- 3.9). From the result we have measured the v_2 of electrons from heavy flavor decay after subtraction of the v_2 of electrons from other sources such as photon conversions and Dalitz decay from light neutral mesons. We observe a non-zero single electron v_2 with a 90% confidence level in the intermediate p_T region.Comment: 330 authors, 11 pages text, RevTeX4, 9 figures, 1 tables. Submitted to Physical Review C. Plain text data tables for the points plotted in figures for this and previous PHENIX publications are (or will be) publicly available at http://www.phenix.bnl.gov/papers.htm