Severity classification of ground-glass opacity via 2-D convolutional neural network and lung CT scans: a 3-day exploration

Ground-glass opacity is a hallmark of numerous lung diseases, including patients with COVID19 and pneumonia, pulmonary fibrosis, and tuberculosis. This brief note presents experimental results of a proof-of-concept framework that got implemented and tested over three days as driven by the third challenge entitled "COVID-19 Competition", hosted at the AI-Enabled Medical Image Analysis Workshop of the 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2023). Using a newly built virtual environment (created on March 17, 2023), we investigated various pre-trained two-dimensional convolutional neural networks (CNN) such as Dense Neural Network, Residual Neural Networks (ResNet), and Vision Transformers, as well as the extent of fine-tuning. Based on empirical experiments, we opted to fine-tune them using ADAM's optimization algorithm with a standard learning rate of 0.001 for all CNN architectures and apply early-stopping whenever the validation loss reached a plateau. For each trained CNN, the model state with the best validation accuracy achieved during training was stored and later reloaded for new classifications of unseen samples drawn from the validation set provided by the challenge organizers. According to the organizers, few of these 2D CNNs yielded performance comparable to an architecture that combined ResNet and Recurrent Neural Network (Gated Recurrent Units). As part of the challenge requirement, the source code produced during the course of this exercise is posted at https://github.com/lisatwyw/cov19. We also hope that other researchers may find this light prototype consisting of few Python files based on PyTorch 1.13.1 and TorchVision 0.14.1 approachable

Random walker image registration with inverse consistency

One important property of a registration solution is in-verse consistency. While often overlooked, this property is critical in many medical applications, including radiation-therapy treatment planning and unbiased atlas-construction. In this paper, we propose a novel extension to the graph-based random walker image registration (RWIR) algorithm to ensure its inverse consistency. In contrast to many exist-ing inverse-consistent algorithms, where two bi-directional transformations are independently sought and subsequently averaged, we calculate both transformations simultaneously by performing a constrained graph labeling in a common domain onto which both images are mapped, and employ a set of coupled labels so that both transformations are computed within a single optimization step. As our results on synthetic and real problems involving cardiac, thigh and brain images demonstrate, our method not only improved in-verse consistency of RWIR, but also statistically significantly improved its accuracy. Comparison to another state-of-the-art symmetric algorithm on various datasets also gave highly encouraging results. 1

Relation of statin use with non-melanoma skin cancer: prospective results from the Women\u27s Health Initiative.

BACKGROUND: The relationship between statin use and non-melanoma skin cancer (NMSC) is unclear with conflicting findings in literature. Data from the Women\u27s Health Initiative (WHI) Observational Study and WHI Clinical Trial were used to investigate the prospective relationship between statin use and NMSC in non-Hispanic white (NHW) postmenopausal women. METHODS: The WHI study enrolled women aged 50-79 years at 40 US centres. Among 133 541 NHW participants, 118 357 with no cancer history at baseline and complete medication/covariate data comprised the analytic cohort. The association of statin use (baseline, overall as a time-varying variable, duration, type, potency, lipophilicity) and NMSC incidence was determined using random-effects logistic regression models. RESULTS: Over a mean of 10.5 years of follow-up, we identified 11 555 NMSC cases. Compared with participants with no statin use, use of any statin at baseline was associated with significantly increased NMSC incidence (adjusted odds ratio (ORadj) 1.21; 95% confidence interval (CI): 1.07-1.35)). In particular, lovastatin (OR 1.52; 95% CI: 1.08-2.16), simvastatin (OR 1.38; 95% CI: 1.12-1.69), and lipophilic statins (OR 1.39; 95% CI: 1.18-1.64) were associated with higher NMSC risk. Low and high, but not medium, potency statins were associated with higher NMSC risk. No significant effect modification of the statin-NMSC relationship was found for age, BMI, smoking, solar irradiation, vitamin D use, and skin cancer history. CONCLUSIONS: Use of statins, particularly lipophilic statins, was associated with increased NMSC risk in postmenopausal white women in the WHI cohort. The lack of duration-effect relationship points to possible residual confounding. Additional prospective research should further investigate this relationship.British Journal of Cancer advance online publication, 7 January 2016; doi:10.1038/bjc.2015.376 www.bjcancer.com

System size and energy dependence of near-side di-hadron correlations

Two-particle azimuthal ($\Delta\phi$) and pseudorapidity ($\Delta\eta$) correlations using a trigger particle with large transverse momentum ($p_T$) in $d$+Au, Cu+Cu and Au+Au collisions at $\sqrt{s_{{NN}}}$ =\xspace 62.4 GeV and 200~GeV from the STAR experiment at RHIC are presented. The \ns correlation is separated into a jet-like component, narrow in both $\Delta\phi$ and $\Delta\eta$, and the ridge, narrow in $\Delta\phi$ but broad in $\Delta\eta$. Both components are studied as a function of collision centrality, and the jet-like correlation is studied as a function of the trigger and associated $p_T$. The behavior of the jet-like component is remarkably consistent for different collision systems, suggesting it is produced by fragmentation. The width of the jet-like correlation is found to increase with the system size. The ridge, previously observed in Au+Au collisions at $\sqrt{s_{{NN}}}$ = 200 GeV, is also found in Cu+Cu collisions and in collisions at $\sqrt{s_{{NN}}}$ =\xspace 62.4 GeV, but is found to be substantially smaller at $\sqrt{s_{{NN}}}$ =\xspace 62.4 GeV than at $\sqrt{s_{{NN}}}$ = 200 GeV for the same average number of participants ($\langle N_{\mathrm{part}}\rangle$). Measurements of the ridge are compared to models.Comment: 17 pages, 14 figures, submitted to Phys. Rev.

Isolation of Flow and Nonflow Correlations by Two- and Four-Particle Cumulant Measurements of Azimuthal Harmonics in sNN=\sqrt{s_{_{\rm NN}}} = 200 GeV Au+Au Collisions

A data-driven method was applied to measurements of Au+Au collisions at $\sqrt{s_{_{\rm NN}}} =$ 200 GeV made with the STAR detector at RHIC to isolate pseudorapidity distance $\Delta\eta$-dependent and $\Delta\eta$-independent correlations by using two- and four-particle azimuthal cumulant measurements. We identified a component of the correlation that is $\Delta\eta$-independent, which is likely dominated by anisotropic flow and flow fluctuations. It was also found to be independent of $\eta$ within the measured range of pseudorapidity $|\eta|<1$. The relative flow fluctuation was found to be $34\% \pm 2\% (stat.) \pm 3\% (sys.)$ for particles of transverse momentum $p_{T}$ less than $2$ GeV/$c$. The $\Delta\eta$-dependent part may be attributed to nonflow correlations, and is found to be $5\% \pm 2\% (sys.)$ relative to the flow of the measured second harmonic cumulant at $|\Delta\eta| > 0.7$

Studies of di-jet survival and surface emission bias in Au+Au collisions via angular correlations with respect to back-to-back leading hadrons

We report first results from an analysis based on a new multi-hadron correlation technique, exploring jet-medium interactions and di-jet surface emission bias at RHIC. Pairs of back-to-back high transverse momentum hadrons are used for triggers to study associated hadron distributions. In contrast with two- and three-particle correlations with a single trigger with similar kinematic selections, the associated hadron distribution of both trigger sides reveals no modification in either relative pseudo-rapidity or relative azimuthal angle from d+Au to central Au+Au collisions. We determine associated hadron yields and spectra as well as production rates for such correlated back-to-back triggers to gain additional insights on medium properties.Comment: By the STAR Collaboration. 6 pages, 2 figure

Measurements of D0D^{0} and D∗D^{*} Production in pp + pp Collisions at s\sqrt{s} = 200 GeV

We report measurements of charmed-hadron ($D^{0}$, $D^{*}$) production cross sections at mid-rapidity in $p$ + $p$ collisions at a center-of-mass energy of 200 GeV by the STAR experiment. Charmed hadrons were reconstructed via the hadronic decays $D^{0}\rightarrow K^{-}\pi^{+}$, $D^{*+}\rightarrow D^{0}\pi^{+}\rightarrow K^{-}\pi^{+}\pi^{+}$ and their charge conjugates, covering the $p_T$ range of 0.6$-$2.0 GeV/$c$ and 2.0$-$6.0 GeV/$c$ for $D^{0}$ and $D^{*+}$, respectively. From this analysis, the charm-pair production cross section at mid-rapidity is $d\sigma/dy|_{y=0}^{c\bar{c}}$ = 170 $\pm$ 45 (stat.) $^{+38}_{-59}$ (sys.) $\mu$b. The extracted charm-pair cross section is compared to perturbative QCD calculations. The transverse momentum differential cross section is found to be consistent with the upper bound of a Fixed-Order Next-to-Leading Logarithm calculation.Comment: 15 pages, 16 figures. Revised version submitted to Phys. Rev.