Structure-Aware Shape Synthesis

We propose a new procedure to guide training of a data-driven shape generative model using a structure-aware loss function. Complex 3D shapes often can be summarized using a coarsely defined structure which is consistent and robust across variety of observations. However, existing synthesis techniques do not account for structure during training, and thus often generate implausible and structurally unrealistic shapes. During training, we enforce structural constraints in order to enforce consistency and structure across the entire manifold. We propose a novel methodology for training 3D generative models that incorporates structural information into an end-to-end training pipeline.Comment: Accepted to 3DV 201

Proton mass decomposition

We report the results on the proton mass decomposition and also on the related quark and glue momentum fractions. The results are based on overlap valence fermions on four ensembles of $N_f = 2+1$ DWF configurations with three lattice spacings and volumes, and several pion masses including the physical pion mass. With 1-loop perturbative calculation and proper normalization of the glue operator, we find that the $u, d,$ and $s$ quark masses contribute 9(2)\% to the proton mass. The quark energy and glue field energy contribute 31(5)\% and 37(5)\% respectively in the $\overline{MS}$ scheme at $\mu = 2$ GeV. The trace anomaly gives the remaining 23(1)\% contribution. The $u,d,s$ and glue momentum fractions in the $\overline{MS}$ scheme are consistent with the global analysis at $\mu = 2$ GeV.Comment: 6 pages. Proceedings of the 35th International Symposium on Lattice Field Theory (Lattice2017), Granada, Spai

Anatomy of the ρ\rho resonance from lattice QCD at the physical point

We propose a strategy to access the $q\bar{q}$ component of the $\rho$ resonance in lattice QCD. Through a mixed action formalism (overlap valence on domain wall sea), the energy of the $q\bar{q}$ component is derived at different valence quark masses, and shows a linear dependence on $m_\pi^2$. The slope is determined to be $c_1=0.505(3)\,{\rm GeV}^{-1}$, from which the valence $\pi \rho$ sigma term is extracted to be $\sigma_{\pi \rho}^{(\rm val)}=9.82(6)$ MeV using the Feynman-Hellman theorem. At the physical pion mass, the mass of the $q\bar{q}$ component is interpolated to be $m_\rho=775.9\pm 6.0\pm 1.8$ MeV, which is close to the $\rho$ resonance mass. We also obtain the leptonic decay constant of the $q\bar{q}$ component to be $f_{\rho^-}=208.5\pm 5.5\pm 0.9$ MeV, which can be compared with the experimental value $f_{\rho}^{\rm exp}\approx 221$ MeV through the relation $f_{\rho}^{\rm exp}=\sqrt{Z_\rho}f_{\rho^\pm}$ with $Z_\rho\approx 1.13$ being the on-shell wavefunction renormalization of $\rho$ owing to the $\rho-\pi$ interaction. We emphasize that $m_\rho$ and $f_\rho$ of the $q\bar{q}$ component, which are obtained for the first time from QCD, can be taken as the input parameters of $\rho$ in effective field theory studies where $\rho$ acts as a fundamental degree of freedom.Comment: 7 pages, 4 figures. Considerably modified, more discussions, matching to the published versio

Proton Mass Decomposition from the QCD Energy Momentum Tensor

We report results on the proton mass decomposition and also on related quark and glue momentum fractions. The results are based on overlap valence fermions on four ensembles of $N_f = 2+1$ DWF configurations with three lattice spacings and three volumes, and several pion masses including the physical pion mass. With fully non-perturbative renormalization (and universal normalization on both quark and gluon), we find that the quark energy and glue field energy contribute 33(4)(4)\% and 37(5)(4)\% respectively in the $\overline{MS}$ scheme at $\mu = 2$ GeV. A quarter of the trace anomaly gives a 23(1)(1)\% contribution to the proton mass based on the sum rule, given 9(2)(1)\% contribution from the $u, d,$ and $s$ quark scalar condensates. The $u,d,s$ and glue momentum fractions in the $\overline{MS}$ scheme are in good agreement with global analyses at $\mu = 2$ GeV.Comment: 10 pages, 6 figure

Enhancing Cardiac MRI Segmentation via Classifier-Guided Two-Stage Network and All-Slice Information Fusion Transformer

Cardiac Magnetic Resonance imaging (CMR) is the gold standard for assessing cardiac function. Segmenting the left ventricle (LV), right ventricle (RV), and LV myocardium (MYO) in CMR images is crucial but time-consuming. Deep learning-based segmentation methods have emerged as effective tools for automating this process. However, CMR images present additional challenges due to irregular and varying heart shapes, particularly in basal and apical slices. In this study, we propose a classifier-guided two-stage network with an all-slice fusion transformer to enhance CMR segmentation accuracy, particularly in basal and apical slices. Our method was evaluated on extensive clinical datasets and demonstrated better performance in terms of Dice score compared to previous CNN-based and transformer-based models. Moreover, our method produces visually appealing segmentation shapes resembling human annotations and avoids common issues like holes or fragments in other models' segmentations.Comment: Accepted by 2023 MICCAI AMAI worksho