An Adaptive Sampling Scheme to Efficiently Train Fully Convolutional Networks for Semantic Segmentation

Deep convolutional neural networks (CNNs) have shown excellent performance in object recognition tasks and dense classification problems such as semantic segmentation. However, training deep neural networks on large and sparse datasets is still challenging and can require large amounts of computation and memory. In this work, we address the task of performing semantic segmentation on large data sets, such as three-dimensional medical images. We propose an adaptive sampling scheme that uses a-posterior error maps, generated throughout training, to focus sampling on difficult regions, resulting in improved learning. Our contribution is threefold: 1) We give a detailed description of the proposed sampling algorithm to speed up and improve learning performance on large images. We propose a deep dual path CNN that captures information at fine and coarse scales, resulting in a network with a large field of view and high resolution outputs. We show that our method is able to attain new state-of-the-art results on the VISCERAL Anatomy benchmark

Volumetric Attention for 3D Medical Image Segmentation and Detection

A volumetric attention(VA) module for 3D medical image segmentation and detection is proposed. VA attention is inspired by recent advances in video processing, enables 2.5D networks to leverage context information along the z direction, and allows the use of pretrained 2D detection models when training data is limited, as is often the case for medical applications. Its integration in the Mask R-CNN is shown to enable state-of-the-art performance on the Liver Tumor Segmentation (LiTS) Challenge, outperforming the previous challenge winner by 3.9 points and achieving top performance on the LiTS leader board at the time of paper submission. Detection experiments on the DeepLesion dataset also show that the addition of VA to existing object detectors enables a 69.1 sensitivity at 0.5 false positive per image, outperforming the best published results by 6.6 points.Comment: Accepted by MICCAI 201

QCD and strongly coupled gauge theories : challenges and perspectives

We highlight the progress, current status, and open challenges of QCD-driven physics, in theory and in experiment. We discuss how the strong interaction is intimately connected to a broad sweep of physical problems, in settings ranging from astrophysics and cosmology to strongly coupled, complex systems in particle and condensed-matter physics, as well as to searches for physics beyond the Standard Model. We also discuss how success in describing the strong interaction impacts other fields, and, in turn, how such subjects can impact studies of the strong interaction. In the course of the work we offer a perspective on the many research streams which flow into and out of QCD, as well as a vision for future developments.Peer reviewe

Fast and Accurate Lung Tumor Spotting and Segmentation for Boundary Delineation on CT Slices In A Coarse-To-Fine Framework

Label noise and class imbalance are two of the critical challenges when training image-based deep neural networks, especially in the biomedical image processing domain. Our work focuses on how to address the two challenges effectively and accurately in the task of lesion segmentation from biomedical/medical images. To address the pixel-level label noise problem, we propose an advanced transfer training and learning approach with a detailed DICOM pre-processing method. To address the tumor/non-tumor class imbalance problem, we exploit a self-adaptive fully convolutional neural network with an automated weight distribution mechanism to spot the Radiomics lung tumor regions accurately. Furthermore, an improved conditional random field method is employed to obtain sophisticated lung tumor contour delineation and segmentation. Finally, our approach has been evaluated using several well-known evaluation metrics on the Lung Tumor segmentation dataset used in the 2018 IEEE VIP-CUP Challenge. Experimental results show that our weakly supervised learning algorithm outperforms other deep models and state-of-the-art approache

Measurement of the branching fraction for B−→D0K∗−B^- \to D^0 K^{*-}

We present a measurement of the branching fraction for the decay B- --> D0 K*- using a sample of approximately 86 million BBbar pairs collected by the BaBar detector from e+e- collisions near the Y(4S) resonance. The D0 is detected through its decays to K- pi+, K- pi+ pi0 and K- pi+ pi- pi+, and the K*- through its decay to K0S pi-. We measure the branching fraction to be B.F.(B- --> D0 K*-)= (6.3 +/- 0.7(stat.) +/- 0.5(syst.)) x 10^{-4}

Neutrinos

229 pages229 pages229 pagesThe Proceedings of the 2011 workshop on Fundamental Physics at the Intensity Frontier. Science opportunities at the intensity frontier are identified and described in the areas of heavy quarks, charged leptons, neutrinos, proton decay, new light weakly-coupled particles, and nucleons, nuclei, and atoms

Observation of a significant excess of π0π0\pi^{0}\pi^{0} events in B meson decays

We present an observation of the decay $B^{0} \to \pi^{0} \pi^{0}$ based on a sample of 124 million $B\bar{B}$ pairs recorded by the BABAR detector at the PEP-II asymmetric-energy $B$ Factory at SLAC. We observe $46 \pm 13 \pm 3$ events, where the first error is statistical and the second is systematic, corresponding to a significance of 4.2 standard deviations including systematic uncertainties. We measure the branching fraction \BR(B^{0} \to \pi^{0} \pi^{0}) = (2.1 \pm 0.6 \pm 0.3) \times 10^{-6}, averaged over $B^{0}$ and $\bar{B}^{0}$ decays

An Epididymis-Specific Secretory Protein HongrES1 Critically Regulates Sperm Capacitation and Male Fertility

Mammalian sperm capacitation is an essential prerequisite to fertilizion. Although progress had been made in understanding the physiology and biochemistry of capacitation, little is known about the potential roles of epididymal proteins during this process. Here we report that HongrES1, a new member of the SERPIN (serine proteinase inhibitor) family exclusively expressed in the rat cauda epididymis and up-regulated by androgen, is secreted into the lumen and covers the sperm head. Co-culture of caudal sperms with HongrES1 antibody in vitro resulted in a significant increase in the percentage of capacitated spermatozoa. Furthermore, the percentage of capacitated spermatozoa clearly increased in rats when HongrES1 was down-regulated by RNAi in vivo. Remarkably, knockdown of HongrES1 in vivo led to reduced fertility accompanied with deformed appearance of fetuses and pups. These results identify HongrES1 as a novel and critical molecule in the regulation of sperm capacitation and male fertility

Direct CP violation searches in charmless hadronic B meson decays

This is the pre-print version of the Article. The official published version can be accessed from the links below. Copyright @ 2002 APSWe search for direct CP violation in charmless hadronic B decays observed in a sample of about 22.7 million BB̅ pairs collected with the BABAR detector at the SLAC PEP-II asymmetric-energy e+e- collider. We measure the following charge asymmetries: ACP(B±→η′K±)=-0.11±0.11±0.02, ACP(B±→ωπ±)=-0.01 - 0.31 + 0.29±0.03, ACP(B±→φK±)=-0.05±0.20±0.03, ACP(B±→φK*±)=-0.43 - 0.30 + 0.36±0.06, and ACP(B0→φK*0)=0.00±0.27±0.03.This work was supported by DOE and NSF (USA), NSERC (Canada), IHEP (China), CEA and CNRS-IN2P3 (France), BMBF (Germany), INFN (Italy), NFR (Norway), MIST (Russia), and PPARC (United Kingdom). Individuals have received support from the Swiss NSF, A. P. Sloan Foundation, Research Corporation, and Alexander von Humboldt Foundation