Guest Editorial Generative Adversarial Networks in Biomedical Image Computing

The papers in this special section focus on generative adversarial networks in biomedical image computing. The field of biomedical imaging has obtained great progress from Roentgen’s original discovery of the X-ray to the current imaging tools, including Magnetic Resonance Imaging (MRI), Positron Emission Tomography (PET), Computed Tomography (CT), and Ultrasound (US). The benefits of using these non-invasive imaging technologies are to assess the current condition of an organ or tissue, which can be used to monitor a patient over time over time for accurate and timely diagnosis and treatment.With the development of imaging technologies, developing advanced artificial intelligence algorithms for automated image analysis has shown the potential to change many aspects of clinical applications within the next decade. Meanwhile, these advanced technologies have also brought new issues and challenges. Thus, there has been a growing demand for biomedical imaging computing to be a component of clinical trials and device improvement. Currently, Generative adversarial networks (GANs) have been attached growing interests in the computer vision community due to their capability of data generation or translation. GAN-based models are able to learn from a set of training data and generate new data with the same characteristics as the training ones, which have also proven to be the state of the art for generating sharp and realistic images. More importantly, GAN has been rapidly applied to many traditional and novel applications in the medical domain, such as image reconstruction, segmentation, diagnosis, synthesis, and so on. Despite GAN substantial progress in these areas, their application to medical image computing still faces challenges and unsolved problems remain

Visualizing the microscopic coexistence of spin density wave and superconductivity in underdoped NaFe1-xCoxAs

Although the origin of high temperature superconductivity in the iron pnictides is still under debate, it is widely believed that magnetic interactions or fluctuations play an important role in triggering Cooper pairing. Because of the relevance of magnetism to pairing, the question of whether long range spin magnetic order can coexist with superconductivity microscopically has attracted strong interests. The available experimental methods used to answer this question are either bulk probes or local ones without control of probing position, thus the answers range from mutual exclusion to homogeneous coexistence. To definitively answer this question, here we use scanning tunneling microscopy to investigate the local electronic structure of an underdoped NaFe1-xCoxAs near the spin density wave (SDW) and superconducting (SC) phase boundary. Spatially resolved spectroscopy directly reveal both the SDW and SC gap features at the same atomic location, providing compelling evidence for the microscopic coexistence of the two phases. The strengths of the SDW and SC features are shown to anti correlate with each other, indicating the competition of the two orders. The microscopic coexistence clearly indicates that Cooper pairing occurs when portions of the Fermi surface (FS) are already gapped by the SDW order. The regime TC < T < TSDW thus show a strong resemblance to the pseudogap phase of the cuprates where growing experimental evidences suggest a FS reconstruction due to certain density wave order. In this phase of the pnictides, the residual FS has a favorable topology for magnetically mediated pairing when the ordering moment of the SDW is small.Comment: 18 pages, 4 figure

Spin-orbit-driven band inversion in bilayer graphene by the van der Waals proximity effect.

Spin-orbit coupling (SOC) is the key to realizing time-reversal-invariant topological phases of matter1,2. SOC was predicted by Kane and Mele3 to stabilize a quantum spin Hall insulator; however, the weak intrinsic SOC in monolayer graphene4-7 has precluded experimental observation in this material. Here we exploit a layer-selective proximity effect-achieved via a van der Waals contact with a semiconducting transition-metal dichalcogenide8-21-to engineer Kane-Mele SOC in ultra clean bilayer graphene. Using high-resolution capacitance measurements to probe the bulk electronic compressibility, we find that SOC leads to the formation of a distinct, incompressible, gapped phase at charge neutrality. The experimental data agree quantitatively with a simple theoretical model in which the new phase results from SOC-driven band inversion. In contrast to Kane-Mele SOC in monolayer graphene, the inverted phase is not expected to be a time-reversal-invariant topological insulator, despite being separated from conventional band insulators by electric-field-tuned phase transitions where crystal symmetry mandates that the bulk gap must close22. Our electrical transport measurements reveal that the inverted phase has a conductivity of approximately e2/h (where e is the electron charge and h Planck's constant), which is suppressed by exceptionally small in-plane magnetic fields. The high conductivity and anomalous magnetoresistance are consistent with theoretical models that predict helical edge states within the inverted phase that are protected from backscattering by an emergent spin symmetry that remains robust even for large Rashba SOC. Our results pave the way for proximity engineering of strong topological insulators as well as correlated quantum phases in the strong spin-orbit regime in graphene heterostructures

Anisotropic Impurity-States, Quasiparticle Scattering and Nematic Transport in Underdoped Ca(Fe1-xCox)2As2

Iron-based high temperature superconductivity develops when the `parent' antiferromagnetic/orthorhombic phase is suppressed, typically by introduction of dopant atoms. But their impact on atomic-scale electronic structure, while in theory quite complex, is unknown experimentally. What is known is that a strong transport anisotropy with its resistivity maximum along the crystal b-axis, develops with increasing concentration of dopant atoms; this `nematicity' vanishes when the `parent' phase disappears near the maximum superconducting Tc. The interplay between the electronic structure surrounding each dopant atom, quasiparticle scattering therefrom, and the transport nematicity has therefore become a pivotal focus of research into these materials. Here, by directly visualizing the atomic-scale electronic structure, we show that substituting Co for Fe atoms in underdoped Ca(Fe1-xCox)2As2 generates a dense population of identical anisotropic impurity states. Each is ~8 Fe-Fe unit cells in length, and all are distributed randomly but aligned with the antiferromagnetic a-axis. By imaging their surrounding interference patterns, we further demonstrate that these impurity states scatter quasiparticles in a highly anisotropic manner, with the maximum scattering rate concentrated along the b-axis. These data provide direct support for the recent proposals that it is primarily anisotropic scattering by dopant-induced impurity states that generates the transport nematicity; they also yield simple explanations for the enhancement of the nematicity proportional to the dopant density and for the occurrence of the highest resistivity along the b-axis

CS-Net: Channel and Spatial Attention Network for Curvilinear Structure Segmentation

The detection of curvilinear structures in medical images, e.g., blood vessels or nerve fibers, is important in aiding management of many diseases. In this work, we propose a general unifying curvilinear structure segmentation network that works on different medical imaging modalities: optical coherence tomography angiography (OCT-A), color fundus image, and corneal confocal microscopy (CCM). Instead of the U-Net based convolutional neural network, we propose a novel network (CS-Net) which includes a self-attention mechanism in the encoder and decoder. Two types of attention modules are utilized - spatial attention and channel attention, to further integrate local features with their global dependencies adaptively. The proposed network has been validated on five datasets: two color fundus datasets, two corneal nerve datasets and one OCT-A dataset. Experimental results show that our method outperforms state-of-the-art methods, for example, sensitivities of corneal nerve fiber segmentation were at least 2% higher than the competitors. As a complementary output, we made manual annotations of two corneal nerve datasets which have been released for public access

Structure of the TPR Domain of AIP: Lack of Client Protein Interaction with the C-Terminal alpha-7 Helix of the TPR Domain of AIP Is Sufficient for Pituitary Adenoma Predisposition

PMCID: PMC3534021This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Developmental Defects of Enamel in Primary Teeth and Association with Early Life Course Events: A Study of 6--36 Month old Children in Manyara, Tanzania.

Children with low birth weight show an increased prevalence of developmental defects of enamel in the primary dentition that subsequently may predispose to early childhood caries (ECC).Focusing 6--36 months old, the purpose of this study was to assess the frequency of enamel defects in the primary dentition and identify influences of early life course factors; socio-demographics, birth weight, child's early illness episodes and mothers' perceived size of the child at birth, whilst controlling for more recent life course events in terms of current breastfeeding and oral hygiene. A cross-sectional study was conducted in the high fluoride area of Manyara, northern Tanzania including 1221 child-mother pairs who attended Reproductive and Child Health (RCH) clinics for immunization and/or growth monitoring. After the primary caregivers had completed face to face interviews at the health care facility, children underwent oral clinical examination whereby ECC and developmental defects of enamel were recorded using field criteria. All erupted teeth were examined and the enamel defects were assessed on buccal surfaces according to the modified DDE Index. The prevalence of enamel defects was 33.3%. Diffuse opacities were the most common defects identified (23.1%), followed by hypoplasia (7.6%) and demarcated opacities (5.0%). The most frequently affected teeth were the upper central incisors (29.0% - 30.5%), whereas lower central incisors (4.3% to 4.5%) were least frequently affected. Multiple logistic regression analysis, adjusting for confounding the factors revealed that having normal birth weight (equal or more than 2500 g) associated with lower odds of having enamel hypoplasia [OR 0.22 (95% CI 0.1-0.7)]. No statistically significant association occurred between birth weight and diffuse opacities, demarcated opacities or combined DDE. Children with the history of low birth weight were more likely than their normal birth weight counterparts to present with enamel hypoplasia. In view of the frequent occurrence of enamel defects and the fact that hypoplasia may constitute a risk factor for future ECC, enamel defects should be included as a dental health indicator in epidemiological studies of children in northern Tanzania