Improving the Segmentation of Anatomical Structures in Chest Radiographs using U-Net with an ImageNet Pre-trained Encoder

Accurate segmentation of anatomical structures in chest radiographs is essential for many computer-aided diagnosis tasks. In this paper we investigate the latest fully-convolutional architectures for the task of multi-class segmentation of the lungs field, heart and clavicles in a chest radiograph. In addition, we explore the influence of using different loss functions in the training process of a neural network for semantic segmentation. We evaluate all models on a common benchmark of 247 X-ray images from the JSRT database and ground-truth segmentation masks from the SCR dataset. Our best performing architecture, is a modified U-Net that benefits from pre-trained encoder weights. This model outperformed the current state-of-the-art methods tested on the same benchmark, with Jaccard overlap scores of 96.1% for lung fields, 90.6% for heart and 85.5% for clavicles.Comment: Presented at the First International Workshop on Thoracic Image Analysis (TIA), MICCAI 201

Anveshak - A Groundtruth Generation Tool for Foreground Regions of Document Images

We propose a graphical user interface based groundtruth generation tool in this paper. Here, annotation of an input document image is done based on the foreground pixels. Foreground pixels are grouped together with user interaction to form labeling units. These units are then labeled by the user with the user defined labels. The output produced by the tool is an image with an XML file containing its metadata information. This annotated data can be further used in different applications of document image analysis.Comment: Accepted in DAR 201

On the dynamics of WKB wave functions whose phase are weak KAM solutions of H-J equation

In the framework of toroidal Pseudodifferential operators on the flat torus $\Bbb T^n := (\Bbb R / 2\pi \Bbb Z)^n$ we begin by proving the closure under composition for the class of Weyl operators $\mathrm{Op}^w_\hbar(b)$ with simbols $b \in S^m (\mathbb{T}^n \times \mathbb{R}^n)$. Subsequently, we consider $\mathrm{Op}^w_\hbar(H)$ when $H=\frac{1}{2} |\eta|^2 + V(x)$ where $V \in C^\infty (\Bbb T^n;\Bbb R)$ and we exhibit the toroidal version of the equation for the Wigner transform of the solution of the Schr\"odinger equation. Moreover, we prove the convergence (in a weak sense) of the Wigner transform of the solution of the Schr\"odinger equation to the solution of the Liouville equation on $\Bbb T^n \times \Bbb R^n$ written in the measure sense. These results are applied to the study of some WKB type wave functions in the Sobolev space $H^{1} (\mathbb{T}^n; \Bbb C)$ with phase functions in the class of Lipschitz continuous weak KAM solutions (of positive and negative type) of the Hamilton-Jacobi equation $\frac{1}{2} |P+ \nabla_x v_\pm (P,x)|^2 + V(x) = \bar{H}(P)$ for $P \in \ell \Bbb Z^n$ with $\ell >0$, and to the study of the backward and forward time propagation of the related Wigner measures supported on the graph of $P+ \nabla_x v_\pm$

The effect of Ga-doped nanocrystalline ZnO electrode on deep-ultraviolet enhanced GaN photodetector

published_or_final_versio

Accurate Liability Estimation Improves Power in Ascertained Case Control Studies

Linear mixed models (LMMs) have emerged as the method of choice for confounded genome-wide association studies. However, the performance of LMMs in non-randomly ascertained case-control studies deteriorates with increasing sample size. We propose a framework called LEAP (Liability Estimator As a Phenotype, https://github.com/omerwe/LEAP) that tests for association with estimated latent values corresponding to severity of phenotype, and demonstrate that this can lead to a substantial power increase

Single-cell RNA expression profiling of SARS-CoV-2-related ACE2 and TMPRSS2 in human trophectoderm and placenta

OBJECTIVES: To examine the characteristics and distribution of possible severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) target cells in the human trophectoderm (TE) and placenta. METHODS: Bioinformatics analysis was performed based on published single-cell transcriptomic datasets of early TE and first- and second-trimester human placentae. We conducted the transcriptomic analysis of 4198 early TE cells, 1260 first-trimester placental cells and 189 extravillous trophoblast cells (EVTs) from 24-week placentae (EVT_24W) using the SMART-Seq2 method. In addition, to confirm the bioinformatic results, we performed immunohistochemical staining of three first-trimester, three second-trimester and three third-trimester placentae from nine women recruited prospectively to this study. We evaluated the expression of the SARS-CoV-2-related molecules angiotensin-converting enzyme 2 (ACE2) and transmembrane protease serine 2 (TMPRSS2). RESULTS: Via bioinformatic analysis, we identified the existence of ACE2 and TMPRSS2 expression in human TE as well as in first- and second-trimester placentae. In the human TE, 54.4% of TE1 cells, 9.0% of cytotrophoblasts (CTBs), 3.2% of EVTs and 29.5% of syncytiotrophoblasts (STBs) were ACE2-positive. In addition, 90.7% of TE1 cells, 31.5% of CTBs, 22.1% of EVTs and 70.8% of STBs were TMPRSS2-positive. In placental cells, 20.4% of CTBs, 44.1% of STBs, 3.4% of EVTs from 8-week placentae (EVT_8W) and 63% of EVT_24W were ACE2-positive, while 1.6% of CTBs, 26.5% of STBs, 1.9% of EVT_8W and 20.1% of EVT_24W were TMPRSS2-positive. Pathway analysis revealed that EVT_24W cells that were positive for both ACE2 and TMPRSS2 (ACE2 + TMPRSS2-positive) were associated with morphogenesis of branching structure, extracellular matrix interaction, oxygen binding and antioxidant activity. The ACE2 + TMPRSS2-positive TE1 cells were correlated with an increased capacity for viral invasion, epithelial-cell proliferation and cell adhesion. Expression of ACE2 and TMPRSS2 was observed on immunohistochemical staining in first-, second- and third-trimester placentae. CONCLUSIONS: ACE2- and TMPRSS2-positive cells are present in the human TE and placenta in all three trimesters of pregnancy, which indicates the possibility that SARS-CoV-2 could spread via the placenta and cause intrauterine fetal infection. © 2020 International Society of Ultrasound in Obstetrics and Gynecolog

Effects of annealing temperature on the characteristics of Ga-doped ZnO film metal-semiconductor-metal ultraviolet photodetectors

published_or_final_versio

Inner Space Preserving Generative Pose Machine

Image-based generative methods, such as generative adversarial networks (GANs) have already been able to generate realistic images with much context control, specially when they are conditioned. However, most successful frameworks share a common procedure which performs an image-to-image translation with pose of figures in the image untouched. When the objective is reposing a figure in an image while preserving the rest of the image, the state-of-the-art mainly assumes a single rigid body with simple background and limited pose shift, which can hardly be extended to the images under normal settings. In this paper, we introduce an image "inner space" preserving model that assigns an interpretable low-dimensional pose descriptor (LDPD) to an articulated figure in the image. Figure reposing is then generated by passing the LDPD and the original image through multi-stage augmented hourglass networks in a conditional GAN structure, called inner space preserving generative pose machine (ISP-GPM). We evaluated ISP-GPM on reposing human figures, which are highly articulated with versatile variations. Test of a state-of-the-art pose estimator on our reposed dataset gave an accuracy over 80% on PCK0.5 metric. The results also elucidated that our ISP-GPM is able to preserve the background with high accuracy while reasonably recovering the area blocked by the figure to be reposed.Comment: http://www.northeastern.edu/ostadabbas/2018/07/23/inner-space-preserving-generative-pose-machine

MnSb2O6: a polar magnet with a chiral crystal structure

Structural and magnetic chiralities are found to coexist in a small group of materials in which they produce intriguing phenomenologies such as the recently discovered Skyrmion phases. Here, we describe a previously unknown manifestation of this interplay in MnSb2O6, a trigonal oxide with a chiral crystal structure. Unlike all other known cases, the MnSb2O6 magnetic structure is based on corotating cycloids rather than helices. The coupling to the structural chirality is provided by a magnetic axial vector, related to the so-called vector chirality. We show that this unique arrangement is the magnetic ground state of the symmetric-exchange Hamiltonian, based on ab initio theoretical calculations of the Heisenberg exchange interactions, and is stabilized by out-of-plane anisotropy. MnSb2O6 is predicted to be multiferroic with a unique ferroelectric switching mechanism.open4

Accessible digital ophthalmoscopy based on liquid-lens technology

Ophthalmoscopes have yet to capitalise on novel low-cost miniature optomechatronics, which could disrupt ophthalmic monitoring in rural areas. This paper demonstrates a new design integrating modern components for ophthalmoscopy. Simulations show that the optical elements can be reduced to just two lenses: an aspheric ophthalmoscopic lens and a commodity liquid-lens, leading to a compact prototype. Circularly polarised transpupilary illumination, with limited use so far for ophthalmoscopy, suppresses reflections, while autofocusing preserves image sharpness. Experiments with a human-eye model and cadaver porcine eyes demonstrate our prototype’s clinical value and its potential for accessible imaging when cost is a limiting factor