Task Decomposition and Synchronization for Semantic Biomedical Image Segmentation

Semantic segmentation is essentially important to biomedical image analysis. Many recent works mainly focus on integrating the Fully Convolutional Network (FCN) architecture with sophisticated convolution implementation and deep supervision. In this paper, we propose to decompose the single segmentation task into three subsequent sub-tasks, including (1) pixel-wise image segmentation, (2) prediction of the class labels of the objects within the image, and (3) classification of the scene the image belonging to. While these three sub-tasks are trained to optimize their individual loss functions of different perceptual levels, we propose to let them interact by the task-task context ensemble. Moreover, we propose a novel sync-regularization to penalize the deviation between the outputs of the pixel-wise segmentation and the class prediction tasks. These effective regularizations help FCN utilize context information comprehensively and attain accurate semantic segmentation, even though the number of the images for training may be limited in many biomedical applications. We have successfully applied our framework to three diverse 2D/3D medical image datasets, including Robotic Scene Segmentation Challenge 18 (ROBOT18), Brain Tumor Segmentation Challenge 18 (BRATS18), and Retinal Fundus Glaucoma Challenge (REFUGE18). We have achieved top-tier performance in all three challenges.Comment: IEEE Transactions on Medical Imagin

Visualization of all two-qubit states via partial-transpose-moments

Efficiently detecting entanglement based on measurable quantities is a basic problem for quantum information processing. Recently, the measurable quantities called partial-transpose (PT)-moments have been proposed to detect and characterize entanglement. In the recently published paper [L. Zhang \emph{et al.}, \href{https://doi.org/10.1002/andp.202200289}{Ann. Phys.(Berlin) \textbf{534}, 2200289 (2022)}], we have already identified the 2-dimensional (2D) region, comprised of the second and third PT-moments, corresponding to two-qubit entangled states, and described the whole region for all two-qubit states. In the present paper, we visualize the 3D region corresponding to all two-qubit states by further involving the fourth PT-moment (the last one for two-qubit states). The characterization of this 3D region can finally be achieved by optimizing some polynomials. Furthermore, we identify the dividing surface which separates the two parts of the whole 3D region corresponding to entangled and separable states respectively. Due to the measurability of PT-moments, we obtain a complete and operational criterion for the detection of two-qubit entanglement.Comment: 29 pages, LaTeX, 8 figures, 2 table

Relationship of cumulative dust exposure dose and cumulative abnormal rate of pulmonary function in coal mixture workers

AbstractTo investigate the dose-response relationship between cumulative dust exposure (CDE) and cumulative abnormal rate of pulmonary function in coal mixture workers. Three hundred and twenty eight coal mixture workers (exposed group) and 169 nondust-exposed workers (control group) were recruited. Basic information data were collected and pulmonary function tests were performed. Pulmonary function was compared between the two groups after comparing smoking behaviors. Pulmonary function indices [forced vital capacity in 1 second after full inspiration (FVC)%, forced expiratory volume (FEV)1%, and FEV1/FVC%] were compared among groups stratified by service length (exposure duration). The relationship between CDE dose and cumulative abnormal rate of pulmonary function in coal mixture workers was analyzed. Abnormal rate of pulmonary function in the exposed group (35.1%) was significantly higher than the control group (10.1%; p < 0.001); FVC%, FEV1%, and FEV1/FVC% in the exposed group decreased significantly compared with the control group (all p < 0.05). Differences in FVC%, FEV1%, and FEV1/FVC% among coal mixture workers stratified by exposure duration in the exposed group were statistically significant (all p < 0.05). The discernible increase in the cumulative abnormal rate was observed, from ≥ 1000 mg/m3·years group to ≥ 1700 mg/m3·years group. Correlation analysis revealed a positive correlation between the CDE dose and the cumulative abnormal rate of pulmonary function. Higher abnormal pulmonary function rate was found among coal mixture workers, characterized by decreased pulmonary function indices. Our results suggested a positive relationship between CDE dose and cumulative abnormal pulmonary function rate, and a rapid increase in cumulative abnormal rate within a certain range of CDE dose. A lower limit value of 1000 mg/m3·years has reference significance

Functionally distinct and selectively phosphorylated GPCR subpopulations co-exist in a single cell.

G protein-coupled receptors (GPCRs) transduce pleiotropic intracellular signals in a broad range of physiological responses and disease states. Activated GPCRs can undergo agonist-induced phosphorylation by G protein receptor kinases (GRKs) and second messenger-dependent protein kinases such as protein kinase A (PKA). Here, we characterize spatially segregated subpopulations of β2-adrenergic receptor (β2AR) undergoing selective phosphorylation by GRKs or PKA in a single cell. GRKs primarily label monomeric β2ARs that undergo endocytosis, whereas PKA modifies dimeric β2ARs that remain at the cell surface. In hippocampal neurons, PKA-phosphorylated β2ARs are enriched in dendrites, whereas GRK-phosphorylated β2ARs accumulate in soma, being excluded from dendrites in a neuron maturation-dependent manner. Moreover, we show that PKA-phosphorylated β2ARs are necessary to augment the activity of L-type calcium channel. Collectively, these findings provide evidence that functionally distinct subpopulations of this prototypical GPCR exist in a single cell

Quetiapine N-oxide–fumaric acid (2/1)

The title compound (systematic name: 2-{2-[4-(dibenzo[b,f][1,4]thia­zepin-11-yl)piperazin-1-yl 1-oxide]eth­oxy}ethanol–fumaric acid (2/1)), C21H25N3O3S·0.5C4H4O4, is one of the oxidation products of quetiapine hemifumaric acid. In the tricyclic fragment, the central thia­zepine ring displays a boat conformation and the benzene rings are inclined to each other at a dihedral angle of 72.0 (2)°. The piperazine ring adopts a chair conformation with its eth­oxy­ethanol side chain oriented equatorially. In addition to the main mol­ecule, the asymmetric unit contains one-half mol­ecule of fumaric acid, the complete mol­ecule being generated by inversion symmetry. In the crystal, O—H⋯O hydrogen bonds link the components into corrugated layers parallel to bc plane

Brain atlas fusion from high-thickness diagnostic magnetic resonance images by learning-based super-resolution

It is fundamentally important to fuse the brain atlas from magnetic resonance (MR) images for many imaging-based studies. Most existing works focus on fusing the atlases from high-quality MR images. However, for low-quality diagnostic images (i.e., with high inter-slice thickness), the problem of atlas fusion has not been addressed yet. In this paper, we intend to fuse the brain atlas from the high-thickness diagnostic MR images that are prevalent for clinical routines. The main idea of our works is to extend the conventional groupwise registration by incorporating a novel super-resolution strategy. The contribution of the proposed super-resolution framework is two-fold. First, each high-thickness subject image is reconstructed to be isotropic by the patch-based sparsity learning. Then, the reconstructed isotropic image is enhanced for better quality through the random-forest-based regression model. In this way, the images obtained by the super-resolution strategy can be fused together by applying the groupwise registration method to construct the required atlas. Our experiments have shown that the proposed framework can effectively solve the problem of atlas fusion from the low-quality brain MR images