Brain Tumor Synthetic Segmentation in 3D Multimodal MRI Scans

The magnetic resonance (MR) analysis of brain tumors is widely used for diagnosis and examination of tumor subregions. The overlapping area among the intensity distribution of healthy, enhancing, non-enhancing, and edema regions makes the automatic segmentation a challenging task. Here, we show that a convolutional neural network trained on high-contrast images can transform the intensity distribution of brain lesions in its internal subregions. Specifically, a generative adversarial network (GAN) is extended to synthesize high-contrast images. A comparison of these synthetic images and real images of brain tumor tissue in MR scans showed significant segmentation improvement and decreased the number of real channels for segmentation. The synthetic images are used as a substitute for real channels and can bypass real modalities in the multimodal brain tumor segmentation framework. Segmentation results on BraTS 2019 dataset demonstrate that our proposed approach can efficiently segment the tumor areas. In the end, we predict patient survival time based on volumetric features of the tumor subregions as well as the age of each case through several regression models

Disruption to control network function correlates with altered dynamic connectivity in the wider autism spectrum.

Autism is a common developmental condition with a wide, variable range of co-occurring neuropsychiatric symptoms. Contrasting with most extant studies, we explored whole-brain functional organization at multiple levels simultaneously in a large subject group reflecting autism's clinical diversity, and present the first network-based analysis of transient brain states, or dynamic connectivity, in autism. Disruption to inter-network and inter-system connectivity, rather than within individual networks, predominated. We identified coupling disruption in the anterior-posterior default mode axis, and among specific control networks specialized for task start cues and the maintenance of domain-independent task positive status, specifically between the right fronto-parietal and cingulo-opercular networks and default mode network subsystems. These appear to propagate downstream in autism, with significantly dampened subject oscillations between brain states, and dynamic connectivity configuration differences. Our account proposes specific motifs that may provide candidates for neuroimaging biomarkers within heterogeneous clinical populations in this diverse condition

Accelerated Reader as a literacy catch-up intervention during primary to secondary school transition phase

This paper describes an evaluation of an internet-based reading programme called Accelerated Reader (AR), which is widely used in UK schools and worldwide. AR is a whole-group reading management and monitoring programme that aims to stimulate the habit of independent reading among primary and secondary age pupils. The evaluation involved 349 pupils in Year 7 who had not achieved secure National Curriculum Level 4 in their Key Stage 2 results for English, randomised to two groups. The intervention group of 166 pupils was exposed to AR for 20 weeks, after which they recorded higher literacy scores in the New Group Reading Test (NGRT) post-test than the control group of 183 pupils (“effect” size of +0.24). The schools led the organisation and implementation of the intervention, and also conducted most elements of the evaluation, with advice from an expert external evaluation team. The process evaluation suggests that these schools were very capable of conducting evaluations of their own practice, given appropriate guidance

TuNet: End-to-end Hierarchical Brain Tumor Segmentation using Cascaded Networks

Glioma is one of the most common types of brain tumors; it arises in the glial cells in the human brain and in the spinal cord. In addition to having a high mortality rate, glioma treatment is also very expensive. Hence, automatic and accurate segmentation and measurement from the early stages are critical in order to prolong the survival rates of the patients and to reduce the costs of the treatment. In the present work, we propose a novel end-to-end cascaded network for semantic segmentation that utilizes the hierarchical structure of the tumor sub-regions with ResNet-like blocks and Squeeze-and-Excitation modules after each convolution and concatenation block. By utilizing cross-validation, an average ensemble technique, and a simple post-processing technique, we obtained dice scores of 88.06, 80.84, and 80.29, and Hausdorff Distances (95th percentile) of 6.10, 5.17, and 2.21 for the whole tumor, tumor core, and enhancing tumor, respectively, on the online test set.Comment: Accepted at MICCAI BrainLes 201

Comparison of human uterine cervical electrical impedance measurements derived using two tetrapolar probes of different sizes

BACKGROUND We sought to compare uterine cervical electrical impedance spectroscopy measurements employing two probes of different sizes, and to employ a finite element model to predict and compare the fraction of electrical current derived from subepithelial stromal tissue. METHODS Cervical impedance was measured in 12 subjects during early pregnancy using 2 different sizes of the probes on each subject. RESULTS Mean cervical resistivity was significantly higher (5.4 vs. 2.8 Ωm; p < 0.001) with the smaller probe in the frequency rage of 4–819 kHz. There was no difference in the short-term intra-observer variability between the two probes. The cervical impedance measurements derived in vivo followed the pattern predicted by the finite element model. CONCLUSION Inter-electrode distance on the probes for measuring cervical impedance influences the tissue resistivity values obtained. Determining the appropriate probe size is necessary when conducting clinical studies of resistivity of the cervix and other human tissues

Results from Shell Model Monte Carlo Studies

We review results obtained using Shell Model Monte Carlo (SMMC) techniques. These methods reduce the imaginary-time many-body evolution operator to a coherent superposition of one-body evolutions in fluctuating one-body fields; the resultant path integral is evaluated stochastically. After a brief review of the methods, we discuss a variety of nuclear physics applications. These include studies of the ground-state properties of pf-shell nuclei, Gamow-Teller strength distributions, thermal and rotational pairing properties of nuclei near N=Z, $\gamma$-soft nuclei, and $\beta\beta$-decay in ^{76}Ge. Several other illustrative calculations are also reviewed. Finally, we discuss prospects for further progress in SMMC and related calculations