Accurate and reliable brain tumor segmentation is a critical component in cancer diagnosis, treatment planning, and treatment outcome evaluation. Build upon successful deep learning techniques, a novel brain tumor segmentation method is developed by integrating fully convolutional neural networks (FCNNs) and Conditional Random Fields (CRFs) in a unified framework to obtain segmentation results with appearance and spatial consistency. We train a deep learning based segmentation model using 2D image patches and image slices in following steps: 1) training FCNNs using image patches; 2) training CRFs as Recurrent Neural Networks (CRF-RNN) using image slices with parameters of FCNNs fixed; and 3) fine-tuning the FCNNs and the CRF-RNN using image slices. Particularly, we train 3 segmentation models using 2D image patches and slices obtained in axial, coronal and sagittal views respectively, and combine them to segment brain tumors using a voting based fusion strategy. Our method could segment brain images slice-by-slice, much faster than those based on image patches. We have evaluated our method based on imaging data provided by the Multimodal Brain Tumor Image Segmentation Challenge (BRATS) 2013, BRATS 2015 and BRATS 2016. The experimental results have demonstrated that our method could build a segmentation model with Flair, T1c, and T2 scans and achieve competitive performance as those built with Flair, T1, T1c, and T2 scans.

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In this work, tungsten triboride (WB3) was successfully synthesized at high pressure and high temperature. The structure was reconfirmed to be WB3 (P63 mmc), and some part has a tungsten atomic defect according to the measurement results of X-ray diffraction, high-resolution transmission electron microscopy, and Rietveld refinement. The asymptotic Vickers hardness that had eliminated influence of excess boron is 25.5 GPa for WB3. This value is in good agreement with the previous theoretic results. Proof of novel electron transfer between the tungsten atom and the boron atom was found. A deficient amount of transfer electron induces distorted sp2 hybridization of B–B bonds in WB3. The weakly directional sp2 hybridization of B–B bonds is an essential factor that can influence the hardness of WB3. Our results are helpful to design new hard and superhard materials of transition metal borides.

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