Accurate 3D Cell Segmentation using Deep Feature and CRF Refinement

We consider the problem of accurately identifying cell boundaries and labeling individual cells in confocal microscopy images, specifically, 3D image stacks of cells with tagged cell membranes. Precise identification of cell boundaries, their shapes, and quantifying inter-cellular space leads to a better understanding of cell morphogenesis. Towards this, we outline a cell segmentation method that uses a deep neural network architecture to extract a confidence map of cell boundaries, followed by a 3D watershed algorithm and a final refinement using a conditional random field. In addition to improving the accuracy of segmentation compared to other state-of-the-art methods, the proposed approach also generalizes well to different datasets without the need to retrain the network for each dataset. Detailed experimental results are provided, and the source code is available on GitHub.Comment: 5 pages, 5 figures, 3 table

Improving Patch-Based Convolutional Neural Networks for MRI Brain Tumor Segmentation by Leveraging Location Information.

The manual brain tumor annotation process is time consuming and resource consuming, therefore, an automated and accurate brain tumor segmentation tool is greatly in demand. In this paper, we introduce a novel method to integrate location information with the state-of-the-art patch-based neural networks for brain tumor segmentation. This is motivated by the observation that lesions are not uniformly distributed across different brain parcellation regions and that a locality-sensitive segmentation is likely to obtain better segmentation accuracy. Toward this, we use an existing brain parcellation atlas in the Montreal Neurological Institute (MNI) space and map this atlas to the individual subject data. This mapped atlas in the subject data space is integrated with structural Magnetic Resonance (MR) imaging data, and patch-based neural networks, including 3D U-Net and DeepMedic, are trained to classify the different brain lesions. Multiple state-of-the-art neural networks are trained and integrated with XGBoost fusion in the proposed two-level ensemble method. The first level reduces the uncertainty of the same type of models with different seed initializations, and the second level leverages the advantages of different types of neural network models. The proposed location information fusion method improves the segmentation performance of state-of-the-art networks including 3D U-Net and DeepMedic. Our proposed ensemble also achieves better segmentation performance compared to the state-of-the-art networks in BraTS 2017 and rivals state-of-the-art networks in BraTS 2018. Detailed results are provided on the public multimodal brain tumor segmentation (BraTS) benchmarks

Corrigendum: Improving Patch-Based Convolutional Neural Networks for MRI Brain Tumor Segmentation by Leveraging Location Information.

[This corrects the article DOI: 10.3389/fnins.2019.01449.]

Long-term effect of transurethral partial cystectomy with a 2-micrometer continuous-wave laser for non-muscle-invasive bladder cancer

PurposeWe have reported the efficacy and safety of 2-micrometer continuous-wave laser cystectomy of non-muscle invasive bladder tumor (NMIBC) (J Urol. 2009;182:66–9). In this study, we evaluated the long-term outcomes of patients with NMIBC who underwent transurethral partial cystectomy with a 2-micrometer continuous-wave laser, and explored the risk factors for tumor recurrence.MethodsThis was a retrospective study of patients with NMIBC planned to undergo transurethral partial cystectomy with a 2-micrometer continuous-wave laser at the Fourth Medical Center of the PLA General Hospital between January 2012 and December 2014. The primary outcome was bladder cancer recurrence.ResultsA total of 75 patients were enrolled. Sixty-two (82.7%) were male. The patients were 59.8 ± 12.9 years of age. The mean operation time was 38.7 ± 20.4 min. No Clavien grade >2 complications occurred. The duration of catheter indwelling was 3.6 ± 1.8 days. The hospital stay was 6.0 ± 2.3 days. The median follow-up was 80 months. A total of 17 patients had a recurrence during follow-up, and the recurrence-free survival (RFS) rate was 77.3%. In the multivariable analysis, the tumor risk group were independently associated with the recurrence of NMIBC (p = 0.026).ConclusionsAfter TURBT with a 2-micrometer continuous-wave laser, RFS was 77.3% at the median follow-up of 80 months. All complications were mild. Only tumor risk group was independently associated with the recurrence of NMIBC

Evolution of microstructure and nanohardness of SiC fiber-reinforced SiC matrix composites under Au ion irradiation

Abstract(#br)Evolution of microstructure and nanohardness of a new type of SiC f /SiC composite under a 6 MeV Au ion irradiation up to 90 displacements per atom at 400 °C was studied. Scanning transmission electron microscopy reveals that the irradiation has induced enrichment of carbon at the grain boundaries in the fibers. This is attributed to the accumulation of C interstitials generated by the irradiation. The disappearance of {200} diffraction ring of 3C–SiC indicates that a phase transition from 3C–SiC to Si has occurred during irradiation. In addition, the hardness of SiC fiber increased after irradiation, which is due to the pinning effect caused by irradiation-induced defects. The pyrolytic-carbon interphase that contains Si-rich nano-grains in the composite has the highest irradiation tolerance as it maintained its basic morphology and graphitic nature after a radiation damage dose up to 90 dpa. Twins are the main internal defects in the SiC matrix of the SiC f /SiC composite, which grew up and resulted in the decrease of the number of twinning boundaries under irradiation. No significant microstructure change has been observed in the SiC matrix except a limited number of dislocation loops at the peak irradiation damage region. The entire matrix still maintained its hardness after irradiation

The relationships of preventive behaviors and psychological resilience with depression, anxiety, and stress among university students during the COVID-19 pandemic: A two-wave longitudinal study in Shandong Province, China

IntroductionStudies have shown that the psychological impact of the COVID-19 pandemic may lead to long-term health problems; therefore, more attention should be paid to the mental health of university students. This study aimed to explore the longitudinal effects of preventive behaviors and psychological resilience on the mental health of Chinese college students during COVID-19.MethodsWe recruited 2,948 university students from five universities in Shandong Province. We used a generalized estimating equation (GEE) model to estimate the impact of preventive behaviors and psychological resilience on mental health.ResultsIn the follow-up survey, the prevalence of anxiety (44.8% at T1 vs 41.2% at T2) and stress (23.0% at T1 vs 19.6% at T2) decreased over time, whereas the prevalence of depression (35.2% at T1 vs 36.9% at T2) increased significantly (P < 0.001). Senior students were more likely to report depression (OR = 1.710, P < 0.001), anxiety (OR = 0.815, P = 0.019), and stress (OR = 1.385, P = 0.011). Among all majors, medical students were most likely to report depression (OR = 1.373, P = 0.021), anxiety (OR = 1.310, P = 0.040), and stress (OR = 1.775, P < 0.001). Students who wore a mask outside were less likely to report depression (OR = 0.761, P = 0.027) and anxiety (OR = 0.686, P = 0.002) compared to those who did not wear masks. Students who complied with the standard hand-washing technique were less likely to report depression (OR = 0.628, P < 0.001), anxiety (OR = 0.701, P < 0.001), and stress (OR = 0.638, P < 0.001). Students who maintained a distance of one meter in queues were less likely to report depression (OR = 0.668, P < 0.001), anxiety (OR = 0.634, P < 0.001), and stress (OR = 0.638, P < 0.001). Psychological resilience was a protective factor against depression (OR = 0.973, P < 0.001), anxiety (OR = 0.980, P < 0.001), and stress (OR = 0.976, P < 0.001).DiscussionThe prevalence of depression among university students increased at follow-up, while the prevalence of anxiety and stress decreased. Senior students and medical students are vulnerable groups. University students should continue to follow relevant preventive behaviors to protect their mental health. Improving psychological resilience may help maintain and promote university students' mental health

The Overseeing Mother: Revisiting the Frontal-Pose Lady in the Wu Family Shrines in Second Century China

Located in present-day Jiaxiang in Shandong province, the Wu family shrines built during the second century in the Eastern Han dynasty (25–220) were among the best-known works in Chinese art history. Although for centuries scholars have exhaustively studied the pictorial programs, the frontal-pose female image situated on the second floor of the central pavilion carved at the rear wall of the shrines has remained a question. Beginning with the woman’s eyes, this article demonstrates that the image is more than a generic portrait (“hard motif ”), but rather represents “feminine overseeing from above” (“soft motif ”). This synthetic motif combines three different earlier motifs – the frontal-pose hostess enjoying entertainment, the elevated spectator, and the Queen Mother of the West. By creatively fusing the three motifs into one unity, the Jiaxiang artists lent to the frontal-pose lady a unique power: she not only dominated the center of the composition, but also, like a divine being, commanded a unified view of the surroundings on the lofty building, hence echoing the political reality of the empress mother’s “overseeing the court” in the second century during Eastern Han dynasty