Search

Brain extraction is an important prerequisite for the automated diagnosis of intracranial lesions and determines, to a certain extent, the accuracy of subsequent lesion identification, localization, and segmentation. To address the problem that the current traditional image segmentation methods are fast in extraction but poor in robustness, while the Full Convolutional Neural Network (FCN) is robust and accurate but relatively slow in extraction, this paper proposes an adaptive mask-based brain extraction method, namely AMBBEM, to achieve brain extraction better. The method first uses threshold segmentation, median filtering, and closed operations for segmentation, generates a mask for the first time, then combines the ResNet50 model, region growing algorithm, and image properties analysis to further segment the mask, and finally complete brain extraction by multiplying the original image and the mask. The algorithm was tested on 22 test sets containing different lesions, and the results showed MPA = 0.9963, MIoU = 0.9924, and MBF = 0.9914, which were equivalent to the extraction effect of the Deeplabv3+ model. However, the method can complete brain extraction of approximately 6.16 head CT images in 1 second, much faster than Deeplabv3+, U-net, and SegNet models. In summary, this method can achieve accurate brain extraction from head CT images more quickly, creating good conditions for subsequent brain volume measurement and feature extraction of intracranial lesions. [ABSTRACT FROM AUTHOR]

Copyright of Angewandte Chemie is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper investigates the attenuation behavior of flexural waves in functionally graded and disordered piezoelectric metamaterials. These structures are expediently designed by tuning the shunted piezoelectric electrical circuit. The transfer matrix method is employed to calculate the dispersive relationship of one-dimensional graded piezoelectric meta beams. It is found that the attenuation zone of the graded arrangement becomes wider compared with the result of the corresponding periodic structures. Moreover, the attenuation zone becomes wider by increasing the capacitance ratio's absolute value in a specific region. We demonstrate that the graded system generating the rainbow effect can slow down the flexural wave propagation in the host structure and increase the interaction time between elastic waves and local electrical circuits through the time-domain analysis. Besides, we study further the two-dimensional graded and disordered piezoelectric meta plates. Numerical results show that the bandwidth of the latter on average is broader than that of the former. Moreover, the disordered system can keep the continuity of the dominant attenuation zone and further increase the attenuation bandwidth within the larger capacitance ratio. These graded and disorder configuration concepts may pave a new way for elastic wave manipulation to realize broadband vibration suppressions and frequency selective spatial separations. [ABSTRACT FROM AUTHOR]

Background: The Picosecond Nd:YAG laser has advantages in skin rejuvenation, which has little damage to surrounding tissues due to the ultra‐short pulse width. We perform clinical application of Picosecond Nd:YAG laser's tender skin mode, which could improve the seborrheic dermatitis. Materials and Methods: Sixty‐three subjects with facial seborrheic dermatitis are randomized to be control and observation groups. Records regarding skin subjective improvement, skin barrier function‐related data, skin microbial status, and dermoscopy detection of the two patient groups before and after treatments are investigated. Results: Improvements of erythema and scales in observation group are significant compared with controls (p < 0.05). In terms of skin barrier function, there are significant changes regarding transepidermal water loss and epidermal seborrhea content in observation group after the laser treatments. Skin microbial state, pityrosporum furfur, and Demodex significantly decrement in observation group. Microscopical findings of infiltration mode advise that scales and capillary congestion and dilatation are significantly improved in observation group. Compared with controls, epidermal gloss increases, pore fineness improves, and capillary density decreases in the observation group. Conclusions: Picosecond Nd:YAG laser could efficiently decrease erythema area and seborrheic dermatitis scales and reduce pruritus incidence. The sebaceous gland secretion of seborrhea and multiplying of epidermal parasitic microbiological are inhibited after laser treatment. Less epidermal seborrhea content and inflammation are induced by parasitic microbiology, which is helpful for skin barrier function and microvascular remodeling. [ABSTRACT FROM AUTHOR]