We propose a novel automatic target recognition (ATR) system for classification of three types of ground vehicles in the moving and stationary target acquisition and recognition (MSTAR) public release database. First, MSTAR image chips are represented as fine and raw feature vectors, where raw features compensate for the target pose estimation error that corrupts fine image features. Then, the chips are classified by using the adaptive boosting (AdaBoost) algorithm with the radial basis function (RBF) network as the base learner. Since the RBF network is a binary classifier, we decompose our multiclass problem into a set of binary ones through the error-correcting output codes (ECOC) method, specifying a dictionary of code words for the set of three possible classes. AdaBoost combines the classification results of the RBF network for each binary problem into a code word, which is then "decoded" as one of the code words (i.e., ground-vehicle classes) in the specified dictionary. Along with classification, within the AdaBoost framework, we also conduct efficient fusion of the fine and raw image-feature vectors. The results of large-scale experiments demonstrate that our ATR scheme outperforms the state-of-the-art systems reported in the literature.

The results indicate that the combination of P300 with an SSVEP-B improves target discrimination greatly; the proposed hybrid paradigm is superior to the control paradigm in spelling performance. Thus, our findings provide a new approach to improve BCI performances.

Objective To investigate the biomechanical effects of reduction quality on patients after femoral neck fracture internal fixation. Methods The data of individual patients with femoral neck fractures were reviewed. Data for patients with simple unilateral femoral neck fractures whose reduction quality was evaluated as good by hip X‐ray films after internal fixation were collected from January 2013 to January 2017. The CT data of the patients was used to reconstruct 3D models of the femur and the screw. The spatial displacement after the operation of femoral neck fracture was measured, which included the displacement of the deepest portion of the femoral head fovea, the displacement of the center of the femoral head, and the rotational angle. The cases were followed up by telephone consultation and clinical review to determine whether the osteonecrosis of the femoral head occurred. Follow‐up time should be more than 18 months after surgery. The cases were grouped according to the results into an osteonecrosis of the femoral head group and a non‐osteonecrosis of the femoral head group. Finally, the differences in postoperative spatial displacement between the two groups were compared and analyzed. In addition, a mechanical analysis of femoral force during gait was performed via finite element analysis. Results Data for 241 patients with femoral neck fractures who were treated with closed reduction and internal fixation were collected. 3D measurement showed the average displacement value, including the center of the femoral head (5.90 ± 3.4 mm), the deepest portion of the femoral head fovea (9.32 ± 4.8 mm), and the rotational angle (16.1° ± 9.4°). After telephone consultation and clinical review, osteonecrosis of the femoral head was diagnosed in 28 (11.62%) of the patients. In the osteonecrosis of the femoral head (ONFH) group, the displacement of the deepest portion of the femoral head fovea was 10.92 ± 9.18 mm; the displacement was 8.86 ± 6.29 mm in the non‐ONFH group. The displacement of the center of the femoral head in the ONFH group was 7.575 ± 5.69 mm and 5.31 ± 4.05 mm in non‐ONFH group. The rotational angle was 20.11° ± 10.27° in the ONFH group and 14.19° ± 11.09° in the non‐ONFH group. The statistical analysis showed that the postoperative spatial displacements, including the displacement of the deepest portion of the femoral head fovea, the displacement of the center of the femoral head, and the rotational angle between the two groups, had statistical differences. Finite element analysis showed that as the spatial displacement increased, the stress, the displacement, and the equivalent strain of the proximal femur also increased. Conclusion Poor reduction quality after femoral neck fracture is a risk factor for re‐fracture and femoral head necrosis, and the measurement method of this study can be used to predict the occurrence of femoral head necrosis early after femoral neck fracture.

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Photoacoustic microscopy (PAM) is an emerging imaging technology that can non-invasively visualize ocular structures in animal eyes. This report describes an integrated multimodality imaging system that combines PAM, optical coherence tomography (OCT), and fluorescence microscopy (FM) to evaluate angiogenesis in larger animal eyes. High-resolution in vivo imaging was performed in live rabbit eyes with vascular endothelial growth factor (VEGF)-induced retinal neovascularization (RNV). The results demonstrate that our multimodality imaging system can non-invasively visualize RNV in both albino and pigmented rabbits to determine retinal pathology using PAM and OCT and verify the leakage of neovascularization using FM and fluorescein dye. This work presents high-resolution visualization of angiogenesis in rabbits using a multimodality PAM, OCT, and FM system and may represent a major step toward the clinical translation of the technology.