Segmenting the lesion regions from the ultrasound (US) images is an important step in the intra-operative planning of some computer-aided therapies. High-Intensity Focused Ultrasound (HIFU), as a popular computer-...Segmenting the lesion regions from the ultrasound (US) images is an important step in the intra-operative planning of some computer-aided therapies. High-Intensity Focused Ultrasound (HIFU), as a popular computer-aided therapy, has been widely used in the treatment of uterine fibroids. However, such segmentation in HIFU remains challenge for two reasons: (1) the blurry or missing boundaries of lesion regions in the HIFU images and (2) the deformation of uterine fibroids caused by the patient's breathing or an external force during the US imaging process, which can lead to complex shapes of lesion regions. These factors have prevented classical active contour-based segmentation methods from yielding desired results for uterine fibroids in US images. In this paper, a novel active contour-based segmentation method is proposed, which utilizes the correlation information of target shapes among a sequence of images as prior knowledge to aid the existing active contour method. This prior knowledge can be interpreted as a unsupervised clustering of shapes prior modeling. Meanwhile, it is also proved that the shapes correlation has the low-rank property in a linear space, and the theory of matrix recovery is used as an effective tool to impose the proposed prior on an existing active contour model. Finally, an accurate method is developed to solve the proposed model by using the Augmented Lagrange Multiplier (ALM). Experimental results from both synthetic and clinical uterine fibroids US image sequences demonstrate that the proposed method can consistently improve the performance of active contour models and increase the robustness against missing or misleading boundaries, and can greatly improve the efficiency of HIFU therapy.展开更多
This paper discusses conditions under which the solution of linear system with minimal Schatten-p norm, 0 〈 p ≤ 1, is also the lowest-rank solution of this linear system. To study this problem, an important tool is ...This paper discusses conditions under which the solution of linear system with minimal Schatten-p norm, 0 〈 p ≤ 1, is also the lowest-rank solution of this linear system. To study this problem, an important tool is the restricted isometry constant (RIC). Some papers provided the upper bounds of RIC to guarantee that the nuclear-norm minimization stably recovers a low-rank matrix. For example, Fazel improved the upper bounds to δ4Ar 〈 0.558 and δ3rA 〈 0.4721, respectively. Recently, the upper bounds of RIC can be improved to δ2rA 〈 0.307. In fact, by using some methods, the upper bounds of RIC can be improved to δ2tA 〈 0.4931 and δrA 〈 0.309. In this paper, we focus on the lower bounds of RIC, we show that there exists linear maps A with δ2rA 〉1√2 or δrA 〉 1/3 for which nuclear norm recovery fail on some matrix with rank at most r. These results indicate that there is only a little limited room for improving the upper bounds for δ2rA and δrA.Furthermore, we also discuss the upper bound of restricted isometry constant associated with linear maps A for Schatten p (0 〈 p 〈 1) quasi norm minimization problem.展开更多
正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)中至关重要的一项技术是信道估计,本文提出一种基于矩阵恢复的OFDM信道估计方法,将连续多个OFDM信号的频域信道构造成一个信道矩阵,由于这个信道矩阵是低秩的,所以可以...正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)中至关重要的一项技术是信道估计,本文提出一种基于矩阵恢复的OFDM信道估计方法,将连续多个OFDM信号的频域信道构造成一个信道矩阵,由于这个信道矩阵是低秩的,所以可以将信道估计问题转换为信道矩阵的加权截断核范数最小化问题,并使用改进的奇异值阈值(Singular Value Thresholding,SVT)算法对信道矩阵进行恢复。仿真结果表明,本文提出的方法和传统信道估计算法相比,使用相同导频数可以获得更高的估计精度,在获得相同估计精度时,消耗导频数更少。与基于压缩感知的信道估计方法相比,本文方法消耗相同数量的导频,但可直接获得高精度的OFDM信道的频域估计。展开更多
为了减小低快拍数和低信噪比下采样协方差矩阵误差,并降低其运算复杂度,提出了一种基于实数化的均匀圆阵采样协方差矩阵重构方法。针对均匀圆阵的特点,通过组建特殊的基向量,构成特殊的重构矩阵。通过将采样协方差矩阵实数化,进一步降...为了减小低快拍数和低信噪比下采样协方差矩阵误差,并降低其运算复杂度,提出了一种基于实数化的均匀圆阵采样协方差矩阵重构方法。针对均匀圆阵的特点,通过组建特殊的基向量,构成特殊的重构矩阵。通过将采样协方差矩阵实数化,进一步降低了重构矩阵的复杂度。考虑到多通道不一致性对重构矩阵的影响,引入0位校正算法,提高了重构方法的稳健性。最后应用重构后的协方差矩阵进行子空间类波达方向估计(direction of arrival,DOA)。实验仿真证明,该特殊重构矩阵在实数化下与原矩阵重构能力相同;当快拍数为100、信噪比为0 dB时,双信源分辨力较重构前由74%提高到95%以上;理论重构运算复杂度降低到原来的53.99%。展开更多
A new nerve matrix membrane derived from decellularized porcine nerves has been shown to retain the major extracellular matrix components, and to be effective in preventing adhesion between the nerve anastomosis sites...A new nerve matrix membrane derived from decellularized porcine nerves has been shown to retain the major extracellular matrix components, and to be effective in preventing adhesion between the nerve anastomosis sites and the surrounding tissues in a rat sciatic nerve transection model, thereby enhancing regeneration of the nerve. The effectiveness of the membrane may be attributed to its various bioactive components. In this prospective, randomized, single-blind, parallel-controlled multicenter clinical trial, we compared the safety and efficacy of the new nerve matrix membrane with a previously approved bovine tendon-derived type I collagen nerve wrapping. A total of 120 patients with peripheral nerve injury were recruited from Beijing Jishuitan Hospital, The First Bethune Hospital of Jilin University, and Yantai Yuhuangding Hospital, China. The patients were randomly assigned to undergo end-to-end and tension-free neurorrhaphy with nerve matrix membrane(n = 60, 52 male, 8 female, mean age 41.34 years, experimental group) or tendon-derived collagen nerve wrapping(n = 60, 42 male, 18 female, mean age 40.17 years, control group). Patients were followed-up at 14 ± 5, 30 ± 7, 90 ± 10 and 180 ± 20 days after the operation. Safety evaluation included analyses of local and systemic reactions, related laboratory tests, and adverse reactions. Efficacy evaluation included a static 2-point discrimination test, a moving 2-point discrimination test, and a Semmes–Weinstein monofilament examination. Sensory nerve function was evaluated with the British Medical Research Council Scale and Semmes–Weinstein monofilament examination. The ratio(percentage) of patients with excellent to good results in sensory nerve recovery 180 ± 20 days after the treatment was used as the primary effectiveness index. The percentages of patients with excellent to good results in the experimental and control groups were 98.00% and 94.44%, respectively, with no significant difference between the two groups. There were no significant differen展开更多
In this paper, a unified matrix recovery model was proposed for diverse corrupted matrices. Resulting from the separable structure of the proposed model, the convex optimization problem can be solved efficiently by ad...In this paper, a unified matrix recovery model was proposed for diverse corrupted matrices. Resulting from the separable structure of the proposed model, the convex optimization problem can be solved efficiently by adopting an inexact augmented Lagrange multiplier (IALM) method. Additionally, a random projection accelerated technique (IALM+RP) was adopted to improve the success rate. From the preliminary numerical comparisons, it was indicated that for the standard robust principal component analysis (PCA) problem, IALM+RP was at least two to six times faster than IALM with an insignificant reduction in accuracy; and for the outlier pursuit (OP) problem, IALM+RP was at least 6.9 times faster, even up to 8.3 times faster when the size of matrix was 2 000×2 000.展开更多
基金Supported by the National Basic Research Program of China(2011CB707904)the Natural Science Foundation of China(61472289)Hubei Province Natural Science Foundation of China(2015CFB254)
文摘Segmenting the lesion regions from the ultrasound (US) images is an important step in the intra-operative planning of some computer-aided therapies. High-Intensity Focused Ultrasound (HIFU), as a popular computer-aided therapy, has been widely used in the treatment of uterine fibroids. However, such segmentation in HIFU remains challenge for two reasons: (1) the blurry or missing boundaries of lesion regions in the HIFU images and (2) the deformation of uterine fibroids caused by the patient's breathing or an external force during the US imaging process, which can lead to complex shapes of lesion regions. These factors have prevented classical active contour-based segmentation methods from yielding desired results for uterine fibroids in US images. In this paper, a novel active contour-based segmentation method is proposed, which utilizes the correlation information of target shapes among a sequence of images as prior knowledge to aid the existing active contour method. This prior knowledge can be interpreted as a unsupervised clustering of shapes prior modeling. Meanwhile, it is also proved that the shapes correlation has the low-rank property in a linear space, and the theory of matrix recovery is used as an effective tool to impose the proposed prior on an existing active contour model. Finally, an accurate method is developed to solve the proposed model by using the Augmented Lagrange Multiplier (ALM). Experimental results from both synthetic and clinical uterine fibroids US image sequences demonstrate that the proposed method can consistently improve the performance of active contour models and increase the robustness against missing or misleading boundaries, and can greatly improve the efficiency of HIFU therapy.
基金supported by National Natural Science Foundation of China (Grant Nos.91130009, 11171299 and 11041005)National Natural Science Foundation of Zhejiang Province in China (Grant Nos. Y6090091 and Y6090641)
文摘This paper discusses conditions under which the solution of linear system with minimal Schatten-p norm, 0 〈 p ≤ 1, is also the lowest-rank solution of this linear system. To study this problem, an important tool is the restricted isometry constant (RIC). Some papers provided the upper bounds of RIC to guarantee that the nuclear-norm minimization stably recovers a low-rank matrix. For example, Fazel improved the upper bounds to δ4Ar 〈 0.558 and δ3rA 〈 0.4721, respectively. Recently, the upper bounds of RIC can be improved to δ2rA 〈 0.307. In fact, by using some methods, the upper bounds of RIC can be improved to δ2tA 〈 0.4931 and δrA 〈 0.309. In this paper, we focus on the lower bounds of RIC, we show that there exists linear maps A with δ2rA 〉1√2 or δrA 〉 1/3 for which nuclear norm recovery fail on some matrix with rank at most r. These results indicate that there is only a little limited room for improving the upper bounds for δ2rA and δrA.Furthermore, we also discuss the upper bound of restricted isometry constant associated with linear maps A for Schatten p (0 〈 p 〈 1) quasi norm minimization problem.
文摘正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)中至关重要的一项技术是信道估计,本文提出一种基于矩阵恢复的OFDM信道估计方法,将连续多个OFDM信号的频域信道构造成一个信道矩阵,由于这个信道矩阵是低秩的,所以可以将信道估计问题转换为信道矩阵的加权截断核范数最小化问题,并使用改进的奇异值阈值(Singular Value Thresholding,SVT)算法对信道矩阵进行恢复。仿真结果表明,本文提出的方法和传统信道估计算法相比,使用相同导频数可以获得更高的估计精度,在获得相同估计精度时,消耗导频数更少。与基于压缩感知的信道估计方法相比,本文方法消耗相同数量的导频,但可直接获得高精度的OFDM信道的频域估计。
文摘为了减小低快拍数和低信噪比下采样协方差矩阵误差,并降低其运算复杂度,提出了一种基于实数化的均匀圆阵采样协方差矩阵重构方法。针对均匀圆阵的特点,通过组建特殊的基向量,构成特殊的重构矩阵。通过将采样协方差矩阵实数化,进一步降低了重构矩阵的复杂度。考虑到多通道不一致性对重构矩阵的影响,引入0位校正算法,提高了重构方法的稳健性。最后应用重构后的协方差矩阵进行子空间类波达方向估计(direction of arrival,DOA)。实验仿真证明,该特殊重构矩阵在实数化下与原矩阵重构能力相同;当快拍数为100、信噪比为0 dB时,双信源分辨力较重构前由74%提高到95%以上;理论重构运算复杂度降低到原来的53.99%。
基金supported by the Wu Jieping Medical Foundation of China,No. 320.6750.17273 (to YBG)。
文摘A new nerve matrix membrane derived from decellularized porcine nerves has been shown to retain the major extracellular matrix components, and to be effective in preventing adhesion between the nerve anastomosis sites and the surrounding tissues in a rat sciatic nerve transection model, thereby enhancing regeneration of the nerve. The effectiveness of the membrane may be attributed to its various bioactive components. In this prospective, randomized, single-blind, parallel-controlled multicenter clinical trial, we compared the safety and efficacy of the new nerve matrix membrane with a previously approved bovine tendon-derived type I collagen nerve wrapping. A total of 120 patients with peripheral nerve injury were recruited from Beijing Jishuitan Hospital, The First Bethune Hospital of Jilin University, and Yantai Yuhuangding Hospital, China. The patients were randomly assigned to undergo end-to-end and tension-free neurorrhaphy with nerve matrix membrane(n = 60, 52 male, 8 female, mean age 41.34 years, experimental group) or tendon-derived collagen nerve wrapping(n = 60, 42 male, 18 female, mean age 40.17 years, control group). Patients were followed-up at 14 ± 5, 30 ± 7, 90 ± 10 and 180 ± 20 days after the operation. Safety evaluation included analyses of local and systemic reactions, related laboratory tests, and adverse reactions. Efficacy evaluation included a static 2-point discrimination test, a moving 2-point discrimination test, and a Semmes–Weinstein monofilament examination. Sensory nerve function was evaluated with the British Medical Research Council Scale and Semmes–Weinstein monofilament examination. The ratio(percentage) of patients with excellent to good results in sensory nerve recovery 180 ± 20 days after the treatment was used as the primary effectiveness index. The percentages of patients with excellent to good results in the experimental and control groups were 98.00% and 94.44%, respectively, with no significant difference between the two groups. There were no significant differen
基金Supported by National Natural Science Foundation of China (No.51275348)College Students Innovation and Entrepreneurship Training Program of Tianjin University (No.201210056339)
文摘In this paper, a unified matrix recovery model was proposed for diverse corrupted matrices. Resulting from the separable structure of the proposed model, the convex optimization problem can be solved efficiently by adopting an inexact augmented Lagrange multiplier (IALM) method. Additionally, a random projection accelerated technique (IALM+RP) was adopted to improve the success rate. From the preliminary numerical comparisons, it was indicated that for the standard robust principal component analysis (PCA) problem, IALM+RP was at least two to six times faster than IALM with an insignificant reduction in accuracy; and for the outlier pursuit (OP) problem, IALM+RP was at least 6.9 times faster, even up to 8.3 times faster when the size of matrix was 2 000×2 000.