In the intricate network environment,the secure transmission of medical images faces challenges such as information leakage and malicious tampering,significantly impacting the accuracy of disease diagnoses by medical ...In the intricate network environment,the secure transmission of medical images faces challenges such as information leakage and malicious tampering,significantly impacting the accuracy of disease diagnoses by medical professionals.To address this problem,the authors propose a robust feature watermarking algorithm for encrypted medical images based on multi-stage discrete wavelet transform(DWT),Daisy descriptor,and discrete cosine transform(DCT).The algorithm initially encrypts the original medical image through DWT-DCT and Logistic mapping.Subsequently,a 3-stage DWT transformation is applied to the encrypted medical image,with the centre point of the LL3 sub-band within its low-frequency component serving as the sampling point.The Daisy descriptor matrix for this point is then computed.Finally,a DCT transformation is performed on the Daisy descriptor matrix,and the low-frequency portion is processed using the perceptual hashing algorithm to generate a 32-bit binary feature vector for the medical image.This scheme utilises cryptographic knowledge and zero-watermarking technique to embed watermarks without modifying medical images and can extract the watermark from test images without the original image,which meets the basic re-quirements of medical image watermarking.The embedding and extraction of water-marks are accomplished in a mere 0.160 and 0.411s,respectively,with minimal computational overhead.Simulation results demonstrate the robustness of the algorithm against both conventional attacks and geometric attacks,with a notable performance in resisting rotation attacks.展开更多
The catalytic descriptor with operational feasibility is highly desired towards rational design of high-performance catalyst especially the electrode/electrolyte solution interface working under mild conditions.Herein...The catalytic descriptor with operational feasibility is highly desired towards rational design of high-performance catalyst especially the electrode/electrolyte solution interface working under mild conditions.Herein,we demonstrate that the descriptorΩparameterized by readily accessible intrinsic properties of metal center and coordination is highly operational and efficient in rational design of single-atom catalyst(SAC)for driving electrochemical nitrogen reduction(NRR).Using twodimensional metal(M)-B_(x)P_(y)S_(z)N_m@C_(2)N as prototype SAC models,we reveal that^(*)N_(2)+(H~++e~-)→^(*)N_(2)H acts predominantly as the potential-limiting step(PLS)of NRR on M-B_(2)P_(2)S_(2)@C_(2)N and M-B_(1)P_(1)S_(1)N_(3)@C_(2)N regardless of the distinction in coordination microenvironment.Among the 28 screened M active sites,withΩvalues close to the optimal 4,M-B_(2)P_(2)S_(2)@C_(2)N(M=V(Ω=3.53),Mo(Ω=5.12),and W(Ω=3.92))and M-B_(1)P_(1)S_(1)N_(3)@C_(2)N(M=V(Ω=3.00),Mo(Ω=4.34),and W(Ω=3.32))yield the lowered limiting potential(U_(L))as-0.45,-0.54.-0.36,-0.58,-0.25,and-0.24 V,respectively,thus making them the promising NRR catalysts.More importantly,these SACs are located around the top of volcano-shape plot of U_(L) versusΩ,re-validatingΩas an effective descriptor for accurately predicting the high-activity NRR SACs even with complex coordination.Our study unravels the relationship between active-site structure and NRR performance via the descriptorΩ,which can be applied to other important sustainable electrocatalytic reactions involving activation of small molecules viaσ-donation andπ^(*)-backdonation mechanism.展开更多
To address the current issues of inaccurate segmentation and the limited applicability of segmentation methods for building facades in point clouds, we propose a facade segmentation algorithm based on optimal dual-sca...To address the current issues of inaccurate segmentation and the limited applicability of segmentation methods for building facades in point clouds, we propose a facade segmentation algorithm based on optimal dual-scale feature descriptors. First, we select the optimal dual-scale descriptors from a range of feature descriptors. Next, we segment the facade according to the threshold value of the chosen optimal dual-scale descriptors. Finally, we use RANSAC (Random Sample Consensus) to fit the segmented surface and optimize the fitting result. Experimental results show that, compared to commonly used facade segmentation algorithms, the proposed method yields more accurate segmentation results, providing a robust data foundation for subsequent 3D model reconstruction of buildings.展开更多
目的:对比三维多回波恢复梯度回波(3D MERGE)、三维可变反转角快速自旋回波(3D SPACE STIR)序列在腰椎间盘突出症(LDH)检查中的应用效果。方法:选择2020年1月~2022年11月收治的135例LDH患者,回顾性分析患者临床和磁共振成像(MRI)资料,...目的:对比三维多回波恢复梯度回波(3D MERGE)、三维可变反转角快速自旋回波(3D SPACE STIR)序列在腰椎间盘突出症(LDH)检查中的应用效果。方法:选择2020年1月~2022年11月收治的135例LDH患者,回顾性分析患者临床和磁共振成像(MRI)资料,所有患者均接受常规MRI扫描及3D MERGE、3D SPACE STIR序列扫描,对比3D MERGE、3D SPACE STIR序列测量神经根直径的一致性,评价两种序列的图像质量参数[信噪比(SNR)、对比噪声比(CNR)]、图像清晰度评分。结果:3D MERGE和3D SPACE STIR序列测量的L3~S1神经根直径比较差异无统计学意义(P>0.05),且两组序列测量的L3、L4、L5和S1直径均显示出较高相关性(r=0.957,0.986,0.975,0.972,P<0.05);3D MERGE序列的SNR及CNR均高于3D SPACE STIR序列,神经根显示分级、图像清晰度评分优于3D SPACE STIR序列,差异有统计学意义(P<0.05)。结论:3D MERGE、3D SPACE STIR序列在LDH神经根直径测量中具有极高一致性,3D MERGE序列较3D SPACE STIR序列能够更清晰显示神经跟的解剖形态,图像质量更好。展开更多
基金National Natural Science Foundation of China,Grant/Award Numbers:62063004,62350410483Key Research and Development Project of Hainan Province,Grant/Award Number:ZDYF2021SHFZ093Zhejiang Provincial Postdoctoral Science Foundation,Grant/Award Number:ZJ2021028。
文摘In the intricate network environment,the secure transmission of medical images faces challenges such as information leakage and malicious tampering,significantly impacting the accuracy of disease diagnoses by medical professionals.To address this problem,the authors propose a robust feature watermarking algorithm for encrypted medical images based on multi-stage discrete wavelet transform(DWT),Daisy descriptor,and discrete cosine transform(DCT).The algorithm initially encrypts the original medical image through DWT-DCT and Logistic mapping.Subsequently,a 3-stage DWT transformation is applied to the encrypted medical image,with the centre point of the LL3 sub-band within its low-frequency component serving as the sampling point.The Daisy descriptor matrix for this point is then computed.Finally,a DCT transformation is performed on the Daisy descriptor matrix,and the low-frequency portion is processed using the perceptual hashing algorithm to generate a 32-bit binary feature vector for the medical image.This scheme utilises cryptographic knowledge and zero-watermarking technique to embed watermarks without modifying medical images and can extract the watermark from test images without the original image,which meets the basic re-quirements of medical image watermarking.The embedding and extraction of water-marks are accomplished in a mere 0.160 and 0.411s,respectively,with minimal computational overhead.Simulation results demonstrate the robustness of the algorithm against both conventional attacks and geometric attacks,with a notable performance in resisting rotation attacks.
基金supported by the National Natural Science Foundation of China (21673137)。
文摘The catalytic descriptor with operational feasibility is highly desired towards rational design of high-performance catalyst especially the electrode/electrolyte solution interface working under mild conditions.Herein,we demonstrate that the descriptorΩparameterized by readily accessible intrinsic properties of metal center and coordination is highly operational and efficient in rational design of single-atom catalyst(SAC)for driving electrochemical nitrogen reduction(NRR).Using twodimensional metal(M)-B_(x)P_(y)S_(z)N_m@C_(2)N as prototype SAC models,we reveal that^(*)N_(2)+(H~++e~-)→^(*)N_(2)H acts predominantly as the potential-limiting step(PLS)of NRR on M-B_(2)P_(2)S_(2)@C_(2)N and M-B_(1)P_(1)S_(1)N_(3)@C_(2)N regardless of the distinction in coordination microenvironment.Among the 28 screened M active sites,withΩvalues close to the optimal 4,M-B_(2)P_(2)S_(2)@C_(2)N(M=V(Ω=3.53),Mo(Ω=5.12),and W(Ω=3.92))and M-B_(1)P_(1)S_(1)N_(3)@C_(2)N(M=V(Ω=3.00),Mo(Ω=4.34),and W(Ω=3.32))yield the lowered limiting potential(U_(L))as-0.45,-0.54.-0.36,-0.58,-0.25,and-0.24 V,respectively,thus making them the promising NRR catalysts.More importantly,these SACs are located around the top of volcano-shape plot of U_(L) versusΩ,re-validatingΩas an effective descriptor for accurately predicting the high-activity NRR SACs even with complex coordination.Our study unravels the relationship between active-site structure and NRR performance via the descriptorΩ,which can be applied to other important sustainable electrocatalytic reactions involving activation of small molecules viaσ-donation andπ^(*)-backdonation mechanism.
文摘To address the current issues of inaccurate segmentation and the limited applicability of segmentation methods for building facades in point clouds, we propose a facade segmentation algorithm based on optimal dual-scale feature descriptors. First, we select the optimal dual-scale descriptors from a range of feature descriptors. Next, we segment the facade according to the threshold value of the chosen optimal dual-scale descriptors. Finally, we use RANSAC (Random Sample Consensus) to fit the segmented surface and optimize the fitting result. Experimental results show that, compared to commonly used facade segmentation algorithms, the proposed method yields more accurate segmentation results, providing a robust data foundation for subsequent 3D model reconstruction of buildings.
文摘目的:对比三维多回波恢复梯度回波(3D MERGE)、三维可变反转角快速自旋回波(3D SPACE STIR)序列在腰椎间盘突出症(LDH)检查中的应用效果。方法:选择2020年1月~2022年11月收治的135例LDH患者,回顾性分析患者临床和磁共振成像(MRI)资料,所有患者均接受常规MRI扫描及3D MERGE、3D SPACE STIR序列扫描,对比3D MERGE、3D SPACE STIR序列测量神经根直径的一致性,评价两种序列的图像质量参数[信噪比(SNR)、对比噪声比(CNR)]、图像清晰度评分。结果:3D MERGE和3D SPACE STIR序列测量的L3~S1神经根直径比较差异无统计学意义(P>0.05),且两组序列测量的L3、L4、L5和S1直径均显示出较高相关性(r=0.957,0.986,0.975,0.972,P<0.05);3D MERGE序列的SNR及CNR均高于3D SPACE STIR序列,神经根显示分级、图像清晰度评分优于3D SPACE STIR序列,差异有统计学意义(P<0.05)。结论:3D MERGE、3D SPACE STIR序列在LDH神经根直径测量中具有极高一致性,3D MERGE序列较3D SPACE STIR序列能够更清晰显示神经跟的解剖形态,图像质量更好。
