Purpose: This study aimed to examine whether the signal-to-noise ratio (SNR) could be increased by combining integrated slice-by-slice shimming (iShim) with a fat suppression (FS) method other than short-tau inversion...Purpose: This study aimed to examine whether the signal-to-noise ratio (SNR) could be increased by combining integrated slice-by-slice shimming (iShim) with a fat suppression (FS) method other than short-tau inversion recovery (STIR) in diffusion-weighted imaging (DWI) and q-space imaging (qsi). Methods: We acquired DWI images (b-values: 0 and nine steps from 400 to 10,000 s/mm2 for six axes) using a prototypical single-shot echo planar imaging sequence by combining two types of shimming (3D Shim and iShim) and two types of FS (STIR and water excitation [WE]) in 10 volunteers. In the DWI study, the SNR for each b-value, FS effect in the b0 image, and distortion in the added image (b0 - b10,000) were evaluated for the above-mentioned four imaging methods. qsi involved original DWI images. In the qsi study, the SNR was evaluated. Results: With regard to both 3D Shim and iShim, the SNRs were significantly higher when using WE than when using STIR in b0 - b900 images (p Conclusion: The combination of iShim and WE has a high SNR on qsi.展开更多
文摘Purpose: This study aimed to examine whether the signal-to-noise ratio (SNR) could be increased by combining integrated slice-by-slice shimming (iShim) with a fat suppression (FS) method other than short-tau inversion recovery (STIR) in diffusion-weighted imaging (DWI) and q-space imaging (qsi). Methods: We acquired DWI images (b-values: 0 and nine steps from 400 to 10,000 s/mm2 for six axes) using a prototypical single-shot echo planar imaging sequence by combining two types of shimming (3D Shim and iShim) and two types of FS (STIR and water excitation [WE]) in 10 volunteers. In the DWI study, the SNR for each b-value, FS effect in the b0 image, and distortion in the added image (b0 - b10,000) were evaluated for the above-mentioned four imaging methods. qsi involved original DWI images. In the qsi study, the SNR was evaluated. Results: With regard to both 3D Shim and iShim, the SNRs were significantly higher when using WE than when using STIR in b0 - b900 images (p Conclusion: The combination of iShim and WE has a high SNR on qsi.
文摘复杂背景抑制是天基红外预警系统中红外弱小目标探测技术的一个关键环节。为降低复杂背景下杂波干扰,提高目标检测精度,利用非下采样轮廓波变换(NSCT,non-subsampled contourlet transform)的多尺度分解及多方向分解特性以及图像矩阵奇异值分解(SVD,singular value decomposition)不同奇异值代表图像不同能量信息的特点,提出了联合NSCT和SVD的红外图像背景的抑制方法。首先依据非下采样轮廓波变换思想对红外原始图像进行多尺度多方向分解,得到与原始图像同样大小的不同尺度和不同方向上的子带图像,然后,利用奇异值分解的中序部分奇异值调整各子带图像矩阵系数以区分目标和背景杂波,最后对调整后各子带系数组成的矩阵施加NSCT逆变换,最终获得抑制背景处理后的图像。对比实验表明,该方法能够在低信噪比环境下有效抑制复杂背景及边缘,突显目标,降低虚警率。
