| 胡海曼,雷雨蒙,余靖,鄢华,叶华容,张舸.自适应奇异值阈值调控下超声微血管成像及融合成像[J].中国医学影像技术,2024,40(10):1582~1587 |
| 自适应奇异值阈值调控下超声微血管成像及融合成像 |
| Ultrasound microvascular imaging and fusion imaging under adaptive singular value threshold control |
| 投稿时间：2024-03-02 修订日期：2024-06-03 |
| DOI：10.13929/j.issn.1003-3289.2024.10.026 |
| 中文关键词: 血管 超声检查 奇异值分解 |
| 英文关键词:blood vessels ultrasonography singular value decomposition |
| 基金项目:湖北省自然科学基金青年项目(2023AFB289)。 |
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| 中文摘要: |
| 目的 观察以奇异值分解滤波提取不同速度超声造影(CEUS)信号并进行融合成像对于提升可视化微血管结构的效果。方法 分别对200帧小鼠皮下肿瘤及250帧人体肝脏CEUS图像数据集进行奇异值分解滤波处理,根据奇异值在其序列中的指数投影,以奇异值拐点作为区分低速与高速CEUS信号的阈值并提取相应信号,对处理后图像进行双模态融合成像;观察不同流速超声微血管成像区域图像分辨率的差异。结果 以高奇异值序列范围处理后的高速血流图像保留快速移动CEUS信号,主要呈现较粗大血管结构;经低奇异值序列范围处理后的低速血流图像则保留低速移动CEUS信号,反映高速血流图像中的微血管结构;二者融合成像显示微血管网络更加完整。结论 适当选取奇异值范围对以奇异值分解滤波处理优化CEUS图像至关重要;融合成像有利于提升微血管结构可视化效果。 |
| 英文摘要: |
| Objective To observe the effect of extracting different speed contrast-enhanced ultrasound (CEUS) signals using singular value decomposition filtering and implementing fused imaging for improving visualization of microvascular structures. Methods Singular value decomposition and filtering were performed on 200 frames of mouse subcutaneous tumor and 250 frames of human liver CEUS image datasets. The singular value inflection point was used as the threshold for separating low-speed and high-speed contrast signals by exponential projection of singular values on the singular value sequence. The low-speed and high-speed signals in dataset were extracted, and dual-modal fusion imaging was performed on the processed images. The image resolution differences of ultrasound microvascular imaging regions with different flow velocities were evaluated. Results The high-speed blood flow images processed by the high singular value sequence range retained the fast-moving contrast signals which mainly showed the thicker blood vessel structures, while the low-speed blood flow images processed by the low singular value sequence range retained the low-speed moving contrast signals which reflected the microvascular structures on high singular value images. The fusion imaging displayed microvascular network more completely. Conclusion Appropriate selection of singular value range was crucial to optimization of CEUS images using singular value decomposition filtering. Fusion imaging was beneficial to improving visualization of microvascular structures. |
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