1) ultrasonic image management
超声图像管理
2) intravascular ultrasound
血管内超声图像
1.
Edge detection of intravascular ultrasound(IVUS) images is important for the diagnosis and treatment of the coronary artery disease.
为了更好地抑制血管内超声图像的血液斑点噪声,首先采用一种时/空滤波方法对IVUS图像进行降噪预处理,以抑制其严重的血液斑点噪声;然后,为了更好地提取血管边缘,提出了一种改进的自适应形变模型,并基于该改进的自适应形变模型(T-Snake模型)给出了一种IVUS图像冠状动脉血管壁内、外膜边缘的提取方法。
4) ultrasound images
超声图像
1.
Objective To promote stability and accuracy of gradient vector flow (GVF) deformable models by improving external potential force field of ultrasound images under speckle noisy environments.
结果通过二值加噪图像和心脏超声图像的实验,验证了该方法的捕捉范围和处理噪声方面优于GVF。
2.
Objective To improve the flexibility and stability of the filter in speckle reduction of ultrasound images.
方法使用二状态的瑞利、高斯混合分布对超声图像灰度分布进行拟合,并采用期望值最大化(expectation maximization,EM)算法实现混合分布的分解;根据分解结果预测图像中斑点噪声均匀分布的区域;通过对均匀区域统计特性的分析获取各向异性扩散的扩散参数。
3.
This article presents an algorithm for semiautomatic segmentation of ultrasound images combining user intervention into the B spline snake models using a new kind of force field and a new control point insertion strategy.
提出了超声图像半自动分割的一种新方法。
5) Ultrasonic image
超声图像
1.
Breast tumor classification based on shape features of ultrasonic images;
基于形态特征判别超声图像中乳腺肿瘤的良恶性
2.
Quantitative analysis of fatty liver ultrasonic images;
脂肪肝超声图像的定量分析
3.
Discussion on extraction of planar contour from ultrasonic image and rebuilding process of three-dimensional image;
超声图像的表面轮廓提取及三维图像重建过程的探讨
6) ultrasound image
超声图像
1.
Automatic detection of breast tumor regions in medical ultrasound images with texture features;
基于纹理的乳房超声图像中肿瘤区域自动检测
2.
Multi-characteristics recognition of breast tumor ultrasound images combining with elasticity parameters;
联合弹性特征的多特征乳腺肿瘤超声图像识别
3.
The classification of the uterine myoma and the uterine adenomyosis from ultrasound images mainly depends on doctors experience and lacks objective criterions by now.
超声图像子宫肌瘤和腺肌病的区分目前主要依赖于医生的经验,缺乏客观的指标。
补充资料：高光谱分辨率遥感图像及图像光谱信息提取
高光谱分辨率遥感图像及图像光谱信息提取
高光谱分辨率遥感图像及图像光谱信息提取 郑兰芬供稿
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条