Law Max W K, Chung Albert C S
Lo Kwee-Seong Medical Image Analysis Laboratory, Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong.
IEEE Trans Med Imaging. 2007 Sep;26(9):1224-41. doi: 10.1109/TMI.2007.903231.
Accurate detection of vessel boundaries is particularly important for a precise extraction of vasculatures in magnetic resonance angiography (MRA). In this paper, we propose the use of weighted local variance (WLV)-based edge detection scheme for vessel boundary detection in MRA. The proposed method is robust against changes of intensity contrast of edges and capable of giving high detection responses on low contrast edges. These robustness and capabilities are essential for detecting the boundaries of vessels in low contrast regions of images, which can contain intensity inhomogeneity, such as bias field, interferences induced from other tissues, or fluctuation of the speed related vessel intensity. The performance of the WLV-based edge detection scheme is studied and shown to be able to return strong and consistent detection responses on low contrast edges in the experiments. The proposed edge detection scheme can be embedded naturally in the active contour models for vascular segmentation. The WLV-based vascular segmentation method is tested using MRA image volumes. It is experimentally shown that the WLV-based edge detection approach can achieve high-quality segmentation of vasculatures in MRA images.
准确检测血管边界对于在磁共振血管造影（MRA）中精确提取血管系统尤为重要。在本文中，我们提出使用基于加权局部方差（WLV）的边缘检测方案来检测MRA中的血管边界。所提出的方法对边缘强度对比度的变化具有鲁棒性，并且能够对低对比度边缘给出高检测响应。这些鲁棒性和能力对于检测图像低对比度区域中的血管边界至关重要，这些区域可能包含强度不均匀性，如偏置场、其他组织引起的干扰或与血管强度相关的速度波动。研究了基于WLV的边缘检测方案的性能，并表明在实验中能够对低对比度边缘返回强烈且一致的检测响应。所提出的边缘检测方案可以自然地嵌入到用于血管分割的主动轮廓模型中。使用MRA图像体积对基于WLV的血管分割方法进行了测试。实验表明，基于WLV的边缘检测方法能够实现MRA图像中血管系统的高质量分割。
