利用纹理相关性对OCT影像进行血管分割

Vessel Border Segmentation of OCT Images Using Textural Correlation

  • 摘要:  随着医学的发展,OCT影像技术越来越广泛的应用于多个医学领域,对OCT影像的处理就显得更加重要。基于图像纹理相关性的影像分割技术已经开始应用于活体微循环OCT影像的处理,如视网膜组织,皮肤血管组织等。对活体OCT影像的处理及其血管的分割有助于医生更好的诊断血管疾病。本文我们提出了一种基于灰度期望和精典Niblack结合的二值化阈值选取方法,并结合图像相关性对活体小白鼠耳朵血管的OCT影像进行图像分割,提取血管的轮廓,再经过形态学处理,得到较为准确的血管轮廓。

     

    Abstract: With the development of medical science, optical coherence tomography (OCT) imaging technology is widely used in more and more medical fields, processing of the OCT image has become more important. vascular segmentation of OCT images based on the texture Correlation has been applied to the processing of the image of the microcirculation OCT in vivo, such as retinal tissue, It can help doctors to diagnosis the vascular disease better. In this paper, the main processing steps consist of vascular segmentation and vascular reconstruction. More specially, binary threshold selection based on graylevel expectations and classical Niblack algorithm are used for vascular segmentation. Then, morphological processing is then adopted to build a basic outline of vessels maps. Finally we show the microcirculation maps of the mouse ear can be generated by the proposed scheme.

     

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