CAJ | 학술논문

血管内超声图像的血管壁内外膜边缘检测是IVUS图像处理中必不可少的步骤与重要环节，基于主动轮廓模型的血管壁边缘提取的效果好坏很大程度上依赖于初始轮廓能否较为精确的选取。提出了一种提取血管壁边缘的新方法，以自适应阈值分割的方式降低目标图像的复杂度，结合 marr 边缘检测算子找到血管壁内外膜边缘的初始轮廓，在此基础之上，采用改进的GVF-snake算法使初始轮廓线精确收敛于真实的血管壁边缘，实验结果验证了此方法的有效性。
혈관내초성도상적혈관벽내외막변연검측시IVUS도상처리중필불가소적보취여중요배절，기우주동륜곽모형적혈관벽변연제취적효과호배흔대정도상의뢰우초시륜곽능부교위정학적선취。제출료일충제취혈관벽변연적신방법，이자괄응역치분할적방식강저목표도상적복잡도，결합 marr 변연검측산자조도혈관벽내외막변연적초시륜곽，재차기출지상，채용개진적GVF-snake산법사초시륜곽선정학수렴우진실적혈관벽변연，실험결과험증료차방법적유효성。
The intima and adventitia edge detection of vascular wall is a key step in Intravascular Ultrasound(IVUS) processing. An accurate selection of initial contour would be significant for edge extraction based on active contour model. This paper puts forward a new method for extracting the edge of vascular wall. At first, adaptive threshold segmentation is used to reduce the complexity of the IVUS original images,then find the initial contour line of the vascular wall with Marr edge detection. Finally, an improved GVF-snake model is used to make the initial contour line converge to the true edge of vascular wall accurately. The experimental results confirm the validity of the new method.