基于曲率匹配的细胞几何形状特征提取方法

细胞轮廓的几何形状是细胞学涂片判读的重要参考，对研究宫颈病变的计算机辅助诊断具有重要意义。针对现有基于形状模板匹配的几何形状识别方法鲁棒性较差的问题，提出了基于曲率匹配的几何形状特征提取方法，通过比较模板轮廓和待识别轮廓的曲率，计算曲率曲线之间的相似度，进而得到细胞轮廓的形状特征，并采用依次旋转轮廓选取最佳匹配的方法来解决轮廓方向不一致的问题，采用以面积等效圆的半径比作为放大比率进行轮廓缩放的方法来解决轮廓大小不一致的问题。通过相关实验证明了该方法所提取的几何形状特征具有尺度不变性和旋转不变性，并与改进Hausdorff距离进行了实验对比，结果表明提取的形状特征能更加准确地识别出细胞轮廓的几何形状。

Cell contour geometric shape feature extraction method using matching curvatures

Cell contour geometry is an important reference for smear interpretation, that has important significance for the study of computer-aided diagnosis of cervical lesions. In order to improve the robustness of the existing recognition method based on the geometry of the shape of the template matching, the paper proposes a new geometry feature extraction based on the geometric shape matching the curvature of the shape. The method proposed by comparing the template contour and contour curvature to be identified, computes the similarity between the curvature of the curve, resulting in characteristic cell shape contour. The paper by successively rotating the contour to select the best matching solves the problem of inconsistency contour direction, and the problem of inconsistent contour size by an area equivalent radius of a circle than a zoom magnification ratio contour method. The paper verifies that geometry feature extracted has a scale and rotational invariance, and the experimental comparison results with improved Hausdorff distance show that the proposed shape features can more accurately identify the cell contour geometry.