基于形状感知的显微图像目标定位方法

Object Localization Method in Microscopic Image Based on Shape Perception

针对卵细胞浆内单精子注射显微图像中注射针针尖点定位不准确的问题,提出了一种基于形状感知的显微图像针尖定位方法。通过将目标形状和边界信息作为约束条件引入图像分割网络的损失函数中,使卷积神经网络在训练过程中更关注目标的形状和边界特征,从而提高针尖点的定位准确度。实验结果表明,基于形状感知的显微图像针尖定位方法在3种常用基线分割模型上的性能提高了7%以上,即所提方法可作为即插即用的模块以提高算法的泛化能力,并且对针尖的定位效果优于领域内其他方法。

To deal with the inaccurate positioning issue of the needle tip in Intracytoplasmic sperm injection microscopic images,a shape-sensing-based microscopic image needle tip positioning method is proposed.In particular,the target shape and boundary information are proposed as constraints on the loss function of the image segmentation network,driving the convolutional neural network to pay more attention to the shape and boundary features of the target during the training process.The experimental results show that the performance of the proposed loss function is increased by more than 7%compared to the three commonly used baseline segmentation models.Thus,the method can be used as a plug-and-play module to improve the generalization ability of the algorithm.In addition,its localization accuracy exceeds the state-of-the-art methods in the field.