显微操作中斑马鱼幼鱼心脏识别与监测方法

Heart recognition and monitoring method for zebrafish larvae in micromanipulation

斑马鱼作为一种典型的有脊椎模式动物,因其幼鱼具有与人类基因相似度高、身体透明方便观察等特点在生物医学领域被广泛研究.其中识别和监测斑马鱼幼鱼心脏对研究心血管疾病的发病机理、药物影响等至关重要.为解决常规显微操作技术对各向异性的斑马鱼幼鱼在操作和观测上的困难,提出了一种基于显微视觉技术的高通量斑马鱼幼鱼心脏识别和监测方法.首先通过混合高斯模型确定多斑马鱼幼鱼个体的位置和二维平面的姿态,在将其中一条斑马鱼幼鱼移动到视野中心后,基于卷积神经网络对各个幼鱼的翻滚角进行检测,并对处于异常姿态的斑马鱼幼鱼进行调整,使其心脏便于监测;在获得斑马鱼幼鱼高倍放大图像之后,根据斑马鱼幼鱼心脏的特征,提出了基于像素强度跟踪的幼鱼心脏监测算法,实现了心脏定位以及心跳检测.实验结果表明,该系统能实现对斑马鱼幼鱼心脏的准确识别并提供心跳和心率曲线,为以斑马鱼为对象的生物医学研究提供了一种新颖、稳定、高效的实验观测手段.

As a typical vertebrate model animal, zebrafish has been widely studied in the biomedical field because of its high similarity with human genes and transparent body for convenient observation. It is vital to recognize and monitor the heart of zebrafish larvae to study the pathogenesis of cardiovascular diseases and drug effects. A high-throughput heart recognition and monitoring method based on micro-vision was proposed to solve the problems of micromanipulation in the manipulation and observation of anisotropic zebrafish larvae. First, the Gaussian mixture model was used to determine the positions and directions of larvae. After one of the larvae was moved to the center of the POV of the microscope, a convolutional neural network was built to identify the roll angle of the larvae, and the larvae in abnormal postures were adjusted to make their hearts easy to monitor. After increasing magnification, a heart monitoring algorithm based on pixel intensity was proposed to realize heartbeat monitor. Experimental results show that the proposed system could realize accurate recognition and provide graphs of heartbeats and beat-rates of zebrafish larvae, which provides a novelty, stable, and efficient experimental observation method for the biomedical research of zebrafish.