Accurate segmentation of zebrafish from bright-field microscope images is crucial to many applications in the life sciences. Early zebrafish stages are used, and in these stages the zebrafish is partially transparent. This transparency leads to edge ambiguity as is typically seen in the larval stages. Therefore, segmentation of zebrafish objects from images is a challenging task in computational bio-imaging. Popular computational methods fail to segment the relevant edges, which subsequently results in inaccurate measurements and evaluations. Here we present a hybrid method to accomplish accurate and efficient segmentation of zebrafish specimens from bright-field microscope images. We employ the mean shift algorithm to augment the colour representation in the images. This improves the discrimination of the specimen to the background and provides a segmentation candidate retaining the overall shape of the zebrafish. A distance-regularised level set function is initialised from this segmentation candidate and fed to an improved level set method, such that we can obtain another segmentation candidate which preserves the explicit contour of the object. The two candidates are fused using heuristics, and the hybrid result is refined to represent the contour of the zebrafish specimen. We have applied the proposed method on two typical datasets. From experiments, we conclude that the proposed hybrid method improves both efficiency and accuracy of the segmentation of the zebrafish specimen. The results are going to be used for high-throughput applications with zebrafish.

中文翻译：

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一种有效且稳健的混合方法，用于从明场显微镜图像中分割斑马鱼物体。

从明场显微镜图像中准确分割斑马鱼对于生命科学中的许多应用至关重要。使用斑马鱼的早期阶段，在这些阶段，斑马鱼是部分透明的。这种透明度会导致边缘模糊，这在幼虫阶段很常见。因此，从图像中分割斑马鱼对象是计算生物成像中的一项具有挑战性的任务。流行的计算方法无法分割相关边缘，从而导致测量和评估不准确。在这里，我们提出了一种混合方法，可以从明场显微镜图像中实现斑马鱼标本的准确有效的分割。我们采用均值平移算法来增强图像中的颜色表示。这提高了样本与背景的辨别力，并提供了保留斑马鱼整体形状的分割候选者。从该分割候选对象初始化距离正则化水平集函数，并将其馈送到改进的水平集方法，以便我们可以获得另一个保留对象的显式轮廓的分割候选对象。使用启发式方法融合两个候选者，并对混合结果进行细化以表示斑马鱼标本的轮廓。我们已将所提出的方法应用于两个典型的数据集。从实验中，我们得出结论，所提出的混合方法提高了斑马鱼标本分割的效率和准确性。结果将用于斑马鱼的高通量应用。