Automated chromosome instance segmentation from metaphase cell microscopic images is critical for the diagnosis of chromosomal disorders (i.e., karyotype analysis). However, it is still a challenging task due to lacking of densely annotated datasets and the complicated morphologies of chromosomes, e.g., dense distribution, arbitrary orientations, and wide range of lengths. To facilitate the development of this area, we take a big step forward and manually construct a large-scale densely annotated dataset named AutoKary2022, which contains over 27,000 chromosome instances in 612 microscopic images from 50 patients. Specifically, each instance is annotated with a polygonal mask and a class label to assist in precise chromosome detection and segmentation. On top of it, we systematically investigate representative methods on this dataset and obtain a number of interesting findings, which helps us have a deeper understanding of the fundamental problems in chromosome instance segmentation. We hope this dataset could advance research towards medical understanding. The dataset can be available at: https://github.com/wangjuncongyu/chromosome-instance-segmentation-dataset.
翻译:从分裂期细胞显微图像中自动分割染色体实例对诊断染色体异常(即核型分析)具有至关重要的意义。然而,由于缺乏密集标注数据集以及染色体形态的复杂性,例如密集分布、任意方向和广泛的长度,该任务仍然具有挑战性。为了促进这一领域的发展,我们迈出了一大步,手动构建了一个名为AutoKary2022的大规模密集注释数据集,其中包含来自50名患者的612张显微图像中的超过27,000个染色体实例。具体而言,每个实例都用多边形掩码和类别标签进行了注释,以帮助精准地检测和分割染色体。在此基础上,我们系统地调查了这个数据集上的代表性方法,并得出了许多有趣的发现,这有助于我们更深入地了解染色体实例分割中的基本问题。我们希望这个数据集能推进医学理解的研究。该数据集可在以下网址上获得: https://github.com/wangjuncongyu/chromosome-instance-segmentation-dataset。