Puybareau Elodie, Genest Diane, Barbeau Emilie, Léonard Marc, Talbot Hugues
Université Paris-Est, LIGM (UMR 8049), CNRS, ENPC, ESIEE, UPEM, 2 Boulevard Blaise Pascal, 93162 Noisy-le-Grand, France.
Université Paris-Est, LIGM (UMR 8049), CNRS, ENPC, ESIEE, UPEM, 2 Boulevard Blaise Pascal, 93162 Noisy-le-Grand, France; L'OREAL Research & Innovation, Aulnay sous Bois, France.
Comput Biol Med. 2017 Feb 1;81:32-44. doi: 10.1016/j.compbiomed.2016.12.007. Epub 2016 Dec 15.
Studies on fish embryo models are widely developed in research. They are used in several research fields including drug discovery or environmental toxicology. In this article, we propose an entirely automated assay to detect cardiac arrest in Medaka (Oryzias latipes) based on image analysis. We propose a multi-scale pipeline based on mathematical morphology. Starting from video sequences of entire wells in 24-well plates, we focus on the embryo, detect its heart, and ascertain whether or not the heart is beating based on intensity variation analysis. Our image analysis pipeline only uses commonly available operators. It has a low computational cost, allowing analysis at the same rate as acquisition. From an initial dataset of 3192 videos, 660 were discarded as unusable (20.7%), 655 of them correctly so (99.25%) and only 5 incorrectly so (0.75%). The 2532 remaining videos were used for our test. On these, 45 errors were made, leading to a success rate of 98.23%.
鱼类胚胎模型研究在科研中得到广泛开展。它们被应用于包括药物研发或环境毒理学在内的多个研究领域。在本文中，我们提出了一种基于图像分析来检测青鳉（Oryzias latipes）心脏骤停的全自动化检测方法。我们提出了一种基于数学形态学的多尺度流程。从24孔板中整个孔的视频序列开始，我们聚焦于胚胎，检测其心脏，并基于强度变化分析确定心脏是否在跳动。我们的图像分析流程仅使用常用的算子。它具有较低的计算成本，能够以与采集相同的速率进行分析。在最初的3192个视频数据集中，660个被作为不可用数据丢弃（20.7%），其中655个丢弃正确（99.25%），只有5个丢弃错误（0.75%）。剩下的2532个视频用于我们的测试。在这些视频上，出现了45个错误，成功率为98.23%。
