论文标题
共聚焦图像的3D细胞形状识别的人工神经网络
Artificial neural networks for 3D cell shape recognition from confocal images
论文作者
论文摘要
我们提出了一个双阶段神经网络体系结构，用于分析3D中显微镜记录的细节。该系统在红细胞上进行了测试，使用了健康供体和先天性血液疾病患者的培训数据。从每个单元的球形谐波频谱中揭示了特征形状的特征，并会自动处理以创建可重复且无偏的形状识别和分类，以诊断和近视使用。
We present a dual-stage neural network architecture for analyzing fine shape details from microscopy recordings in 3D. The system, tested on red blood cells, uses training data from both healthy donors and patients with a congenital blood disease. Characteristic shape features are revealed from the spherical harmonics spectrum of each cell and are automatically processed to create a reproducible and unbiased shape recognition and classification for diagnostic and theragnostic use.
