4D Cellular Morphology Atlas Construction Simultaneously Reveals Shape-adhesion Patterns During Embryogenesis

<p dir="ltr"><b>3D Shape Training: </b>Ground truth (GT) for training membrane recognition (TUNETr)</p><p dir="ltr"><b>3D Shape Evaluation: </b>GT for evaluation and comparison of segmentation</p><p dir="ltr"><b>2D Time-lapse Evaluation: </b>GT for time-lapse embryos (cell morphology map)</p><p dir="ltr"><b>Nuclei Generative Training: </b>GT for training m2nGAN (pseudo nuclei image generation) with real stained fluorescence images</p><p dir="ltr"><b>Nuclei Generative Evaluation: </b>GT for evaluating m2nGAN (pseudo nuclei image generation) with real stained fluorescence images</p><p dir="ltr"><b>Shape-adhesion E-cadherin</b>: Dataset for discovering shape-adhesion patterns</p><p dir="ltr"><b>GUI DATA Cell Wise</b>: drive.google.com/drive/folders/11jgB8V3IMPRL6tE7b9dv-4TBnC8dWlkH?usp=sharing (GUIDataCellWise)</p><p dir="ltr"><br></p><p dir="ltr"><b>CTransformer (mainly TUNETr) Code Link</b>: github.com/chiellini/CTransformer</p><p dir="ltr"><b>m2nGAN Code Link:</b> github.com/chiellini/m2nGAN</p><p dir="ltr"><b>Image Processing Python Script Link:</b> github.com/chiellini/CImageProcessor</p><p dir="ltr"><b>Visualization Python Script Link: </b>github.com/chiellini/GUIData</p>