Deep learning models for enhancing cortical microtubule structures in tobacco BY-2 cells for AIVIA software

This dataset includes a series of deep learning models developed for enhancing cortical microtubule structures in tobacco BY-2 cells, designed to operate with the 2-D segmentation function of the AIVIA software. Each model was trained on a different number of images, with training set sizes ranging from N=2 to N=400. These models enable users to selectively enhance microtubule structures in confocal microscopy images, facilitating rapid and high-precision segmentation.Included Files:HlgakiLab_BY-YTRF_cMT_model_N=002.hdf5HlgakiLab_BY-YTRF_cMT_model_N=005.hdf5eHlgakiLab_BY-YTRF_cMT_model_N=010.hdf5eHlgakiLab_BY-YTRF_cMT_model_N=020.hdf5eHlgakiLab_BY-YTRF_cMT_model_N=040.hdf5eHlgakiLab_BY-YTRF_cMT_model_N=060.hdf5eHlgakiLab_BY-YTRF_cMT_model_N=080.hdf5eHlgakiLab_BY-YTRF_cMT_model_N=100.hdf5eHlgakiLab_BY-YTRF_cMT_model_N=120.hdf5eHlgakiLab_BY-YTRF_cMT_model_N=150.hdf5eHlgakiLab_BY-YTRF_cMT_model_N=200.hdf5eHlgakiLab_BY-YTRF_cMT_model_N=400.hdf5e