BioTISR: Microtubules (3D)

3D microtubules data of BioTISR dataset. BioTISR is a biological image dataset for super-resolution microscopy, currently including 2D and 3D time-lapse image pairs of low-and-high resolution images of a variety of biology structures, aiming to provide a high-quality dataset of time-lapse biological SR images for the community to spark more developments of computational SR methods. At present, 2D dataset includes five specimens (clathrin-coated pits, lysosomes, outer mitochondrial membrane, microtubules, and F-actin) acquired with the GI/TIRF-SIM mode and nonlinear SIM mode of our Multi-SIM system, and 3D data includes three specimens (outer mitochondrial membrane, microtubules, and F-actin) acquired with 3D-SIM mode of the Multi-SIM system. For each type of specimen and each imaging modality, we acquired the raw data from at least 50 distinct regions-of-interest (ROI). For each ROI, we acquired two (3D data) or three (2D data) groups of N-phase × M-orientation × T-timepoint raw images with a constant exposure time but increasing the excitation light intensity, where (N, M, T) are (3, 3, 20) for TIRF-SIM and GI-SIM, (5, 5, 10) for nonlinear SIM, and (3, 5, 10) for 3D-SIM. The BioTISR dataset is related to the following paper:Chang Qiao, Shuran Liu, Yuwang Wang, Wencong Xu, et al. "Time-lapse Image Super-resolution Neural Network with Reliable Confidence Evaluation for Optical Microscopy." bioRxiv 2024.05.04.592503 (2024), which is an extension of our previously published BioSR dataset (https://www.nature.com/articles/s41592-020-01048-5).BioTISR数据集的三维微管数据。 BioTISR是一款面向超分辨率显微镜的生物图像数据集，目前涵盖多种生物结构的低分辨率与高分辨率图像的二维、三维时序图像对，旨在为学界提供高质量的时序生物超分辨率（Super-resolution, SR）图像数据集，以推动计算超分辨率方法的进一步发展。 目前，二维数据集包含5类标本：网格蛋白包被小窝、溶酶体、线粒体外膜、微管以及肌动蛋白丝（F-actin），采集自本团队Multi-SIM系统的GI/TIRF-SIM模式与非线性结构光照显微镜（Structured Illumination Microscopy, SIM）模式；三维数据集则包含3类标本：线粒体外膜、微管以及肌动蛋白丝，采集自Multi-SIM系统的3D-SIM模式。针对每一类标本与每一种成像模态，我们均从至少50个独立的感兴趣区域（Region-of-Interest, ROI）获取原始数据。对于每个感兴趣区域，我们采集了两组（三维数据）或三组（二维数据）N相位×M方位×T时间点的原始图像，所有图像的曝光时间固定，但激发光强度依次递增，其中TIRF-SIM与GI-SIM的(N, M, T)参数为(3, 3, 20)，非线性SIM为(5, 5, 10)，3D-SIM为(3, 5, 10)。 BioTISR数据集关联以下论文：Chang Qiao、Shuran Liu、Yuwang Wang、Wencong Xu等发表于预印本平台bioRxiv的《面向光学显微镜的带可靠置信度评估的时序图像超分辨率神经网络》，论文编号为bioRxiv 2024.05.04.592503 (2024)。该数据集是本团队此前发布的BioSR数据集的扩展版本，原BioSR数据集链接为：https://www.nature.com/articles/s41592-020-01048-5。