Saurabh Joshi, André Forjaz, Kyu Sang Han, Yu Shen, Daniel Xenes, Jordan Matelsky, Brock Wester, Arrate Munoz Barrutia, Ashley L Kiemen, Pei-Hsun Wu, Denis Wirtz
The development of novel imaging platforms has improved our ability to collect and analyze large three-dimensional (3D) biological imaging datasets. Advances in computing have led to an ability to extract complex spatial information from these data, such as the composition, morphology, and interactions of multi-cellular structures, rare events, and integration of multi-modal features combining anatomical, molecular, and transcriptomic (among other) information. Yet, the accuracy of these quantitative results is intrinsically limited by the quality of the input images, which can contain missing or damaged regions, or can be of poor resolution due to mechanical, temporal, or financial constraints...
March 12, 2024: bioRxiv