Explore a comprehensive tutorial on calcium imaging data cell extraction techniques, focusing on the CNMF-E method developed for analyzing microendoscopic data. Learn about the challenges of extracting single-neuronal activity from microendoscopic recordings and how CNMF-E improves upon existing methods. Dive into the matrix factorization approach, which accurately separates background fluctuations and simultaneously demixes and denoises neuronal signals. Compare CNMF-E with independent components analysis and constrained nonnegative matrix factorization approaches, and discover its superior performance in detecting well-isolated neural signals, especially in noisy data regimes. Follow along with a hands-on demonstration of the MATLAB version of CNMF-E, applicable to both 1-photon microendoscopic and 2-photon imaging data. Gain insights into the method's framework, including background modeling, optimization problems, and the overall pipeline for cell extraction.