DeepD3 - A deep learning framework for detection of dendritic spines and dendrites
Andreas Kist, Martin H P Fernholz, Drago A Guggiana Nilo, Tobias Bonhoeffer · FENS Forum 2024
Dendritic spines are the seat of most excitatory synapses in the brain, and a cellular structure considered central to learning, memory, and activity-dependent plasticity. Typically, humans quantify dendritic spines from light microscopy data in a manual painstaking, error-prone process. We found that human-to-human variability is substantial (inter-rater reliability 82.2±6.4 %), raising concerns about the reproducibility of experiments and the validity of using human-annotated 'ground truth' as an evaluation method for computational approaches of spine identification. To address this, we pres
ePoster · Neuroscience