Noise reduction of imaging data

摘要

The present invention relates to systems and methods for reducing noise in image data. Preferred embodiments relate to methods for analyzing two-photon in vivo imaging of biological systems. With neuronal population imaging with subcellular resolution, this modality offers an approach for gaining a fundamental understanding of brain anatomy and physiology. Analysis of calcium imaging data requires denoising, that is separating the signal from complex physiological noise. To analyze two-photon brain imaging data, for example, harmonic regression plus colored noise model and an efficient cyclic descent algorithm for parameter estimation. This approach reliably separates stimulus-evoked fluorescence response from background activity and noise, assesses goodness of fit, and estimates confidence intervals and signal-to-noise ratio.

主权项

1. A computer implemented method for reducing a noise component of image data comprising:
stimulating a sensory response in a region of interest in a biological material with a stimulus to induce a neural response; detecting signals associated with the neural response in a plurality of cells that are spatially distributed within the biological material to generate detected neural response image data; recording the detected neural response image data; processing the neural response image data with a data processor, the data processor being programmed to process the neural response image data with an analytic representation to separate a stimulus response component and a noise component, the stimulus response component being represented by a vector having an order determined by a convergent iterative process; and generating processed neural response image data to generate reduced noise neural response image data.