Abstract: A computer implemented method for reading a test region of an assay, the method comprising: (i) providing digital image data of a first assay; (ii) inputting the digital image data into a trained convolutional neural network configured to output a first probability, based on the input digital image data, that a first region of pixels of the digital image data corresponds to a first test region of the assay; (iii) if the first probability is at or above a first predetermined threshold, accepting the first region of pixels as a first region of interest associated with the first test region; and (iv) estimating an intensity value of a portion of the first test region in the first region of interest.

Abstract: A computer implemented method for reading a test region of an assay, the method comprising: (i) providing digital image data of a first assay; (ii) inputting the digital image data into a trained convolutional neural network configured to output a first probability, based on the input digital image data, that a first region of pixels of the digital image data corresponds to a first test region of the assay; (iii) if the first probability is at or above a first predetermined threshold, accepting the first region of pixels as a first region of interest associated with the first test region; and (iv) estimating an intensity value of a portion of the first test region in the first region of interest.