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00925njm 22002777a 4500 dc Bustince, Humberto author Pagola, Miguel author Fernández, Javier author Melo Pinto, P. author Couto, P. author Tizhoosh, H. R. author Montero De Juan, Francisco Javier author 2010 In this paper, we define the concept of an ignorance function and use it to determine the best threshold with which to binarize an image. We introduce a method to construct such functions from t-norms and automorphisms. By means of these new measures, we represent the degree of ignorance of the expert when given one fuzzy set to represent the background and another to represent the object. From this ignorance degree, we assign interval-valued fuzzy sets to the image in such a way that the best threshold is given by the interval-valued fuzzy set with the lowest associated ignorance. We prove that the proposed method provides better thresholds than the fuzzy classical methods when applied to transrectal prostateultrasoundimages. The experimental results on ultrasound and natural images also allow us to determine the best choice of the function to represent the ignorance. Bustince, H., Pagola, M., Barrenechea, E., Fernandez, J., Melo-Pinto, P., Couto, P., Tizhoosh, H.R., Montero, J.: Ignorance functions. An application to the calculation of the threshold in prostate ultrasound images. Fuzzy Sets and Systems. 161, 20-36 (2010). https://doi.org/10.1016/j.fss.2009.03.005 0165-0114 10.1016/j.fss.2009.03.005 https://hdl.handle.net/20.500.14352/42262 https//doi.org/10.1016/j.fss.2009.03.005 http://www.sciencedirect.com/science/article/pii/S0165011409001389 Ignorance functions. An application to the calculation of the threshold in prostate ultrasound images.