The binary cross entropy and categorical cross entropy should produce equivalent loss values in the case of binary classification, and the weights in the dense layer for the 2 output case should be the negatives of each other, so in most cases it won’t matter.
This isn’t true if you’re using label smoothing, and numerical precision issues could cause them to produce slightly different outputs, but in general there is little reason to prefer one over the other.