The conventional iterative tomographic reconstruction schemes:Landweber Descent,SIRTand theConjugate Gradient Method, are implicitly optimisation routines each seeking to minimise an objective functiontaking the form of a sum of squares. Here we leverage this property to solve for Maximum Likelihood solutionsunder various imaging noise models.