I have a dataset of 39 medical MR images, and I have to build a model to classify the tumor type. so is it suitable to use k-fold cross validation for validating the model? if so, what would be the number of K?
Given the size of your data set, the best approach to cross validation is the Leave-One-Out method. You haven't discussed the language or package you used for your model, but generally speaking you set the $k$ equal to the number of records. In your case, that 39. This will cause your model to train on 38 instances and predict the 39th, with each instance eventually will receive a classification.