Abstract: Certain aspects of the present disclosure provide techniques for training a tumor detection model. A method generally includes processing an input scan image of a tumor in a first state using a first computational model configured to simulate growth of the tumor in a first configuration to generate model output images of the simulated tumor comprising at least a first model output image representing the tumor in a second state, wherein the first model output image comprises a timestamp associated with the second state, training a first machine learning model to convert the first model output image to a first synthesized scan image, and training a second machine learning model to detect the simulated tumor in image data using the first synthesized scan image and the input scan image.