Provided in the present invention are a segmentation model training method and apparatus, and a computer-readable storage medium. The method comprises: inputting collected heart CT images into a deep learning network model for training to obtain a first segmentation result of each heart CT image; performing, based on a reinforcement learning method, fine adjustment on the first segmentation result according to ventricular position information and the first segmentation result to obtain a second segmentation result; and performing iterative training on the deep learning network model according to the second segmentation result and the ventricular position information, and taking the trained deep learning network model as a segmentation model for segmenting the myocardium of the heart. A segmentation model capable of automatically performing ventricle segmentation on heart CT images can be obtained through training a deep learning network model by means of taking the heart CT images and ventricular position information of each heart CT image as training data; and furthermore, a segmentation model with higher segmentation precision can be obtained by performing fine adjustment and iterative training by means of combining a reinforcement learning method.
SEGMENTATION MODEL TRAINING METHOD AND APPARATUS, AND COMPUTER-READABLE STORAGE MEDIUM