This study proposes an enhancement to the ConText-GAN, an image synthesis model using a controllable texture input. The improvement consists in using a texture feature fusion module to reduce the complexity of the model, and enable the use of the OASIS architecture for image generation. Clinical relevance— The ConText-GAN can be used to generate images of fake patients, which are useful in the medical field due to the scarcity of data. An example is given of the generation of images showing pathological muscle tissue in the context of neuromuscular diseases.