Keywords: Machine Learning/Artificial Intelligence, Machine Learning/Artificial IntelligenceMost veterinary imaging has been achieved using human MRI scanners. Therefore, extensive averaging is required to obtain high-resolution images with high SNR for the animals, thereby leading to a long scan time. Veterinary MRI is typically performed under general anesthesia to minimize the level of stress and movement during image scanning. Therefore, long anesthetic conditions could affect animal normal physiology and be life-threatening, especially for patients in veterinary medical field. Here, we aimed to obtain higher image quality with short scanning time using super-resolution generative adversarial network (SRGAN) in the canine brain MRI.
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