A generative adversarial network (GAN) is one of the most significant research directions in
the field of artificial intelligence, and its superior data generation capability has garnered …

Neural network-based approaches can achieve high accuracy in various medical image
segmentation tasks. However, they generally require large labelled datasets for supervised …

Purpose Orbital decompression for thyroid-associated ophthalmopathy (TAO) is an
ophthalmic plastic surgery technique to prevent optic neuropathy and reduce exophthalmos …

Abstract The Generative Adversarial Network (GAN) is commonly used for medical image
augmentation, a method to alleviate the data shortage for downstream tasks. However …

Rapid and accurate classification of medical images plays an important role in medical
diagnosis. Nowadays, for medical image classification, there are some methods based on …

The generation-based data augmentation method can overcome the challenge caused by
the imbalance of medical image data to a certain extent. However, most of the current …

Data annotation is a fundamental precursor for establishing large training sets to effectively
apply deep learning methods to medical image analysis. For cell segmentation, obtaining …

Purpose It is of great significance to accurately identify the KRAS gene mutation status for
patients in tumor prognosis and personalized treatment. Although the computer‐aided …

The increasing efficiency and compactness of deep learning architectures, together with
hardware improvements, have enabled the complex and high-dimensional modelling of …

Abstract Machine learning methods heavily rely on the availability of large annotated
datasets of a certain domain for training. However, freely available datasets of patients with …