HAGAN: Hybrid Augmented Generative Adversarial Network for Medical Image Synthesis

arXiv:2405.04902v1 Announce Type: cross
Abstract: Medical Image Synthesis (MIS) plays an important role in the intelligent medical field, which greatly saves the economic and time costs of medical diagnosis. However, due to the complexity of medical images and similar characteristics of different tissue cells, existing methods face great challenges in meeting their biological consistency. To this end, we propose the Hybrid Augmented Generative Adversarial Network (HAGAN) to maintain the authenticity of structural texture and tissue cells. HAGAN contains Attention Mixed …

abstract adversarial arxiv cells challenges complexity costs cs.cv diagnosis economic eess.iv face generative generative adversarial network however hybrid image images intelligent medical medical field network role synthesis type