Generative Active Learning with Variational Autoencoder for Radiology Data Generation in Veterinary Medicine

arXiv:2403.03642v1 Announce Type: cross
Abstract: Recently, with increasing interest in pet healthcare, the demand for computer-aided diagnosis (CAD) systems in veterinary medicine has increased. The development of veterinary CAD has stagnated due to a lack of sufficient radiology data. To overcome the challenge, we propose a generative active learning framework based on a variational autoencoder. This approach aims to alleviate the scarcity of reliable data for CAD systems in veterinary medicine. This study utilizes datasets comprising cardiomegaly radiograph data. After …

abstract active learning arxiv autoencoder cad challenge computer cs.cv cs.lg data demand development diagnosis eess.iv generative healthcare medicine pet radiology systems type veterinary