Bone Suppression

Bone suppression techniques aim to digitally remove or reduce the obscuring effects of bone structures in medical images, primarily chest X-rays and ultrasound, to improve the visibility of underlying soft tissues and aid in disease diagnosis. Current research heavily utilizes deep learning, employing convolutional neural networks (CNNs) and diffusion models, often incorporating U-Net architectures, to achieve this suppression while preserving crucial image details. These advancements are significant because they offer a potential alternative to existing methods that are either time-consuming, require specialized equipment, or produce suboptimal results, ultimately improving the accuracy and efficiency of medical image analysis.