Biomedical Image Reconstruction

Biomedical image reconstruction aims to create high-quality images from incomplete or noisy data acquired by medical imaging modalities. Current research heavily emphasizes deep learning approaches, leveraging convolutional neural networks and other architectures to improve image resolution, reduce artifacts, and accelerate reconstruction times compared to traditional analytical and iterative methods. This field is crucial for advancing medical diagnostics and treatment planning, enabling more accurate and efficient analysis of medical images across various applications.