Imaging Pipeline

Imaging pipelines encompass the entire process of acquiring, processing, and analyzing images, with a current research focus on improving robustness and mitigating biases. This involves leveraging deep learning models, particularly convolutional neural networks (CNNs), for tasks like image age estimation, segmentation, and enhancement, often within the context of standardized frameworks like DICOM and MONAI. Significant efforts are dedicated to addressing challenges such as uncertainty quantification, data imbalance leading to demographic bias, and adversarial attacks targeting image processing stages. These advancements are crucial for reliable and trustworthy applications across diverse fields, including medical imaging and forensic analysis.