Unleashing the Strengths of Unlabeled Data in Pan-cancer Abdominal Organ Quantification: the FLARE22 Challenge
Quantitative organ assessment is an essential step in automated abdominal disease diagnosis and treatment planning. Artificial intelligence (AI) has shown great potential to automatize this...
Cine-MRI detection of abdominal adhesions with spatio-temporal deep learning
Adhesions are an important cause of chronic pain following abdominal surgery. Recent developments in abdominal cine-MRI have enabled the non-invasive diagnosis of adhesions. Adhesions are...
Beyond Pixels: Medical Image Quality Assessment with Implicit Neural Representations
Uncertainty-Guided Self-learning Framework for Semi-supervised Multi-organ Segmentation
Beyond Pixels: Medical Image Quality Assessment with Implicit Neural Representations
Artifacts pose a significant challenge in medical imaging, impacting diagnostic accuracy and downstream analysis. While image-based approaches for detecting artifacts can be effective, they often...
Steerable Anatomical Shape Synthesis with Implicit Neural Representations
Generative modeling of anatomical structures plays a crucial role in virtual imaging trials, which allow researchers to perform studies without the costs and constraints inherent to in vivo and...
Medical diffusion on a budget: Textual Inversion for medical image generation
Diffusion models for text-to-image generation, known for their efficiency, accessibility, and quality, have gained popularity. While inference with these systems on consumer-grade GPUs is...