Artificial intelligence (AI) is an exciting technology that has the potential to transform endodontics. Recent advances include the application of AI to improve the detection and classification of anatomic structures and of endodontic disease, such a... read more
While potentially revolutionary, the application of artificial intelligence (AI) in periodontology is in its early stages of development. AI tools hold promise in diagnosis, risk assessment and of progression, and treatment outcomes of periodontitis ... read more
Pneumonia clinical decision support (CDS) has evolved from simple paper-based guidelines to complex electronic systems powered by artificial intelligence. By harmonizing risk stratification, diagnostic testing, antibiotic selection and standardizing ... read more
Paleoradiology, the use of modern imaging technologies to study archaeological and anthropological remains, offers new windows on millennial scale patterns of human health. Unfortunately, the radiographs collected during field campaigns are heterogen... read more
While representation alignment with self-supervised models has been shown to improve diffusion model training, its potential for enhancing inference-time conditioning remains largely unexplored. We introduce Representation-Aligned Guidance (REPA-G), ... read more
Most vision models are trained on RGB images processed through ISP pipelines optimized for human perception, which can discard sensor-level information useful for machine reasoning. RAW images preserve unprocessed scene data, enabling models to lever... read more
Human vision is foveated, with variable resolution peaking at the center of a large field of view; this reflects an efficient trade-off for active sensing, allowing eye-movements to bring different parts of the world into focus with other parts of th... read more
Introduction: In neurosurgery, image-guided Neurosurgery Systems (IGNS) highly rely on preoperative brain magnetic resonance images (MRI) to assist surgeons in locating surgical targets and determining surgical paths. However, brain shift invalidates... read more
Stochastic interpolants unify flows and diffusions, popular generative modeling frameworks. A primary hyperparameter in these methods is the interpolation schedule that determines how to bridge a standard Gaussian base measure to an arbitrary target ... read more
A key challenge in autoregressive image generation is to efficiently sample independent locations in parallel, while still modeling mutual dependencies with serial conditioning. Some recent works have addressed this by conditioning between scales in ... read more
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