Shaping the Future through Innovations: From Medical Imaging to Precision Medicine
Medical images constitute a source of information essential for disease diagnosis, treatment and follow-up. In addition, due to its patient-specific nature, imaging information represents a critical component required for advancing precision medicine into clinical practice. This manuscript describes recently developed technologies for better handling of image information: photorealistic visualization of medical images with Cinematic Rendering, artificial agents for in-depth image understanding, support for minimally invasive procedures, and patient-specific computational models with enhanced predictive power. Throughout the manuscript we will analyze the capabilities of such technologies and extrapolate on their potential impact to advance the quality of medical care, while reducing its cost.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Foundation Models for Medical Imaging: Status, Challenges, and Directions
Foundation models (FMs) are rapidly reshaping medical imaging, shifting the field from narrowly trained, task-specific networks toward large, general-purpose models that can be adapted across modalities, anatomies, and c…
Recent Advances in Medical Imaging Segmentation: A Survey
Medical imaging is a cornerstone of modern healthcare, driving advancements in diagnosis, treatment planning, and patient care. Among its various tasks, segmentation remains one of the most challenging problem due to fac…
Domain AdaptationFew-Shot LearningImage SegmentationMedical Image Segmentation+3Deep Learning in Medical Image Registration: A Survey
The establishment of image correspondence through robust image registration is critical to many clinical tasks such as image fusion, organ atlas creation, and tumor growth monitoring, and is a very challenging problem. S…
Deep LearningImage RegistrationMedical Image RegistrationSurveyContinual Learning in Medical Imaging: A Survey and Practical Analysis
Deep Learning has shown great success in reshaping medical imaging, yet it faces numerous challenges hindering widespread application. Issues like catastrophic forgetting and distribution shifts in the continuously evolv…
Continual LearningSurveyBrain Imaging Foundation Models, Are We There Yet? A Systematic Review of Foundation Models for Brain Imaging and Biomedical Research
Foundation models (FMs), large neural networks pretrained on extensive and diverse datasets, have revolutionized artificial intelligence and shown significant promise in medical imaging by enabling robust performance wit…
Data Integration