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Found 5 papers, 1 papers with code
Leveraging Foundation Models for Content-Based Medical Image Retrieval in Radiology
Despite these challenges, our research underscores the vast potential of foundation models for CBIR in radiology, proposing a shift towards versatile, general-purpose medical image retrieval systems that do not require specific tuning.
Efficient Large Scale Medical Image Dataset Preparation for Machine Learning Applications
In the rapidly evolving field of medical imaging, machine learning algorithms have become indispensable for enhancing diagnostic accuracy.
Shape-based pose estimation for automatic standard views of the knee
The characteristics of the standard views of the knee suggests that the shape information of individual bones could guide an automatic positioning procedure, reducing time and the amount of unnecessary radiation during C-arm positioning.
Automatic Plane Adjustment of Orthopedic Intra-operative Flat Panel Detector CT-Volumes
The most important benefit of the MTL approach is that it is a single network for standard plane regression for all body regions with a reduced number of stored parameters.
Representing Ambiguity in Registration Problems with Conditional Invertible Neural Networks
One example is the registration of 2D X-ray images with preoperative three-dimensional computed tomography (CT) images in intraoperative surgical guidance systems.
