Search Results for author:
Found 10 papers, 2 papers with code
Confidence intervals uncovered: Are we ready for real-world medical imaging AI?
For more than 60% of papers, the mean performance of the second-ranked method was within the CI of the first-ranked method.
Quality Assured: Rethinking Annotation Strategies in Imaging AI
Our work could enable researchers to derive substantially more value from a fixed annotation budget and change the way annotation companies conduct internal QA.
Understanding metric-related pitfalls in image analysis validation
Validation metrics are key for the reliable tracking of scientific progress and for bridging the current chasm between artificial intelligence (AI) research and its translation into practice.
Labeling instructions matter in biomedical image analysis
Here, we present the first systematic study of labeling instructions and their impact on annotation quality in the field.
Metrics reloaded: Recommendations for image analysis validation
The framework was developed in a multi-stage Delphi process and is based on the novel concept of a problem fingerprint - a structured representation of the given problem that captures all aspects that are relevant for metric selection, from the domain interest to the properties of the target structure(s), data set and algorithm output.
Semantic segmentation of multispectral photoacoustic images using deep learning
Due to the intuitive representation of high-dimensional information, such a preprocessing algorithm could be a valuable means to facilitate the clinical translation of photoacoustic imaging.
Common Limitations of Image Processing Metrics: A Picture Story
While the importance of automatic image analysis is continuously increasing, recent meta-research revealed major flaws with respect to algorithm validation.
Photoacoustic image synthesis with generative adversarial networks
Photoacoustic tomography (PAT) has the potential to recover morphological and functional tissue properties with high spatial resolution.
Tattoo tomography: Freehand 3D photoacoustic image reconstruction with an optical pattern
Methods: In this paper, we present a novel approach to 3D reconstruction of PAT data (Tattoo tomography) that does not require an external tracking system and can smoothly be integrated into clinical workflows.
Surgical Data Science -- from Concepts toward Clinical Translation
We further complement this technical perspective with (4) a review of currently available SDS products and the translational progress from academia and (5) a roadmap for faster clinical translation and exploitation of the full potential of SDS, based on an international multi-round Delphi process.
