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Found 5 papers, 0 papers with code
Accurately identifying vertebral levels in large datasets
We next developed an algorithm which performs iterative instance segmentation and classification of the entire spine with a 3D U-Net.
Image Translation by Latent Union of Subspaces for Cross-Domain Plaque Detection
In medical imaging applications, preserving small structures is important since these structures can carry information which is highly relevant for disease diagnosis.
Cross-Domain Medical Image Translation by Shared Latent Gaussian Mixture Model
We expect the utility of our framework will extend to other problems beyond segmentation due to the improved quality of the generated images and enhanced ability to preserve small structures.
Image Translation by Latent Union of Subspaces for Cross-Domain Plaque Segmentation
In medical imaging applications, preserving small structures is important since these structures can carry information which is highly relevant for disease diagnosis.
Lesion classification by model-based feature extraction: A differential affine invariant model of soft tissue elasticity
The outcomes of this modeling approach reached the score of area under the curve of the receiver operating characteristics of 94. 2 % for the polyps and 87. 4 % for the nodules, resulting in an average gain of 5 % to 30 % over ten existing state-of-the-art lesion classification methods.
