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Found 4 papers, 2 papers with code
Cephalometric Landmark Regression with Convolutional Neural Networks on 3D Computed Tomography Data
In this paper, we provide a wide overview of existing approaches for cephalometric landmark regression.
CHAOS Challenge -- Combined (CT-MR) Healthy Abdominal Organ Segmentation
The analysis shows that the performance of DL models for single modality (CT / MR) can show reliable volumetric analysis performance (DICE: 0. 98 $\pm$ 0. 00 / 0. 95 $\pm$ 0. 01) but the best MSSD performance remain limited (21. 89 $\pm$ 13. 94 / 20. 85 $\pm$ 10. 63 mm).
The Coherent Point Drift for Clustered Point Sets
We evaluate our approach and compare the Cluster Coherent Point Drift with other existing non-rigid point set registration methods and show it's advantages for digital medicine tasks, especially for heart template model personalization using patient's medical data.
Glioma Segmentation with Cascaded Unet
MRI analysis takes central position in brain tumor diagnosis and treatment, thus it's precise evaluation is crucially important.
