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Found 2 papers, 2 papers with code
Mediastinal lymph nodes segmentation using 3D convolutional neural network ensembles and anatomical priors guiding
For the 1178 lymph nodes with a short-axis diameter $\geq10$ mm, our best performing approach reached a patient-wise recall of 92%, a false positive per patient ratio of 5, and a segmentation overlap of 80. 5%.
Fast meningioma segmentation in T1-weighted MRI volumes using a lightweight 3D deep learning architecture
We studied two different 3D neural network architectures: (i) a simple encoder-decoder similar to a 3D U-Net, and (ii) a lightweight multi-scale architecture (PLS-Net).
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