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Found 3 papers, 3 papers with code
cRedAnno+: Annotation Exploitation in Self-Explanatory Lung Nodule Diagnosis
Recently, attempts have been made to reduce annotation requirements in feature-based self-explanatory models for lung nodule diagnosis.
Auto-segmentation of Hip Joints using MultiPlanar UNet with Transfer learning
Accurate geometry representation is essential in developing finite element models.
Reducing Annotation Need in Self-Explanatory Models for Lung Nodule Diagnosis
Visualisation of the learned space further indicates that the correlation between the clustering of malignancy and nodule attributes coincides with clinical knowledge.
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