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LitCall: Learning Implicit Topology for CNN-based Aortic Landmark Localization
Given that the thoracic aorta has a relatively conserved topology across the population and that a human annotator with minimal training can estimate the location of unseen landmarks from limited examples, we proposed an auxiliary learning task to learn the implicit topology of aortic landmarks through a CNN-based network.
Lung Cancer Lesion Detection in Histopathology Images Using Graph-Based Sparse PCA Network
In this paper, we propose a simple machine learning approach called the graph-based sparse principal component analysis (GS-PCA) network, for automated detection of cancerous lesions on histological lung slides stained by hematoxylin and eosin (H&E).
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