M3Net achieves state-of-the-art accuracies of 86.96% on LIDC-IDRI and 84.24% on USTC-FHLN for pulmonary nodule classification using a hierarchical multi-scale 3D network with cross-scale consistency.
EMeR- ALDS: Electronic Medical Record Driven Automated Lung Nodule Detection and Classification in Thoracic CT Images
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M3Net: A Macro-to-Meso-to-Micro Clinical-inspired Hierarchical 3D Network for Pulmonary Nodule Classification
M3Net achieves state-of-the-art accuracies of 86.96% on LIDC-IDRI and 84.24% on USTC-FHLN for pulmonary nodule classification using a hierarchical multi-scale 3D network with cross-scale consistency.