Multiple instance learning for computer aided detection and diagnosis of gastric cancer with dual-energy CT imaging
A multiple instance learning algorithm-based CAD scheme is proposed. Identify tumor invasion depth of gastric cancer with dual-energy CT imaging. We extract two-level features, bag-level features and instance-level features. We propose weighted distance Citation-KNN algorithm for classification.
multiple instance learning gastric cancer dual-energy ct computer aided diagnosis circular gabor features