Discrimination of benign and malignant solid breast masses using deeprn residual leaing-based bimodal computer-aided diagnosis system
A bimodal deep residual learning model is proposed for solid mass classification. Suitable combinations of the deep features are implemented using feature-maps fusion. Six different configurations evaluated to find the best one for our framework. Experiments demonstrated significant improvements over previous SOA results.
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