Automatic Diagnosis of Benign and Malignant Breast Tumours Based on Deep Learning
Ultrasound is now one of the common means of diagnosing breast tumours.To address the problems of similar tex-ture and low differentiation between benign and malignant tumours in ultrasound,this paper proposes a deep learning-based auto-matic diagnosis model for benign and malignant breast ultrasound to assist doctors in diagnosis.This paper uses Densenet to enhance detailed feature extraction,attention mechanisms to simulate clinical diagnosis,and transfer learning to alleviate data dependency.The experimental results show that the model can provide a good aid to diagnosis for young doctors,with good reliability and clinical utility.
breast tumoursultrasound imagesattentional mechanismstransfer learning
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