The invention relates to a novel mammary gland MRI automatic auxiliary diagnosis method based on a fusion attention mechanism. The novel mammary gland MRI automatic auxiliary diagnosis method comprises the following steps: S1, manually selecting a mammary gland segmentation data set, training a DenseUNet model, inputting a TSE sequence of mammary glands into the trained DenseUNet model for mammarygland segmentation, and removing organs interfering with tumor detection in the thoracic cavity; S2, mapping the segmentation result obtained in the step S1 to a DCE sequence, to obtaining the segmented mammary tissues, inputting the segmented mammary tissues into an ADUNet model with an attention mechanism to perform tumor segmentation, and aiming at the problems of class imbalance and difficultsamples, adopting Focal Loss in a training process to prevent the model from deviating; S3, inputting the result obtained in the S2 into a lightweight neural network, and carrying out benign and malignant judgment to obtain an auxiliary diagnosis result. According to the invention, the end-to-end breast cancer auxiliary diagnosis can be realized without manual intervention, and the diagnosis efficiency and accuracy can be greatly improved.