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In this paper, a computationally effective and explainable Vision Transformer (ViT)-based framework is also suggested that can be used to perform automated classification of ultrasound images of the breast into benign, malignant, and normal issues. The pipeline combines paired image-mask representation, class-weighted training
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In this paper, a computationally effective and explainable Vision Transformer (ViT)-based framework is also suggested that can be used to perform automated classification of ultrasound images of the breast into benign, malignant, and normal issues. The pipeline combines paired image-mask representation, class-weighted training In this paper, a computationally effective and explainable Vision Transformer (ViT)-based framework is also suggested that can be used to perform automated classification of ultrasound images of the breast into benign, malignant, and normal issues. The pipeline combines paired image-mask representation, class-weighted training In this paper, a computationally effective and explainable Vision Transformer (ViT)-based framework is also suggested that can be used to perform automated classification of ultrasound images of the breast into benign, malignant, and normal issues. The pipeline combines paired image-mask representation, class-weighted training
