A UNet++ variant with LSTM-based channel attention and multiscale feature extraction reports 98.88% accuracy and 92.74% Dice on the BUSI breast ultrasound dataset.
: A comparative study of breast cancer tumor classification by classical machine learning methods and deep learning method
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UNet++ and LSTM combined approach for Breast Ultrasound Image Segmentation
A UNet++ variant with LSTM-based channel attention and multiscale feature extraction reports 98.88% accuracy and 92.74% Dice on the BUSI breast ultrasound dataset.