BTS-ST: Swin transformer network for segmentation and classification of multimodality breast cancer images.
Ahmed IqbalMuhammad SharifPublished in: Knowl. Based Syst. (2023)
Keyphrases
- breast cancer
- mammogram images
- benign and malignant
- breast tissue
- breast cancer diagnosis
- computer aided detection
- segmentation algorithm
- segmentation method
- early detection
- early detection of breast cancer
- skin lesion
- lung nodules
- digital mammography
- mammographic images
- segmentation accuracy
- bladder cancer
- image analysis
- fully automatic
- computer aided diagnosis
- diagnosis of breast cancer
- fractal analysis
- cancer datasets
- logistic regression
- dce mri
- breast cancer detection
- accurate segmentation
- automated segmentation
- microcalcification clusters
- quantitative evaluation
- input image
- image segmentation
- cell segmentation
- feature selection
- decision trees
- edge detection
- digital mammograms
- medical images
- feature vectors
- support vector
- cad systems
- low contrast
- region of interest
- classification accuracy
- cancer diagnosis
- textural features
- machine learning
- image features
- text classification
- level set