Breast cancer detection from ultrasound images using attention U-nets model

Muhammad Azaz Farooq; Zhao Xuan Gong; Yu Liu; Muhammad Zubair; Arslan Manzoor; Guodong Zhang

doi:10.1117/12.2643599

12 October 2022 Breast cancer detection from ultrasound images using attention U-nets model

Muhammad Azaz Farooq, Zhao Xuan Gong, Yu Liu, Muhammad Zubair, Arslan Manzoor, Guodong Zhang

Proceedings Volume 12342, Fourteenth International Conference on Digital Image Processing (ICDIP 2022); 123420L (2022) https://doi.org/10.1117/12.2643599
Event: Fourteenth International Conference on Digital Image Processing (ICDIP 2022), 2022, Wuhan, China

Abstract

Breast cancer is the most common form of invasive cancer in women. In recent years, it has become standard practise to perform breast mass evaluations using ultrasound (US) imaging. US can accurately distinguish between malignant and benign breast masses when used by skilled radiologists, as compared to other medical imaging modalities such as MRI. Human domain knowledge is difficult to incorporate into the diagnosis of breast tumours because it differs greatly from person to person in terms of shape, border, curve, intensity, and other commonly used medical priors. A deep learning model that incorporates visual saliency can now be used to segment breast tumours in ultrasound images. Radiologists use the term "visual saliency," which refers to areas of an image that are more likely to be noticed. Features that prioritise spatial regions with high saliency levels are learned using the proposed method. According to validation results, tumours are more accurately identified in models that include attention layers than those without them. The salient attention model has the potential to improve medical image analysis accuracy and robustness by allowing deep learning architectures to incorporate task-specific knowledge. AUC-ROC plots show that our new model is more accurate in terms of IOU and AUC-ROC scores, dice score, precision, recall, and IOU.

Citation Download Citation

Muhammad Azaz Farooq, Zhao Xuan Gong, Yu Liu, Muhammad Zubair, Arslan Manzoor, and Guodong Zhang "Breast cancer detection from ultrasound images using attention U-nets model", Proc. SPIE 12342, Fourteenth International Conference on Digital Image Processing (ICDIP 2022), 123420L (12 October 2022); https://doi.org/10.1117/12.2643599

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KEYWORDS

Breast

3D modeling

Breast cancer

Image segmentation

Tumor growth modeling

Ultrasonography

Mammography

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