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Cancer surveillance, early diagnosis, treatment, and prognosis assessment are issues of great concern to medical systems around the world. Ultrasound, as one of the most widely used imaging modalities, has been used in diagnosing and supervising tumors of thyroid, breast, liver, kidney, prostate, etc. ...

Cancer surveillance, early diagnosis, treatment, and prognosis assessment are issues of great concern to medical systems around the world. Ultrasound, as one of the most widely used imaging modalities, has been used in diagnosing and supervising tumors of thyroid, breast, liver, kidney, prostate, etc. High-resolution images and new imaging processing technologies make ultrasound become a reliable diagnostic and monitoring tool for cancer. It can provide not only morphological information but also stiffness and perfusion assessments. Nowadays, big data and artificial intelligence have been brought a new era to medical imaging. Big data analysis of ultrasound imaging, combined with data mining, advanced machine learning algorithms, and deep learning models, can help radiologists make better diagnoses and surveillance of cancer.

This research topic aims to provide an overview of the rapid development as well as major trends and challenges in the field of big data and artificial intelligence applied to ultrasound technology. We welcome original research, case report, opinion, mini-review and review articles that address, but are not limited to the following aspects:

1) Surveillance and detection
2) Diagnosis and differential diagnosis
3) Cancer grading and staging
4) Treatment guidance
5) Response to treatment
6) Prognosis prediction and prevention
7) Monitoring of disease status
8) Updated and improved specific algorithm for ultrasound

Keywords: ultrasound, cancer, big data, artificial intelligence


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