Ultrasound in Oncology: Application of Big Data and Artificial Intelligence

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Editorial

22 December 2021

Editorial: Ultrasound in Oncology: Application of Big Data and Artificial Intelligence

Yu-Ting Shen

,

Wen-Wen Yue

and

Hui-Xiong Xu

2,730 views

2 citations

Editors

4

Department of Medical Ultrasound, Shanghai Tenth People's Hospital, Tongji University

The First Affiliated Hospital of Sun Yat-sen University

Richard Gary Barr

Northeast Ohio Medical University

Katsutoshi Sugimoto

Tokyo Medical University

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About

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

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

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Editors

Department of Medical Ultrasound, Shanghai Tenth People's Hospital, Tongji University

The First Affiliated Hospital of Sun Yat-sen University

Richard Gary Barr

Northeast Ohio Medical University

Katsutoshi Sugimoto

Tokyo Medical University

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64,118 Total views

41,319 Article views

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Frontiers in Oncology

Cancer Imaging and Image-directed Interventions

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