Improved Classification of Benign and Malignant Breast Lesions Using Deep Feature Maximum Intensity Projection MRI in Breast Cancer Diagnosis Using Dynamic Contrast-enhanced MRI-Reference-Cited by-同舟云学术

Improved Classification of Benign and Malignant Breast Lesions Using Deep Feature Maximum Intensity Projection MRI in Breast Cancer Diagnosis Using Dynamic Contrast-enhanced MRI

Published:2021-05-01 Issue:3 Volume:3 Page:e200159
ISSN:2638-6100
Container-title:Radiology: Artificial Intelligence
language:en
Short-container-title:Radiology: Artificial Intelligence

Author:

Hu Qiyuan¹^ORCID,Whitney Heather M.¹^ORCID,Li Hui¹^ORCID,Ji Yu¹^ORCID,Liu Peifang¹^ORCID,Giger Maryellen L.¹^ORCID

Affiliation:

1. From the Department of Radiology, The University of Chicago, 5841 S Maryland Ave, MC2026, Chicago, IL 60637 (Q.H., H.M.W., H.L., M.L.G.); Department of Physics, Wheaton College, Wheaton, Ill (H.M.W.); and Department of Breast Imaging, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin Medical University, Tianjin, China (Y.J., P.L.).

Funder

National Institutes of Health Quantitative Imaging Network

National Cancer Institute

National Institutes of Health

Radiological Society of North America

American Association of Physicists in Medicine

Publisher

Radiological Society of North America (RSNA)

Subject

General Medicine

Link

http://pubs.rsna.org/doi/pdf/10.1148/ryai.2021200159

Reference37 articles.

1. Prognostic value of DCE-MRI in breast cancer patients undergoing neoadjuvant chemotherapy: a comparison with traditional survival indicators

2. Dynamic contrast-enhanced MRI in the diagnosis and management of breast cancer

3. MRI for breast cancer screening, diagnosis, and treatment

4. Mammography, Breast Ultrasound, and Magnetic Resonance Imaging for Surveillance of Women at High Familial Risk for Breast Cancer

5. Breast Image Analysis for Risk Assessment, Detection, Diagnosis, and Treatment of Cancer

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