Automatic Image Segmentation and Grading Diagnosis of Sacroiliitis Associated with AS Using a Deep Convolutional Neural Network on CT Images-Reference-Cited by-同舟云学术

Automatic Image Segmentation and Grading Diagnosis of Sacroiliitis Associated with AS Using a Deep Convolutional Neural Network on CT Images

Published:2023-06-02 Issue:5 Volume:36 Page:2025-2034
ISSN:1618-727X
Container-title:Journal of Digital Imaging
language:en
Short-container-title:J Digit Imaging

Author:

Zhang Ke,Luo Guibo,Li Wenjuan,Zhu Yunfei,Pan Jielin,Li Ximeng,Liu Chaoran,Liang Jianchao,Zhan Yingying,Zheng Jing,Li Shaolin,Cai Wenli,Hong Guobin^ORCID

Funder

the National Natural Science Foundation of China

the Science and Technology Project in the Social Development Field of Zhuhai City, Guangdong Province, China

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology

Link

https://link.springer.com/content/pdf/10.1007/s10278-023-00858-1.pdf

Reference31 articles.

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3. Christiansen AA, Hendricks O, Kuettel D, et al: Limited reliability of radiographic assessment of Sacroiliac joints in patients with suspected early spondyloarthritis. J Rheumatol 44:70-77, 2017

4. Bakker PA, van den Berg R, Lenczner G, et al: Can we use structural lesions seen on MRI of the sacroiliac joints reliably for the classification of patients according to the ASAS axial spondyloarthritis criteria? data from the DESIR cohort. Ann Rheum Dis 76:392-398, 2017

5. Diekhoff T, Hermann KG, Greese J, et al: Comparison of MRI with radiography for detecting structural lesions of the sacroiliac joint using CT as standard of reference: results from the SIMACT study. Ann Rheum Dis 76:1502-1508, 2017

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