Automated Recognition of healthy Anterior Cruciate Ligament in Sagittal MR images using Lightweight Deep Learning-Reference-Cited by-同舟云学术

Automated Recognition of healthy Anterior Cruciate Ligament in Sagittal MR images using Lightweight Deep Learning

Published:2022-07-18 Issue: Volume: Page:
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Container-title:2022 13th International Conference on Information, Intelligence, Systems & Applications (IISA)
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Author:

Siouras Athanasios¹,Moustakidis Serafeim²,Giannakidis Archontis³,Chalatsis Georgios⁴,Malizos Konstantinos N.⁵,Hantes Michael⁶,Tasoulis Sotiris¹,Tsaopoulos Dimitrios⁷

Affiliation:

1. University of Thessaly,School of Science,Department of Computer Science and Biomedical Informatics,Lamia,Greece,35131

2. AIDEAS OÜ,Tallinn,Estonia,10117

3. Nottingham Trent University,School of Science and Technology,Nottingham,UK,NG11 8NS

4. University of Thessaly,Faculty of Medicine,Department of Orthopedic Surgery,Larissa,Greece,41500

5. University of Thessaly,Department of Orthopedics,Larissa,Greece

6. University of Thessaly,Department of Orthopedic Surgery, faculty of Medicine,Greece

7. Centre for Research and Technology Hellas,Volos,Greece,38333

Funder

European Regional Development Fund

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9903994/9904331/09904387.pdf?arnumber=9904387

Reference25 articles.

1. Magnetic Resonance Imaging

2. A Critical Review for Developing Accurate and Dynamic Predictive Models Using Machine Learning Methods in Medicine and Health Care

3. MRI of the knee: how do field strength and radiologist’s experience influence diagnostic accuracy and interobserver correlation in assessing chondral and meniscal lesions and the integrity of the anterior cruciate ligament?

4. Pitfalls and Pearls in MRI of the Knee

5. A survey on deep learning in medical image analysis

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