Parametric Comparison of Deep Learning Models for Musculoskeletal Abnormality Detection-Reference-Cited by-同舟云学术

Parametric Comparison of Deep Learning Models for Musculoskeletal Abnormality Detection

Published:2024 Issue: Volume: Page:145-155
ISSN:2367-3370
Container-title:Lecture Notes in Networks and Systems
language:en
Short-container-title:

Author:

Raghunath Niharika Gowri,Harikumar Nandana,Sree Paladi Navya,Sougandheeka Kothuru Eesha,Vanamala H. R.

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-99-7886-1_13

Reference7 articles.

1. Rajpurkar P, Irvin J, Bagul A, Ding D, Duan T et al (2018) MURA: Larde dataset for abnormality detection in musculuskeletal radiographs. In: 1st conference on medical imaging with deep learning (MIDL 2018)

2. Erwin RZ, Noviyanti DS, Utami GR, Harison AN, Agung PS (2019) Improved image quality retinal fundus with contrast limited adaptive histogram equalization and filter variation. In: 2019 international conference on informatics, multimedia, cyber and information system (ICIMCIS), pp 49–54. https://doi.org/10.1109/ICIMCIS48181.2019.8985198

3. Kavitha A, Kujani T, Kannan SG, Akila V (2022) Diagnosing musculoskeletal disorders from shoulder radiographs using deep learning models. In: 2022 international conference on electronic systems and intelligent computing (ICESIC), pp 85–90. https://doi.org/10.1109/ICESIC53714.2022.9783501

4. Mondol TC, Iqbal H, Hashem M (2019) Deep CNN-based ensemble CADx model for musculoskeletal abnormality detection from radiographs. In: 2019 5th international conference on advances in electrical engineering (ICAEE), pp 392–397. https://doi.org/10.1109/ICAEE48663.2019.8975455

5. Saif AFM, Shahnaz C, Zhu W, Ahmad MO Abnormality detection in musculoskeletal radiographs using capsule network. IEEE Access 7