A Deep Learning Harmonization of Multi-Vendor MRI for Robust Intervertebral Disc Segmentation-Reference-Cited by-同舟云学术

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A Deep Learning Harmonization of Multi-Vendor MRI for Robust Intervertebral Disc Segmentation

Published:2024 Issue: Volume:12 Page:19482-19499
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Kim Chaewoo¹^ORCID,Park Sang-Min²,Lee Sanghoon²^ORCID,Lee Deukhee¹^ORCID

Affiliation:

1. Center for Healthcare Robotics, Korea Institute of Science and Technology, Seoul, Republic of Korea

2. Spine Center and Department of Orthopaedic Surgery, Seoul National University College of Medicine, Seoul National University Bundang Hospital, Seongnam, Republic of Korea

Funder

KIST Institutional Programs

Korea Medical Device Development Fund

Korean Government

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6287639/10380310/10419023.pdf?arnumber=10419023

Reference58 articles.

1. DeepHarmony: A deep learning approach to contrast harmonization across scanner changes

2. MIL normalization —— prerequisites for accurate MRI radiomics analysis

3. Data harmonisation for information fusion in digital healthcare: A state-of-the-art systematic review, meta-analysis and future research directions

4. Normalization of breast MRIs using cycle-consistent generative adversarial networks

5. Statistical normalization techniques for magnetic resonance imaging

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1. Automated Detection of Spinal Lesions From CT Scans via Deep Transfer Learning;IEEE Access;2024

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