دورية أكاديمية
A Systematic Review of Low-Rank and Local Low-Rank Matrix Approximation in Big Data Medical Imaging ...
| العنوان: | A Systematic Review of Low-Rank and Local Low-Rank Matrix Approximation in Big Data Medical Imaging ... |
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| المؤلفون: | Hamlomo, Sisipho, Atemkeng, Marcellin, Brima, Yusuf, Nunhokee, Chuneeta, Baxter, Jeremy |
| بيانات النشر: | arXiv |
| سنة النشر: | 2024 |
| المجموعة: | DataCite Metadata Store (German National Library of Science and Technology) |
| مصطلحات موضوعية: | Image and Video Processing eess.IV, Computer Vision and Pattern Recognition cs.CV, Machine Learning cs.LG, FOS Electrical engineering, electronic engineering, information engineering, FOS Computer and information sciences |
| الوصف: | The large volume and complexity of medical imaging datasets are bottlenecks for storage, transmission, and processing. To tackle these challenges, the application of low-rank matrix approximation (LRMA) and its derivative, local LRMA (LLRMA) has demonstrated potential. A detailed analysis of the literature identifies LRMA and LLRMA methods applied to various imaging modalities, and the challenges and limitations associated with existing LRMA and LLRMA methods are addressed. We note a significant shift towards a preference for LLRMA in the medical imaging field since 2015, demonstrating its potential and effectiveness in capturing complex structures in medical data compared to LRMA. Acknowledging the limitations of shallow similarity methods used with LLRMA, we suggest advanced semantic image segmentation for similarity measure, explaining in detail how it can be used to measure similar patches and its feasibility. We note that LRMA and LLRMA are mainly applied to unstructured medical data, and we propose ... |
| نوع الوثيقة: | article in journal/newspaper report |
| اللغة: | unknown |
| DOI: | 10.48550/arxiv.2402.14045 |
| الإتاحة: | https://doi.org/10.48550/arxiv.2402.14045Test https://arxiv.org/abs/2402.14045Test |
| حقوق: | Creative Commons Attribution 4.0 International ; https://creativecommons.org/licenses/by/4.0/legalcodeTest ; cc-by-4.0 |
| رقم الانضمام: | edsbas.10585A8A |
| قاعدة البيانات: | BASE |
| DOI: | 10.48550/arxiv.2402.14045 |
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