Biomedical Image Analysis Special Applications in MRIs and CT scans /
This book provides an in-depth study of biomedical image analysis. It reviews and summarizes previous research work in biomedical image analysis and also provides a brief introduction to other computation techniques, such as fuzzy sets, neutrosophic sets, clustering algorithm and fast forward quantu...
Furkejuvvon:
| Váldodahkki: | |
|---|---|
| Searvvušdahkki: | |
| Materiálatiipa: | Elektrovnnalaš E-girji |
| Giella: | eaŋgalasgiella |
| Almmustuhtton: |
Singapore :
Springer Nature Singapore : Imprint: Springer,
2024.
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| Preanttus: | 1st ed. 2024. |
| Ráidu: | Brain Informatics and Health,
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| Fáttát: | |
| Liŋkkat: | https://doi.org/10.1007/978-981-99-9939-2 |
| Fáddágilkorat: |
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| 100 | 1 | |a Singh, Pritpal. |e author. |0 (orcid)0000-0002-0889-6011 |1 https://orcid.org/0000-0002-0889-6011 |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 245 | 1 | 0 | |a Biomedical Image Analysis |h [electronic resource] : |b Special Applications in MRIs and CT scans / |c by Pritpal Singh. |
| 250 | |a 1st ed. 2024. | ||
| 264 | 1 | |a Singapore : |b Springer Nature Singapore : |b Imprint: Springer, |c 2024. | |
| 300 | |a 1 online resource (XI, 166 p. 1 illus.). | ||
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| 341 | 0 | |b Table of contents navigation |2 onix | |
| 341 | 0 | |b Single logical reading order |2 onix | |
| 341 | 0 | |b Short alternative textual descriptions |2 onix | |
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| 490 | 1 | |a Brain Informatics and Health, |x 2367-1750 | |
| 505 | 0 | |a Chapter 1 Parkinson's disease MRIs analysis using fuzzy clustering approach -- Chapter 2 Parkinson's disease MRIs analysis using neutrosophic segmentation approach -- Chapter 3 Parkinson's disease MRIs analysis using neutrosophic clustering approach -- Chapter 4 Brain tumor segmentation using type-2 neutrosophic thresholding approach -- Chapter 5 COVID-19 scan image segmentation using quantum-clustering approach -- Chapter 6 Empirical Analyses. | |
| 520 | |a This book provides an in-depth study of biomedical image analysis. It reviews and summarizes previous research work in biomedical image analysis and also provides a brief introduction to other computation techniques, such as fuzzy sets, neutrosophic sets, clustering algorithm and fast forward quantum optimization algorithm, focusing on how these techniques can be integrated into different phases of the biomedical image analysis. In particular, this book describes novel methods resulting from the fuzzy sets, neutrosophic sets, clustering algorithm and fast forward quantum optimization algorithm. It also demonstrates how a new quantum-clustering based model can be successfully applied in the context of clustering the COVID-19 CT scans. Thanks to its easy-to-read style and the clear explanations of the models, the book can be used as a concise yet comprehensive reference guide to biomedical image analysis, and will be valuable not only for graduate students, but also for researchers and professionals working for academic, business and government institutes and medical colleges. | ||
| 532 | 8 | |a Accessibility summary: This PDF does not fully comply with PDF/UA standards, but does feature limited screen reader support, described non-text content (images, graphs), bookmarks for easy navigation and searchable, selectable text. Users of assistive technologies may experience difficulty navigating or interpreting content in this document. We recognize the importance of accessibility, and we welcome queries about accessibility for any of our products. If you have a question or an access need, please get in touch with us at accessibilitysupport@springernature.com. | |
| 532 | 8 | |a No reading system accessibility options actively disabled | |
| 532 | 8 | |a Publisher contact for further accessibility information: accessibilitysupport@springernature.com | |
| 588 | |a Print version record. | ||
| 650 | 0 | |a Image processing. | |
| 650 | 0 | |a Artificial intelligence. | |
| 650 | 0 | |a Machine learning. | |
| 650 | 0 | |a Artificial intelligence |x Data processing. | |
| 650 | 1 | 4 | |a Image Processing. |
| 650 | 2 | 4 | |a Artificial Intelligence. |
| 650 | 2 | 4 | |a Machine Learning. |
| 650 | 2 | 4 | |a Data Science. |
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| 830 | 0 | |a Brain Informatics and Health, |x 2367-1750 | |
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