Analyzing Tumor Lesions in PET/CT Images Using Deep Learning Methods and Physiological Models
Seiten
- Keine Verlagsinformationen verfügbar
- Artikel merken
The detection of pathological lesions plays an important role in the diagnostic and therapeutic assessment of various oncological disorders. Medical imaging provides a visualized way to keep track of tumor status. On the other hand, tumor hypoxia, which characterizes a depletion of oxygen (O2) supply, is a major factor that impedes radiotherapy.
Based on the above concerns the dissertation consists of two parts, which explores to automatically detect tumor using deep learning methods, and also investigates the characteristics of chronic and acute hypoxia.
Based on the above concerns the dissertation consists of two parts, which explores to automatically detect tumor using deep learning methods, and also investigates the characteristics of chronic and acute hypoxia.
| Erscheinungsdatum | 17.02.2019 |
|---|---|
| Reihe/Serie | Informatik |
| Verlagsort | München |
| Sprache | englisch |
| Maße | 148 x 210 mm |
| Gewicht | 211 g |
| Themenwelt | Mathematik / Informatik ► Informatik ► Theorie / Studium |
| Schlagworte | Deep learning • Physiological model • Tumor Detection |
| ISBN-10 | 3-8439-3929-2 / 3843939292 |
| ISBN-13 | 978-3-8439-3929-4 / 9783843939294 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
| Haben Sie eine Frage zum Produkt? |
Mehr entdecken
aus dem Bereich
aus dem Bereich
was jeder über Informatik wissen sollte
Buch | Softcover (2024)
Springer Vieweg (Verlag)
CHF 53,15
Grundlagen – Anwendungen – Perspektiven
Buch | Softcover (2022)
Springer Vieweg (Verlag)
CHF 53,15
Teil 2 der gestreckten Abschlussprüfung Fachinformatiker/-in …
Buch | Softcover (2025)
Europa-Lehrmittel (Verlag)
CHF 37,90
