Computational Cytology
Springer Verlag, Singapore
978-981-95-3271-1 (ISBN)
The book serves as a practical guide for pathologists, researchers, professionals in bioinformatics, and computer scientists, helping them understand how to integrate digital and molecular data into cytology for research, diagnosis, cancer screening, personalized management, and drug discovery.
Dr. Pranab Dey is currently working as a professor of Oncopathology Homi Bhabha Cancer Hospital and Research Centre (Tata Memorial Center), New Chandigarh, India. Previously, he was a professor of cytology at the Post Graduate Institute of Medical Education and Research, Chandigarh, India. Dr. Dey’s areas of research interest include fine needle aspiration cytology, exfoliative cytology, cervical smears, and gynecologic histopathology. He is skilled in artificial neural networks and flow cytometry. Dr. Dey has published over 710 papers in peer-reviewed national and international journals and 13 books.
Section I: Computational Integration in Cytology.- Chapter 1. Introduction to Computational Cytology.- Chapter 2. Digital Cytology: The Cornerstone of Computational Cytology.- Chapter 3. Digital Workflow in Cytology.- Section II: Major Components of Computational Cytology.- Chapter 4. Data acquisition and preparation in Computational Cytology.- Chapter 5. Overview of Artificial neural network.- Section III: Computational Techniques and Tools.- Chapter 6. Image Processing for Cytology.- Chapter 7. Deep Learning in Computational Cytology.- Chapter 8. Natural Language Processing in Cytology Reports.- Section IV: Applications of Computational Cytology.- Chapter 9. Diagnosis of Cancer.- Chapter 10. Molecular Data Interpretation by artificial intelligence.- Chapter 11. Automation in Cytology Laboratory.- Chapter 12. Personalized Medicine and Computational Cytology.- Section V: Advanced Topics and Emerging Trends.- Chapter 13. Multi-modal Data Fusion by combining imaging, clinical and molecular data.- Chapter 14. Data storage, security and Ethical issues in Computational Cytology.- Chapter 15. Future Directions, and challenges in Computational Cytology.- Section VI: Hands-On and Practical Applications.- Chapter 16. A practical guide to build the Computational Model.- Chapter 17. Software and Tools for Computational Cytology.- Chapter 18. Data management, data Sharing in Computational Cytology.- Section VII: Challenges and Future Directions.- Chapter 20. Current Limitations and solution in Computational Cytology.
| Erscheinungsdatum | 18.11.2025 |
|---|---|
| Zusatzinfo | 116 Illustrations, color; 1 Illustrations, black and white |
| Verlagsort | Singapore |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Themenwelt | Mathematik / Informatik ► Informatik ► Theorie / Studium |
| Medizin / Pharmazie ► Medizinische Fachgebiete | |
| Studium ► 2. Studienabschnitt (Klinik) ► Pathologie | |
| Naturwissenschaften ► Biologie | |
| Schlagworte | Automation in the laboratory and liquid-based cytology • Computational Models • Deep learning for computational cytology • Digital cytopathology • Digital Pathology • Generative AI in computational biology and bioinformatics • Natural language processing in pathology |
| ISBN-10 | 981-95-3271-X / 981953271X |
| ISBN-13 | 978-981-95-3271-1 / 9789819532711 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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