Téléchargez le livre : Generative Machine Learning Models in Medical Image Computing

Generative Machine Learning Models in Medical Image Computing

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Springer


Paru le : 2025-03-12

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Description

Generative Machine Learning Models in Medical Image Computing" provides a comprehensive exploration of generative modeling techniques tailored to the unique demands of medical imaging. This book presents an in-depth overview of cutting-edge generative models such as GANs, VAEs, and diffusion models, examining how they enable groundbreaking applications in medical image synthesis, reconstruction, and enhancement. Covering diverse imaging modalities like MRI, CT, and ultrasound, it illustrates how these models facilitate improvements in image quality, support data augmentation for scarce datasets, and create new avenues for predictive diagnostics.
Beyond technical details, the book addresses critical challenges in deploying generative models for healthcare, including ethical concerns, interpretability, and clinical validation. With a strong focus on real-world applications, it includes case studies and implementation guidelines, guiding readers in translating theory into practice. By addressing model robustness, reproducibility, and clinical utility, this book is an essential resource for researchers, clinicians, and data scientists seeking to leverage generative models to enhance biomedical imaging and deliver impactful healthcare solutions. Combining technical rigor with practical insights, it offers a roadmap for integrating advanced generative approaches in the field of medical image computing.
Pages
382 pages
Collection
n.c
Parution
2025-03-12
Marque
Springer
EAN papier
9783031809644
EAN PDF
9783031809651
Informations sur l'ebook
Nombre pages copiables
3
Nombre pages imprimables
38
Taille du fichier
34898 Ko
Prix
147,69 €
EAN EPUB
9783031809651
Informations sur l'ebook
Nombre pages copiables
3
Nombre pages imprimables
38
Taille du fichier
68424 Ko
Prix
147,69 €

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