Generative Machine Learning Models in Medical Image Computing

Part I Segmentation.- Synthesis of annotated data for medical image segmentation.- Diffusion Models For Histopathological Image Generation.- Generative AI Techniques for Ultrasound Image Reconstruction.- Part II Detection and Classification.- Vision Language Pre training from Synthetic Data.- Diffusion models for inverse problems in medical imaging.- Virtual Elastography Ultrasound via Generative Adversarial Network and its Application to Breast Cancer Diagnosis.- Generative Adversarial Networks for Brain MR Image Synthesis and Its Clinical Validation on Multiple Sclerosis.- Histopathological Synthetic Augmentation with Generative Models.- Part III Image Super resolution and Reconstruction.- Enhancing PET with Image Generation Techniques Generating Standard dose PET from Low dose PET.- EyesGAN Synthesize human face from human eyes.- Deep Generative Models for 3D Medical Image Synthesis.- Part IV Various Applications.- Cross Modal Attention Fusion based Generative Adversarial Network for text to image synthesis.- CHeart A Conditional Spatio Temporal Generative Model for Cardiac Anatomy.- Generative Models for Synthesizing Anatomical Plausible 3D Medical Images.- Diffusion Probabilistic Models for Image Formation in MRI.- Embedding 3D CT Prior into X ray Imaging Using Generative Adversarial Networks.

• Erscheinungsdatum: 12.03.2025
• Autor/Autorin: Le Zhang
• Reihe: Mathematics and Statistics (R0)
• Format: E-Book
• Dateiformat: PDF
• Kopierschutz: Wasserzeichen
• Dateigröße: 34.1 MB
• Verlag: SPRINGER
• Sprache: Englisch
• Umfang: 381 Seiten
• ISBN: 9783031809651
• Lieferung: Sofort per Download
• Hinweis: Sofort per Download lieferbar. Kein physischer Versand.
• Kompatibilität: Lesbar auf Geräten und Apps mit PDF-Unterstützung.