Generative Machine Learning Models in Medical Image Computing
portes grátis
Generative Machine Learning Models in Medical Image Computing
Slabaugh, Greg; Chen, Chen; Li, Zeju; Zhang, Le
Springer International Publishing AG
04/2025
384
Dura
9783031809644
Pré-lançamento - envio 15 a 20 dias após a sua edição
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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.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Generative Models;Medical Imaging;Machine Learning;Generative Adversarial Networks (GANs);Variational Autoencoders (VAEs);Diffusion Models;Image Synthesis;Image Reconstruction;Data Augmentation;MRI Analysis;CT Imaging;Ultrasound Imaging;Predictive Diagnostics;Model Interpretability;Clinical Validation;Biomedical Image Analysis;Artificial Intelligence in Healthcare;Ethical Considerations in AI;Computational Healthcare;Image Quality Enhancement
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.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Generative Models;Medical Imaging;Machine Learning;Generative Adversarial Networks (GANs);Variational Autoencoders (VAEs);Diffusion Models;Image Synthesis;Image Reconstruction;Data Augmentation;MRI Analysis;CT Imaging;Ultrasound Imaging;Predictive Diagnostics;Model Interpretability;Clinical Validation;Biomedical Image Analysis;Artificial Intelligence in Healthcare;Ethical Considerations in AI;Computational Healthcare;Image Quality Enhancement
