Vector Quantized Convolutional Autoencoder Network for LDCT Image Reconstruction with Hybrid Loss

Medical image reconstruction is the process of creating high-quality and accurate images. During acquisition, these devices capture raw measurements or signals that represent the internal structures of the human body. However, these raw measurements are often noisy or incomplete. Low-dose CT is a me...

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Veröffentlicht in:	SN computer science Jg. 5; H. 1; S. 2
Hauptverfasser:	Ramanathan, Shalini, Ramasundaram, Mohan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Singapore Springer Nature Singapore 01.01.2024 Springer Nature B.V
Schlagworte:	Accuracy Algorithms Artificial intelligence Codes Computed tomography Computer Imaging Computer Science Computer Systems Organization and Communication Networks COVID-19 Data compression Data Structures and Information Theory Datasets Deep learning Dictionaries Image acquisition Image enhancement Image quality Image reconstruction Imaging techniques Information Systems and Communication Service Machine learning Medical imaging Neural networks Noise reduction Original Research Pattern Recognition and Graphics Quality assessment Radiation Radiation dosage Representations Research Trends in Computational Intelligence Software Engineering/Programming and Operating Systems Vision Deep learning Quantization Convolutional neural network medical image reconstruction Autoencoders Low-dose computed tomography
ISSN:	2661-8907, 2662-995X, 2661-8907
Online-Zugang:	Volltext
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