A review of medical image data augmentation techniques for deep learning applications

P Chlap, H Min, N Vandenberg… - Journal of Medical …, 2021 - Wiley Online Library
Research in artificial intelligence for radiology and radiotherapy has recently become
increasingly reliant on the use of deep learning‐based algorithms. While the performance of …

Deep learning-based image reconstruction and post-processing methods in positron emission tomography for low-dose imaging and resolution enhancement

CD Pain, GF Egan, Z Chen - European Journal of Nuclear Medicine and …, 2022 - Springer
Image processing plays a crucial role in maximising diagnostic quality of positron emission
tomography (PET) images. Recently, deep learning methods developed across many fields …

Adaptive rectification based adversarial network with spectrum constraint for high-quality PET image synthesis

Y Luo, L Zhou, B Zhan, Y Fei, J Zhou, Y Wang… - Medical Image …, 2022 - Elsevier
Positron emission tomography (PET) is a typical nuclear imaging technique, which can
provide crucial functional information for early brain disease diagnosis. Generally, clinically …

PET image denoising based on denoising diffusion probabilistic model

K Gong, K Johnson, G El Fakhri, Q Li, T Pan - European Journal of …, 2024 - Springer
Purpose Due to various physical degradation factors and limited counts received, PET
image quality needs further improvements. The denoising diffusion probabilistic model …

Artificial intelligence-based image enhancement in pet imaging: Noise reduction and resolution enhancement

J Liu, M Malekzadeh, N Mirian, TA Song, C Liu… - PET clinics, 2021 - pet.theclinics.com
PET is a noninvasive molecular imaging modality that is increasingly popular in oncology,
neurology, cardiology, and other fields. 1–3 Accurate quantitation of PET radiotracer uptake …

Low-count whole-body PET/MRI restoration: an evaluation of dose reduction spectrum and five state-of-the-art artificial intelligence models

YR Wang, P Wang, LC Adams, ND Sheybani… - European journal of …, 2023 - Springer
Purpose To provide a holistic and complete comparison of the five most advanced AI models
in the augmentation of low-dose 18F-FDG PET data over the entire dose reduction …

Spach Transformer: Spatial and channel-wise transformer based on local and global self-attentions for PET image denoising

SI Jang, T Pan, Y Li, P Heidari, J Chen… - IEEE transactions on …, 2023 - ieeexplore.ieee.org
Position emission tomography (PET) is widely used in clinics and research due to its
quantitative merits and high sensitivity, but suffers from low signal-to-noise ratio (SNR) …

Anatomical-guided attention enhances unsupervised PET image denoising performance

Y Onishi, F Hashimoto, K Ote, H Ohba, R Ota… - Medical image …, 2021 - Elsevier
Although supervised convolutional neural networks (CNNs) often outperform conventional
alternatives for denoising positron emission tomography (PET) images, they require many …

[HTML][HTML] Applications of artificial intelligence in nuclear medicine image generation

Z Cheng, J Wen, G Huang, J Yan - Quantitative Imaging in …, 2021 - ncbi.nlm.nih.gov
Recently, the application of artificial intelligence (AI) in medical imaging (including nuclear
medicine imaging) has rapidly developed. Most AI applications in nuclear medicine imaging …

Deep learning-based PET image denoising and reconstruction: a review

F Hashimoto, Y Onishi, K Ote, H Tashima… - … physics and technology, 2024 - Springer
This review focuses on positron emission tomography (PET) imaging algorithms and traces
the evolution of PET image reconstruction methods. First, we provide an overview of …