Progressively volumetrized deep generative models for data-efficient contextual learning of MR image recovery
Magnetic resonance imaging (MRI) offers the flexibility to image a given anatomic volume
under a multitude of tissue contrasts. Yet, scan time considerations put stringent limits on the …
under a multitude of tissue contrasts. Yet, scan time considerations put stringent limits on the …
Artificial intelligence (enhanced super-resolution generative adversarial network) for calcium deblooming in coronary computed tomography angiography: A feasibility …
Background: The presence of heavy calcification in the coronary artery always presents a
challenge for coronary computed tomography angiography (CCTA) in assessing the degree …
challenge for coronary computed tomography angiography (CCTA) in assessing the degree …
DuDoSS: Deep‐learning‐based dual‐domain sinogram synthesis from sparsely sampled projections of cardiac SPECT
Purpose Myocardial perfusion imaging (MPI) using single‐photon emission‐computed
tomography (SPECT) is widely applied for the diagnosis of cardiovascular diseases. In …
tomography (SPECT) is widely applied for the diagnosis of cardiovascular diseases. In …
TCGAN: a transformer-enhanced GAN for PET synthetic CT
J Li, Z Qu, Y Yang, F Zhang, M Li, S Hu - Biomedical Optics Express, 2022 - opg.optica.org
Multimodal medical images can be used in a multifaceted approach to resolve a wide range
of medical diagnostic problems. However, these images are generally difficult to obtain due …
of medical diagnostic problems. However, these images are generally difficult to obtain due …
Comparison between a dual-time-window protocol and other simplified protocols for dynamic total-body 18F-FDG PET imaging
Purpose Efforts have been made both to avoid invasive blood sampling and to shorten the
scan duration for dynamic positron emission tomography (PET) imaging. A total-body …
scan duration for dynamic positron emission tomography (PET) imaging. A total-body …
Artificial intelligence in radiation oncology: A review of its current status and potential application for the radiotherapy workforce
Objective Radiation oncology is a continually evolving speciality. With the development of
new imaging modalities and advanced imaging processing techniques, there is an …
new imaging modalities and advanced imaging processing techniques, there is an …
Artificial intelligence-aided method to detect uterine fibroids in ultrasound images: A retrospective study
T Huo, L Li, X Chen, Z Wang, X Zhang, S Liu… - Scientific Reports, 2023 - nature.com
We explored a new artificial intelligence-assisted method to assist junior ultrasonographers
in improving the diagnostic performance of uterine fibroids and further compared it with …
in improving the diagnostic performance of uterine fibroids and further compared it with …
Denoising diffusion-based MRI to CT image translation enables automated spinal segmentation
Background Automated segmentation of spinal magnetic resonance imaging (MRI) plays a
vital role both scientifically and clinically. However, accurately delineating posterior spine …
vital role both scientifically and clinically. However, accurately delineating posterior spine …
DermSynth3D: Synthesis of in-the-wild annotated dermatology images
In recent years, deep learning (DL) has shown great potential in the field of dermatological
image analysis. However, existing datasets in this domain have significant limitations …
image analysis. However, existing datasets in this domain have significant limitations …
[HTML][HTML] Combating COVID-19 using generative adversarial networks and artificial intelligence for medical images: scoping review
Background: Research on the diagnosis of COVID-19 using lung images is limited by the
scarcity of imaging data. Generative adversarial networks (GANs) are popular for synthesis …
scarcity of imaging data. Generative adversarial networks (GANs) are popular for synthesis …