Advances in medical image analysis with vision transformers: a comprehensive review
The remarkable performance of the Transformer architecture in natural language processing
has recently also triggered broad interest in Computer Vision. Among other merits …
has recently also triggered broad interest in Computer Vision. Among other merits …
Transmorph: Transformer for unsupervised medical image registration
In the last decade, convolutional neural networks (ConvNets) have been a major focus of
research in medical image analysis. However, the performances of ConvNets may be limited …
research in medical image analysis. However, the performances of ConvNets may be limited …
Vit-v-net: Vision transformer for unsupervised volumetric medical image registration
In the last decade, convolutional neural networks (ConvNets) have dominated and achieved
state-of-the-art performances in a variety of medical imaging applications. However, the …
state-of-the-art performances in a variety of medical imaging applications. However, the …
An update on computational anthropomorphic anatomical models
The prevalent availability of high-performance computing coupled with validated
computerized simulation platforms as open-source packages have motivated progress in the …
computerized simulation platforms as open-source packages have motivated progress in the …
A survey on deep learning in medical image registration: New technologies, uncertainty, evaluation metrics, and beyond
Over the past decade, deep learning technologies have greatly advanced the field of
medical image registration. The initial developments, such as ResNet-based and U-Net …
medical image registration. The initial developments, such as ResNet-based and U-Net …
The stochastic digital human is now enrolling for in silico imaging trials—methods and tools for generating digital cohorts
Randomized clinical trials, while often viewed as the highest evidentiary bar by which to
judge the quality of a medical intervention, are far from perfect. In silico imaging trials are …
judge the quality of a medical intervention, are far from perfect. In silico imaging trials are …
Learning fuzzy clustering for SPECT/CT segmentation via convolutional neural networks
Purpose Quantitative bone single‐photon emission computed tomography (QBSPECT) has
the potential to provide a better quantitative assessment of bone metastasis than planar …
the potential to provide a better quantitative assessment of bone metastasis than planar …
[HTML][HTML] PLOSL: Population learning followed by one shot learning pulmonary image registration using tissue volume preserving and vesselness constraints
D Wang, Y Pan, OC Durumeric, JM Reinhardt… - Medical image …, 2022 - Elsevier
This paper presents the Population Learning followed by One Shot Learning (PLOSL)
pulmonary image registration method. PLOSL is a fast unsupervised learning-based …
pulmonary image registration method. PLOSL is a fast unsupervised learning-based …
4D‐CT deformable image registration using unsupervised recursive cascaded full‐resolution residual networks
L Xu, P Jiang, T Tsui, J Liu, X Zhang… - Bioengineering & …, 2023 - Wiley Online Library
A novel recursive cascaded full‐resolution residual network (RCFRR‐Net) for abdominal
four‐dimensional computed tomography (4D‐CT) image registration was proposed. The …
four‐dimensional computed tomography (4D‐CT) image registration was proposed. The …
Spatial transform depthwise over-parameterized convolution recurrent neural network for license plate recognition in complex environment
J Deng, H Wei, Z Lai, G Gu… - … of Computing and …, 2023 - asmedigitalcollection.asme.org
Automatic license plate recognition (ALPR) system has been widely used in intelligent
transportation and other fields. However, in complex environments such as vehicle sound …
transportation and other fields. However, in complex environments such as vehicle sound …