PURPOSE: To develop a geometry-informed deep learning framework for volumetric MRI with sub-second acquisition time in support of 3D motion tracking, which is highly desirable for improved radiotherapy precision but hindered by the long image acquisi...
IEEE journal of biomedical and health informatics
Jul 1, 2022
We systematically evaluate a Deep Learning model in a 3D medical image segmentation task. With our model, we address the flaws of manual segmentation: high inter-rater contouring variability and time consumption of the contouring process. The main ex...
With the increase of the adult orthodontic population, there is a need for an accurate and evidence-based prediction of the posttreatment face in 3 dimensions (3D). The objectives of this study are 1) to develop a 3D postorthodontic face prediction m...
Accurate segmentation of lesions in medical images is of great significance for clinical diagnosis and evaluation. The low contrast between lesions and surrounding tissues increases the difficulty of automatic segmentation, while the efficiency of ma...
The purpose of this study is to evaluate whether thin-slice high-resolution 2D fat-suppressed proton density-weighted image of the knee joint using denoising approach with deep learning-based reconstruction (dDLR) with MPR is more useful than 3D FS-P...
BACKGROUND: Remote surgery social implementation necessitates achieving low latency and highly reliable video/operation signal transmission over economical commercial networks. However, with commercial lines, communication bandwidth often fluctuates ...
Computational and mathematical methods in medicine
Jun 13, 2022
This study was focused on the positioning of the intracranial aneurysm in the magnetic resonance imaging (MRI) images using the deep learning-based U-Net model, to realize the computer-aided diagnosis of the intracranial aneurysm. First, a network wa...
OBJECTIVES: To evaluate the targeting accuracy of stereotactic punctures based on a hybrid robotic device in combination with optical tracking-a phantom study.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Jun 9, 2022
Recently, deep convolutional neural networks have achieved great success for medical image segmentation. However, unlike segmentation of natural images, most medical images such as MRI and CT are volumetric data. In order to make full use of volumetr...
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