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Four-Dimensional Computed Tomography

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Automatic segmentation and labelling of wrist bones in four-dimensional computed tomography datasets via deep learning.

The Journal of hand surgery, European volume
This study developed a deep learning model for fully automatic segmentation and labelling of wrist bones from four-dimensional computed tomography (4DCT) scans. This is a crucial step towards implementing 4DCT for diagnosing wrist ligament lesions, r...

Deep learning based automatic internal gross target volume delineation from 4D-CT of hepatocellular carcinoma patients.

Journal of applied clinical medical physics
BACKGROUND: The location and morphology of the liver are significantly affected by respiratory motion. Therefore, delineating the gross target volume (GTV) based on 4D medical images is more accurate than regular 3D-CT with contrast. However, the 4D ...

Deep learning-based conditional inpainting for restoration of artifact-affected 4D CT images.

Medical physics
BACKGROUND: 4D CT imaging is an essential component of radiotherapy of thoracic and abdominal tumors. 4D CT images are, however, often affected by artifacts that compromise treatment planning quality and image information reliability.

CvTMorph: Improving Local Feature Extraction in Medical Image Registration for Respiratory Motion Modeling with Convolutional Vision Transformer.

Current medical imaging
BACKGROUND: Accurately modeling respiratory motion in medical images is crucial for various applications, including radiation therapy planning. However, existing registration methods often struggle to extract local features effectively, limiting thei...

A deep learning model for translating CT to ventilation imaging: analysis of accuracy and impact on functional avoidance radiotherapy planning.

Japanese journal of radiology
PURPOSE: Radiotherapy planning incorporating functional lung images has the potential to reduce pulmonary toxicity. Free-breathing 4DCT-derived ventilation image (CTVI) may help quantify lung function. This study introduces a novel deep-learning mode...

Benchmarking machine learning-based real-time respiratory signal predictors in 4D SBRT.

Medical physics
BACKGROUND: Stereotactic body radiotherapy of thoracic and abdominal tumors has to account for respiratory intrafractional tumor motion. Commonly, an external breathing signal is continuously acquired that serves as a surrogate of the tumor motion an...

Deep learning-based target decomposition for markerless lung tumor tracking in radiotherapy.

Medical physics
BACKGROUND: In radiotherapy, real-time tumor tracking can verify tumor position during beam delivery, guide the radiation beam to target the tumor, and reduce the chance of a geometric miss. Markerless kV x-ray image-based tumor tracking is challengi...

A back propagation neural network based respiratory motion modelling method.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: This study presents the development of a backpropagation neural network-based respiratory motion modelling method (BP-RMM) for precisely tracking arbitrary points within lung tissue throughout free respiration, encompassing deep inspirati...

DPI-MoCo: Deep Prior Image Constrained Motion Compensation Reconstruction for 4D CBCT.

IEEE transactions on medical imaging
4D cone-beam computed tomography (CBCT) plays a critical role in adaptive radiation therapy for lung cancer. However, extremely sparse sampling projection data will cause severe streak artifacts in 4D CBCT images. Existing deep learning (DL) methods ...