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Four-Dimensional Computed Tomography

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Comparison between target margins derived from 4DCT scans and real-time tumor motion tracking: insights from lung tumor patients treated with robotic radiosurgery.

Medical physics
PURPOSE: A unique capability of the CyberKnife system is dynamic target tracking. However, not all patients are eligible for this approach. Rather, their tumors are tracked statically using the vertebral column for alignment. When using static tracki...

A method for volumetric imaging in radiotherapy using single x-ray projection.

Medical physics
PURPOSE: It is an intriguing problem to generate an instantaneous volumetric image based on the corresponding x-ray projection. The purpose of this study is to develop a new method to achieve this goal via a sparse learning approach.

Multiple Kernel Point Set Registration.

IEEE transactions on medical imaging
The finite Gaussian mixture model with kernel correlation is a flexible tool that has recently received attention for point set registration. While there are many algorithms for point set registration presented in the literature, an important issue a...

Dosimetric and delivery efficiency investigation for treating hepatic lesions with a MLC-equipped robotic radiosurgery-radiotherapy combined system.

Medical physics
PURPOSE: The CyberKnife M6 (CK-M6) Series introduced a multileaf collimator (MLC) for extending its capability from stereotactic radiosurgery/stereotactic radiotherapy (SBRT) to conventionally fractionated radiotherapy. This work is to investigate th...

A method to combine target volume data from 3D and 4D planned thoracic radiotherapy patient cohorts for machine learning applications.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: The gross tumour volume (GTV) is predictive of clinical outcome and consequently features in many machine-learned models. 4D-planning, however, has prompted substitution of the GTV with the internal gross target volume (iGTV)....

Principal component reconstruction (PCR) for cine CBCT with motion learning from 2D fluoroscopy.

Medical physics
PURPOSE: This work aims to generate cine CT images (i.e., 4D images with high-temporal resolution) based on a novel principal component reconstruction (PCR) technique with motion learning from 2D fluoroscopic training images.

Functional-guided radiotherapy using knowledge-based planning.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: There are two significant challenges when implementing functional-guided radiotherapy using 4DCT-ventilation imaging: (1) lack of knowledge of realistic patient specific dosimetric goals for functional lung and (2) ensuring co...

Real-time tumor tracking using fluoroscopic imaging with deep neural network analysis.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: To improve respiratory gating accuracy and treatment throughput, we developed a fluoroscopic markerless tumor tracking algorithm based on a deep neural network (DNN).

Technical Note: Deriving ventilation imaging from 4DCT by deep convolutional neural network.

Medical physics
PURPOSE: Ventilation images can be derived from four-dimensional computed tomography (4DCT) by analyzing the change in HU values and deformable vector fields between different respiration phases of computed tomography (CT). As deformable image regist...

Using a deep neural network for four-dimensional CT artifact reduction in image-guided radiotherapy.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
INTRODUCTION: Breathing artifact may affect the quality of four-dimensional computed tomography (4DCT) images. We developed a deep neural network (DNN)-based artifact reduction method.