The international journal of medical robotics + computer assisted surgery : MRCAS
Jun 1, 2024
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...
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...
CT is one of the most widely used modalities for musculoskeletal imaging. Recent advancements in the field include the introduction of four-dimensional CT, which captures a CT image during motion; cone-beam CT, which uses flat-panel detectors to capt...
Technology in cancer research & treatment
Jan 1, 2022
This study aims to develop a deep learning (DL)-based (Mask R-CNN) method to predict the internal target volume (ITV) in cone beam computed tomography (CBCT) images for lung stereotactic body radiotherapy (SBRT) patients and to evaluate the predictio...
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...
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.
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...
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