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Your search keyword '"marker tracking"' showing total 3 results
Start Over Descriptor "marker tracking" Publisher elsevier
3 results on '"marker tracking"'

1. Quantitative evaluation of image recognition performance of fiducial markers in real-time tumor-tracking radiation therapy

Author

Ryo Morita, Hiroki Shirato, Shinichi Shimizu, Naoki Miyamoto, Kenichiro Maeda, Taeko Matsuura, Daisuke Abo, Seishin Takao, Kikuo Umegaki, and Norio Katoh

Subjects
Time Factors, Computer science, medicine.medical_treatment, Biophysics, General Physics and Astronomy, Image registration, Imaging phantom, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, 0302 clinical medicine, Fiducial Markers, Neoplasms, Image Processing, Computer-Assisted, medicine, Polymethyl Methacrylate, Radiology, Nuclear Medicine and imaging, Computer vision, Image-guided radiation therapy, Fiducial marker, Lung, Phantoms, Imaging, business.industry, Marker tracking, Image recognition, General Medicine, Real-time tumor-tracking radiation therapy, Radiation therapy, Liver, Fluoroscopy, 030220 oncology & carcinogenesis, Line (geometry), Tumor tracking, Artificial intelligence, business, Radiotherapy, Image-Guided
Abstract

Purpose: To quantitatively evaluate and compare the image recognition performance of multiple fiducial markers available in real-time tumor-tracking radiation therapy (RTRT). Methods: Clinically available markers including sphere shape, coil shape, cylinder shape, line shape, and ball shape (folded line shape) were evaluated in liver and lung models of RTRT. Maximum thickness of the polymethyl metacrylate (PMMA) phantom that could automatically recognize the marker was determined by template-pattern matching. Image registration accuracy of the fiducial marker was determined using liver RTRT model. Lung RTRT was mimicked with an anthropomorphic chest phantom and a one-dimensional motion stage in order to simulate marker motion in heterogeneous fluoroscopic images. The success or failure of marker tracking and image registration accuracy for the lung model were evaluated in the same manner as that for the liver model. Results: All fiducial markers except for line shape and coil shape of thinner diameter were recognized by the PMMA phantom, which is assumed to have the typical thickness of an abdomen, with two-dimensional image registration accuracy of < 2 pixels. Three-dimensional calculation error with the use of real-time stereoscopic fluoroscopy in RTRT was thought to be within 1 mm. In the evaluation using the lung model, the fiducial markers were recognized stably with sufficient accuracy for clinical application. The same was true for the evaluation using the liver model. Conclusions: The image recognition performance of fiducial markers was quantified and compared. The results presented here may be useful for the selection of fiducial markers.

Published
2019

2. Robust labeling of human motion markers in the presence of occlusions

Author

Ciencia de la computación e inteligencia artificial, Ingeniería de sistemas y automática, Konputazio zientziak eta adimen artifiziala, Sistemen ingeniaritza eta automatika, Jiménez Bascones, Juan Luis, Graña Romay, Manuel María, López Guede, José Manuel, Ciencia de la computación e inteligencia artificial, Ingeniería de sistemas y automática, Konputazio zientziak eta adimen artifiziala, Sistemen ingeniaritza eta automatika, Jiménez Bascones, Juan Luis, Graña Romay, Manuel María, and López Guede, José Manuel

Abstract

Human motion capture by optical sensors produces snapshots of the motion of a cloud of points that need to be labeled in order to carry out ensuing motion analysis for medical or other purposes. We generate the labeling of instantaneous captures of the cloud of points, discarding temporal correlations, in the presence of occlusions. Our approach proposes an ensemble of weak classifiers defined over geometrical features extracted from small subsets of the cloud of points. We apply an Adaboost strategy to select a minimal ensemble of weak classifiers achieving a target correct labeling detection accuracy. Furthermore, we use these features to generate the labeling of the points in the cloud even in the presence of occlusions.To deal with the occlusions of markers we search for ensembles of partial labeling solvers which can provide partial consistent labelings which cover the unoccluded markers. We test two greedy search approaches and a genetic algorithm in the search for the optimal ensemble of partial solvers We demonstrate the approach on a real dataset obtained from the measurement of gait motion of persons, with available ground truth labeling. Results are encouraging, achieving high accuracy label generation at a reduced computational cost. (C) 2019 The Author(s). Published by Elsevier B.V.

Published
2019

3. Hayabusa-final autonomous descent and landing based on target marker tracking

Author

Hideo Morita, Tetsuo Yoshimitsu, Tatsuaki Hashimoto, Jun'ichiro Kawaguchi, Takashi Kubota, Ken'ichi Shirakawa, and Masashi Uo

Subjects
Spacecraft, business.industry, Computer science, Marker tracking, Irregular shape, Process (computing), Aerospace Engineering, Touchdown, Terrain, Reaction wheel, Quasi real time, Aerospace engineering, Descent (aeronautics), business, Simulation
Abstract

Accepted: 2009-01-12, 資料番号: SA1000721000

Published
2009

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