scholarly journals Sparse sampling in helical cone-beam CT perfect reconstruction algorithms

2016 ◽  
Vol 24 (3) ◽  
pp. 389-405 ◽  
Author(s):  
Tamir Bendory ◽  
Arie Feuer
Keyword(s):  
Cone Beam Ct ◽  
Sparse Sampling ◽  
Perfect Reconstruction ◽  
Cone Beam ◽  
Reconstruction Algorithms

Recent Advances in Cone-beam CT in Oral Medicine

2020 ◽  
Vol 16 (5) ◽  
pp. 553-564
Author(s):  
Delphine Maret ◽  
Jean-Noel Vergnes ◽  
Ove A. Peters ◽  
Christine Peters ◽  
Karim Nasr ◽  
...  
Keyword(s):  
Oral Surgery ◽  
Cone Beam Ct ◽  
Cone Beam ◽  
Standards Of Care ◽  
Reconstruction Algorithms ◽  
Oral Medicine ◽  
Patient Centered ◽  
Entire Volume ◽  
Recent Advances ◽  
Medical Physicists

Background: The cone-beam computed tomography (CBCT) technology has continuously evolved since its appearance in oral medicine in the early 2000s. Objective: To present recent advances in CBCT in oral medicine: i) selection of recent and consensual evidence-based sources, ii) structured summary of the information based on an iterative framework and iii) compliance with ethical, public health and patient-centered concerns. Main Findings: We will focus on technological advances, such as sensors and reconstruction algorithms used to improve the constant quality of the image and dosimetry. CBCT examination is now performed in almost all disciplines of oral medicine: currently, the main clinical disciplines that use CBCT acquisitions are endodontics and oral surgery, with clearly defined indications. Periodontology and ear, nose and throat medicine are more recent fields of application. For a given application and indication, the smallest possible field of view must be used. One of the major challenges in contemporary healthcare is ensuring that technological developments do not take precedence over admitted standards of care. The entire volume should be reviewed in full, with a systematic approach. All findings are noted in the patient’s record and explained to the patient, including incidental findings. This presupposes the person reviewing the images is sufficiently trained to interpret such images, inform the patient and organize the clinical pathway, with referrals to other medical or oral medicine specialties as needed. Conclusion: A close collaboration between dentists, medical physicists, radiologists, radiographers and engineers is critical for all aspects of CBCT technology.

Fast shading correction for cone beam CT in radiation therapy via sparse sampling on planning CT

2017 ◽  
Vol 44 (5) ◽  
pp. 1796-1808 ◽  
Author(s):  
Linxi Shi ◽  
Tiffany Tsui ◽  
Jikun Wei ◽  
Lei Zhu
Keyword(s):  
Radiation Therapy ◽  
Cone Beam Ct ◽  
Sparse Sampling ◽  
Cone Beam ◽  
Planning Ct

scholarly journals Cone‐beam CT for imaging of the head/brain: Development and assessment of scanner prototype and reconstruction algorithms

2020 ◽  
Vol 47 (6) ◽  
pp. 2392-2407 ◽  
Author(s):  
P. Wu ◽  
A. Sisniega ◽  
J. W. Stayman ◽  
W. Zbijewski ◽  
D. Foos ◽  
...  
Keyword(s):  
Brain Development ◽  
Cone Beam Ct ◽  
Cone Beam ◽  
Reconstruction Algorithms

Evaluation of helical cone-beam CT reconstruction algorithms

2004 ◽  
Author(s):  
T. Kohler ◽  
C. Bontus ◽  
K. Brown ◽  
D. Heuscher ◽  
M. Grass ◽  
...  
Keyword(s):  
Cone Beam Ct ◽  
Cone Beam ◽  
Ct Reconstruction ◽  
Reconstruction Algorithms

View-independent reconstruction algorithms for cone beam CT with general saddle trajectory

2006 ◽  
Vol 51 (15) ◽  
pp. 3865-3884 ◽  
Author(s):  
Haiquan Yang ◽  
Meihua Li ◽  
Kazuhito Koizumi ◽  
Hiroyuki Kudo
Keyword(s):  
Cone Beam Ct ◽  
Cone Beam ◽  
Reconstruction Algorithms

scholarly journals REVIEW OF RECENT DEVELOPMENTS IN CONE-BEAM CT RECONSTRUCTION ALGORITHMS FOR LONG-OBJECT PROBLEM

2011 ◽  
Vol 23 (2) ◽  
pp. 83 ◽  
Author(s):  
Kai Zeng ◽  
Zhiqiang Chen
Keyword(s):  
Cone Beam Ct ◽  
Region Of Interest ◽  
Axial Direction ◽  
Cone Beam ◽  
Ct Reconstruction ◽  
Reconstruction Algorithms ◽  
Recent Developments ◽  
History Of ◽  
Object Problem ◽  
Helical Scan

Long-object problem and short-object problem both deal with reconstruction problems with truncated conebeam CT projections acquired with a helical path. They have significantly less practical limitations than original exact cone-beam CT reconstruction algorithms which the cone-beam must cover the whole object. The short-object problem can be defined as reconstruction of the whole object having a finite support in the axial direction with helical scan extends a little bit above and below the object's support. However the longobject problem is to reconstruct the central region of interest (ROI) of a long object having an infinite support in the axial direction with helical scan extends a little a bit above and below the ROI. Although the short-object problem is more difficult to solve than the conventional exact reconstruction with non-truncated projections, the long-object problem presents greater challenge to researchers. Recently, with the great development of panel detector technology and computer technology, more and more researchers have been inspired to work on it. Because of great practical value of long-object algorithms, this paper focuses on the review and discussion of recent developments in long-object algorithms. All Long-object algorithms are classified as exact and approximate algorithms. After going briefly over the history of cone-beam algorithms, some novel cone-beam long-object algorithms are introduced, such as: Tam's algorithm, PImethod, PHI-method, etc. Then, the methods described are being compared and discussed.

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