A Novel Hierarchical Information Fusion Method for Three-Dimensional Upper Limb Motion Estimation

2011 ◽  
Vol 60 (11) ◽  
pp. 3709-3719 ◽  
Author(s):  
Zhi-Qiang Zhang ◽  
Jian-Kang Wu
Keyword(s):  
Motion Estimation ◽  
Information Fusion ◽  
Upper Limb ◽  
Three Dimensional ◽  
Fusion Method

Fault Classification of Hydroelectric Generating Unit Based on Improved Evidence Theory

2014 ◽  
Vol 7 (1) ◽  
pp. 78-83 ◽  
Author(s):  
Jiatang Cheng ◽  
Li Ai ◽  
Zhimei Duan ◽  
Yan Xiong
Keyword(s):  
Fault Diagnosis ◽  
Information Fusion ◽  
Evidence Theory ◽  
Fault Classification ◽  
Fusion Method ◽  
Inconsistent Result ◽  
High Conflict

Aiming at the problem of the conventional vibration fault diagnosis technology with inconsistent result of a hydroelectric generating unit, an information fusion method was proposed based on the improved evidence theory. In this algorithm, the original evidence was amended by the credibility factor, and then the synthesis rule of standard evidence theory was utilized to carry out information fusion. The results show that the proposed method can obtain any definitive conclusion even if there is high conflict evidence in the synthesis evidence process, and may avoid the divergent phenomenon when the consistent evidence is fused, and is suitable for the fault classification of hydroelectric generating unit.

scholarly journals Study protocol for a single-centre non-inferior randomised controlled trial on a novel three-dimensional matrix positioning-based cognitive fusion-targeted biopsy and software-based fusion-targeted biopsy for the detection rate of clinically significant prostate cancer in men without a prior biopsy

BMJ Open ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. e041427
Author(s):  
Biming He ◽  
Rongbing Li ◽  
Dongyang Li ◽  
Liqun Huang ◽  
Xiaofei Wen ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Detection Rate ◽  
Three Dimensional ◽  
Multiparametric Mri ◽  
Fusion Method ◽  
Targeted Biopsy ◽  
Cognitive Fusion ◽  
Single Centre ◽  
Clinically Significant ◽  
Randomised Controlled

IntroductionThe classical pathway for diagnosing prostate cancer is systematic 12-core biopsy under the guidance of transrectal ultrasound, which tends to underdiagnose the clinically significant tumour and overdiagnose the insignificant disease. Another pathway named targeted biopsy is using multiparametric MRI to localise the tumour precisely and then obtain the samples from the suspicious lesions. Targeted biopsy, which is mainly divided into cognitive fusion method and software-based fusion method, is getting prevalent for its good performance in detecting significant cancer. However, the preferred targeted biopsy technique in detecting clinically significant prostate cancer between cognitive fusion and software-based fusion is still beyond consensus.Methods and analysisThis trial is a prospective, single-centre, randomised controlled and non-inferiority study in which all men suspicious to have clinically significant prostate cancer are included. This study aims to determine whether a novel three-dimensional matrix positioning cognitive fusion-targeted biopsy is non-inferior to software-based fusion-targeted biopsy in the detection rate of clinically significant cancer in men without a prior biopsy. The main inclusion criteria are men with elevated serum prostate-specific antigen above 4–20 ng/mL or with an abnormal digital rectal examination and have never had a biopsy before. A sample size of 602 participants allowing for a 10% loss will be recruited. All patients will undergo a multiparametric MRI examination, and those who fail to be found with a suspicious lesion, with the anticipation of half of the total number, will be dropped. The remaining participants will be randomly allocated to cognitive fusion-targeted biopsy (n=137) and software-based fusion-targeted biopsy (n=137). The primary outcome is the detection rate of clinically significant prostate cancer for cognitive fusion-targeted biopsy and software-based fusion-targeted biopsy in men without a prior biopsy. The clinically significant prostate cancer will be defined as the International Society of Urological Pathology grade group 2 or higher.Ethics and disseminationEthical approval was obtained from the ethics committee of Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China. The results of the study will be disseminated and published in international peer-reviewed journals.Trial registration numberClinicalTrials.gov Registry (NCT04271527).

scholarly journals Two-Dimensional Visualization of the Three-Dimensional Planned Sacroiliac Screw Corridor with the Slice Fusion Method

2021 ◽  
Vol 10 (2) ◽  
pp. 184
Author(s):  
Maximilian Kerschbaum ◽  
Siegmund Lang ◽  
Florian Baumann ◽  
Volker Alt ◽  
Michael Worlicek
Keyword(s):  
Pelvic Ring ◽  
Three Dimensional ◽  
Fusion Method ◽  
Two Dimensional ◽  
Posterior Pelvic Ring ◽  
Simple Method ◽  
Sacroiliac Screw ◽  
Screw Insertion ◽  
Multiplanar Reconstructions ◽  
Screw Position

Insertion of sacro-iliac (SI) screws for stabilization of the posterior pelvic ring without intraoperative navigation or three-dimensional imaging can be challenging. The aim of this study was to develop a simple method to visualize the ideal SI screw corridor, on lateral two-dimensional images, corresponding to the lateral fluoroscopic view, used intraoperatively while screw insertion, to prevent neurovascular injury. We used multiplanar reconstructions of pre- and postoperative computed tomography scans (CT) to determine the position of the SI corridor. Then, we processed the dataset into a lateral two-dimensional slice fusion image (SFI) matching head and tip of the screw. Comparison of the preoperative SFI planning and the screw position in the postoperative SFI showed reproducible results. In conclusion, the slice fusion method is a simple technique for translation of three-dimensional planned SI screw positioning into a two-dimensional strict lateral fluoroscopic-like view.

Adaptive Information Fusion for Human Upper Limb Movement Estimation

2012 ◽  
Vol 42 (5) ◽  
pp. 1100-1108 ◽  
Author(s):  
Zhi-Qiang Zhang ◽  
Lian-Ying Ji ◽  
Zhi-Pei Huang ◽  
Jian-Kang Wu
Keyword(s):  
Information Fusion ◽  
Upper Limb ◽  
Limb Movement ◽  
Human Upper Limb
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