Non-rigid curve correspondence for estimating heart motion

Author(s):  
Hemant D. Tagare
Keyword(s):  
1961 ◽  
Vol 61 (1) ◽  
pp. 61-75 ◽  
Author(s):  
Tsuneo Yoshida ◽  
Masayoshi Mori ◽  
Yasuharu Nimura ◽  
Gen-ichi Hikita ◽  
Shinpachi Takagishi ◽  
...  

1986 ◽  
Vol 11 (10) ◽  
Author(s):  
John Yiannikas ◽  
Setsuo Takatani ◽  
WilliamJ. MacIntyre ◽  
DonaldA. Underwood ◽  
SebastianA. Cook ◽  
...  
Keyword(s):  

1977 ◽  
Vol 10 (11-12) ◽  
pp. 789-797 ◽  
Author(s):  
T.R. Fenton ◽  
R. Vas

2021 ◽  
Vol 143 (7) ◽  
Author(s):  
Ran Hao ◽  
E. Erdem Tuna ◽  
M. Cenk Çavuşoğlu

Abstract Contact force quality is one of the most critical factors for safe and effective lesion formation during catheter based atrial fibrillation ablation procedures. In this paper, the contact stability and contact safety of a novel magnetic resonance imaging (MRI)-actuated robotic cardiac ablation catheter subject to surface motion disturbances are studied. First, a quasi-static contact force optimization algorithm, which calculates the actuation needed to achieve a desired contact force at an instantaneous tissue surface configuration is introduced. This algorithm is then generalized using a least-squares formulation to optimize the contact stability and safety over a prediction horizon for a given estimated heart motion trajectory. Four contact force control schemes are proposed based on these algorithms. The first proposed force control scheme employs instantaneous heart position feedback. The second control scheme applies a constant actuation level using a quasi-periodic heart motion prediction. The third and the last contact force control schemes employ a generalized adaptive filter-based heart motion prediction, where the former uses the predicted instantaneous position feedback, and the latter is a receding horizon controller. The performance of the proposed control schemes is compared and evaluated in a simulation environment.


2021 ◽  
Author(s):  
Miloš Kojić ◽  

Modeling of heart wall deformation remains a challenge due to complex structure of tissue, which contains different group of cells and connective tissue. Muscle cells are dominant where, besides stresses coming from tissue deformation, active stresses are generated representing the load which produces heart motion and function. These cells form a helicoidal structure within so- called wall sheets and are considered as tissue fibers. Usual approach in the finite element (FE) discretization is to use 3D isoparametric elements. The dominant stresses lie in the sheet planes, while normal stresses in the wall normal directions are of the order smaller. Taking this stress state into account, we explore a possibility to model heart wall by membrane finite elements, hence considering the wall as a thick membrane (shell without bending effects). The membrane element is composite, containing layers over the thickness and variation of the direction of fibers. The formulated element is applied to a simplified left ventricle geometry to demonstrate a possibility to simulate heart mechanics by models which are much smaller and simpler for use than 3D conventional models.


1975 ◽  
pp. 248-248
Author(s):  
V. E. Friedewald ◽  
M. Laughead ◽  
R. Jennett ◽  
J. E. Futral ◽  
M. Wilcox ◽  
...  

2015 ◽  
Vol 18 (2) ◽  
pp. 123-130
Author(s):  
Huong Thi Minh Nguyen ◽  
Khai Quoc Le ◽  
Hai Chi Nguyen ◽  
Tri Minh Ngo ◽  
Linh Quang Huynh

ERPs (Event Related Potentials) are EEG signals which are directly measured from cortical electrical response to external stimuli such as feelings, sensual or cognitive events. The evaluation of the amplitude and latency of the ERP wave has important significance in evaluating neurological reflex. However, the ERP wave amplitude is small compared with the EEG wave, and considerably affected by the noise such as eyes, muscles, heart motion etc. In this paper, datasets are collected from ERPLAB and journals provided available datasets with the stimulus of sound and light. Using adaptive noise cancellation (ANC) combined with LMS algorithm the waves P300 of ERP were detected and separated. The algorithm was evaluated by the ratio SNR and average value. Results were compared with other published tools such as P300 calculation algorithm of ERPLAB softwar.


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