scholarly journals Torsional Ultrasound Sensor Optimization for Soft Tissue Characterization

Sensors ◽  
2017 ◽  
Vol 17 (6) ◽  
pp. 1402 ◽  
Author(s):  
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Author(s):  
Janine Rennert ◽  
Jirka Grosse ◽  
Ingo Einspieler ◽  
Wolf Bäumler ◽  
Christian Stroszczynski ◽  
...  

AIM: To evaluate the effectiveness of complementary imaging of high-resolution ultrasound including CEUS with PET/CT for tissue characterization and tumor detection. MATERIAL AND METHODS: 100 patients were examined with PET/CT and US/CEUS between January 2018 until February 2020. All patients underwent PET/CT followed by selective US/CEUS within 4 weeks. Comparison regarding concordant or diverging findings in PET/CT and US. Analysis of the differences concerning the lesions number of found by PET/CT and US/CEUS or the possibility of a secured diagnosis following ultrasound causing therapeutic changes. RESULTS: Diverging findings regarding the number of liver lesions in PET/CT and CEUS were found in 35 out of 64 patients (54%). Regarding renal lesions, a more definite diagnosis following ultrasound, causing a change of therapeutic approach, was achieved in 89%. Concordant results in PET/CT and US were found in 83%of patients with splenic and nodal findings. In 78%of patients with increased musculoskeletal or soft tissue tracer uptake, US was able to make a secured diagnosis with therapeutic changes. CONCLUSION: The present results indicate a strong benefit of complementary imaging of PET/CT and selective, high-resolution ultrasound especially in patients with liver, renal and musculoskeletal or soft tissue findings.


2016 ◽  
Vol 16 (08) ◽  
pp. 1640019 ◽  
Author(s):  
JAEHYUN SHIN ◽  
YONGMIN ZHONG ◽  
JULIAN SMITH ◽  
CHENGFAN GU

Dynamic soft tissue characterization is of importance to robotic-assisted minimally invasive surgery. The traditional linear regression method is unsuited to handle the non-linear Hunt–Crossley (HC) model and its linearization process involves a linearization error. This paper presents a new non-linear estimation method for dynamic characterization of mechanical properties of soft tissues. In order to deal with non-linear and dynamic conditions involved in soft tissue characterization, this method improves the non-linearity and dynamics of the HC model by treating parameter [Formula: see text] as independent variable. Based on this, an unscented Kalman filter is developed for online estimation of soft tissue parameters. Simulations and comparison analysis demonstrate that the proposed method is able to estimate mechanical parameters for both homogeneous tissues and heterogeneous and multi-layer tissues, and the achieved performance is much better than that of the linear regression method.


2008 ◽  
Author(s):  
Bummo Ahn ◽  
Jung Kim

Soft tissue characterization with finite element (FE) modeling is important to develop a realistic model for medical simulation, since it is possible to display complex tool-tissue interactions during medical interventions. However, it is difficult to integrate large deformation and geometrical boundary conditions to the FE computations. In this paper, the force responses and surface deformation fields of the tissues against the indentation were measured by a force transducer and three-dimensional optical system. Large indentation experiments on porcine liver were performed to estimate the radius of influence from the indented point up to 8 mm indentation and to measure the force response for 7mm indentation. The radius of influence region was plotted against various indentation depths and indenter shapes, and it could be used to determine the model size for the characterization. The tissue behavior of large deformation considering influence of the boundary conditions was characterized with FE modeling via hyperelastic and linear viscoelastic model.


2021 ◽  
pp. 102245
Author(s):  
Farah Deeba ◽  
Caitlin Schneider ◽  
Shahed Mohammed ◽  
Mohammad Honarvar ◽  
Julio Lobo ◽  
...  

2019 ◽  
Author(s):  
Kim L Schwaner ◽  
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Diego Dall Alba ◽  
Zhuoqi Cheng ◽  
Leonardo S Mattos ◽  
...  

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