scholarly journals The interactive electrode localization utility: software for automatic sorting and labeling of intracranial subdural electrodes

2016 ◽  
Vol 12 (10) ◽  
pp. 1829-1837 ◽  
Author(s):  
Roan A. LaPlante ◽  
Wei Tang ◽  
Noam Peled ◽  
Deborah I. Vallejo ◽  
Mia Borzello ◽  
...  
2014 ◽  
Vol 26 (05) ◽  
pp. 1450051
Author(s):  
Shuo Dong ◽  
Yuan Liu ◽  
Lixin Cai ◽  
Mei Bai ◽  
Hanmin Yan

Surgical treatment has been proved to be an effective way to control seizures for some kinds of intractable epilepsy. The electrocorticogram (ECoG) recorded from subdural electrodes has become an important technique for defining epileptogenic zones before surgery in clinical practice. The exact location of subdural electrodes has to be determined to establish the connection between electrodes and epileptogenic zones. Artifacts caused by the electrodes can severely affect the quality of CT imaging and sequentially image registration. In this paper, we discussed the performance of mean squares and the Mattes mutual information metric methods in multimodal image registration for subdural electrode localization. Since the skull can be regarded as a rigid body, rigid registration is sufficient for the purpose of subdural electrode localization. The vital parameter for the rigid registration is rotation. The translation result depends on the result of rotation. Both the methods performed well in the determination of the rotation center. Rotation angles of different image pairs of the same volume pair fluctuated a lot. Based on the image acquisition process, we assume that the images within the same volume pair should have the same transformation parameters for registration. Results show that the mean rotation angles of images within one dataset are approximate to the manual results that are considered to be the actual result for registration despite their fluctuation range.


2020 ◽  
Vol 4 (41) ◽  
pp. 83-87
Author(s):  
ALEKSEY SEDOV ◽  

The Federal scientific Agroengineering center VIM has developed technical tools, algorithms and software for the intelligent automatic control system for milking animals “Stimul” on the “Herringbone” milking unit in three versions. The created system does not include automatic selection gates for effective management of zootechnical and veterinary services of animals. (Research purpose) The research purpose is in developing an intelligent machine for automatic sorting of animals for servicing and managing the herd according to specified characteristics. (Materials and methods) The article presents the development of control and management systems in dairy farming based on the conceptual principles of digital transformation. The digital control system is based on a multifunctional panel controller. The created control unit has a port for connecting to the RS 485 network and provides support for network functions via the Modbus Protocol. The programming of the control unit has been made in the SMLogix tool environment, which supports the FBD function block language. (Results and discussion) The article presents an intelligent machine for automatic sorting of animal flows for servicing and managing the herd according to specified characteristics with the unification of hardware, software modules and interface. The article describes the necessary parameters for the automatic remote animal identification system, the basic component of the control system of an intelligent machine for sorting animals according to specified characteristics. (Conclusions) The machine allows to automatically identify, sort and send animals to the specified areas for individual service.


2021 ◽  
Vol 11 (10) ◽  
pp. 4349
Author(s):  
Tianzhong Xiong ◽  
Wenhua Ye ◽  
Xiang Xu

As an important part of pretreatment before recycling, sorting has a great impact on the quality, efficiency, cost and difficulty of recycling. In this paper, dual-energy X-ray transmission (DE-XRT) combined with variable gas-ejection is used to improve the quality and efficiency of in-line automatic sorting of waste non-ferrous metals. A method was proposed to judge the sorting ability, identify the types, and calculate the mass and center-of-gravity coordinates according to the shading of low-energy, the line scan direction coordinate and transparency natural logarithm ratio of low energy to high energy (R_value). The material identification was satisfied by the nearest neighbor algorithm of effective points in the material range to the R_value calibration surface. The flow-process of identification was also presented. Based on the thickness of the calibration surface, the material mass and center-of-gravity coordinates were calculated. The feasibility of controlling material falling points by variable gas-ejection was analyzed. The experimental verification of self-made materials showed that identification accuracy by count basis was 85%, mass and center-of-gravity coordinates calculation errors were both below 5%. The method proposed features high accuracy, high efficiency, and low operation cost and is of great application value even to other solid waste sorting, such as plastics, glass and ceramics.


Neuroreport ◽  
2004 ◽  
Vol 15 (17) ◽  
pp. 2625-2627 ◽  
Author(s):  
S. Fecteau ◽  
L. Carmant ◽  
C. Tremblay ◽  
M. Robert ◽  
A. Bouthillier ◽  
...  

Brain ◽  
1984 ◽  
Vol 107 (1) ◽  
pp. 115-131 ◽  
Author(s):  
Y. S. LEE ◽  
H. LUEDERS ◽  
D. S. DINNER ◽  
R.P. LESSER ◽  
J. HAHN ◽  
...  

2018 ◽  
Vol 51 (1) ◽  
pp. 60-67 ◽  
Author(s):  
Erick A. Perez-Alday ◽  
Jason A. Thomas ◽  
Muammar Kabir ◽  
Golriz Sedaghat ◽  
Nichole Rogovoy ◽  
...  

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