scholarly journals Automatic Joint Part Detection Method for Joint Space Measurement

2021 ◽  
Vol 9 (3) ◽  
Author(s):  
Kosuke Goto ◽  
◽  
Tomio Goto ◽  
Koji Funahashi
Keyword(s):  
Detection Method ◽  
Joint Space ◽  
Joint Space Measurement ◽  
Space Measurement

scholarly journals Joint space measurement in hand radiographs using computerized image analysis

1995 ◽  
Vol 38 (7) ◽  
pp. 891-901 ◽  
Author(s):  
Michael F. James ◽  
Geoff Heald ◽  
John H. Shorter ◽  
Robert A. Turner
Keyword(s):  
Image Analysis ◽  
Joint Space ◽  
Computerized Image Analysis ◽  
Joint Space Measurement ◽  
Hand Radiographs ◽  
Space Measurement

Solid-phase immunoelectron microscopy for rapid diagnosis of enteroviruses

1984 ◽  
Vol 42 ◽  
pp. 226-227 ◽  
Author(s):  
K. Pegg-Feige ◽  
F. W. Doane
Keyword(s):  
Electron Microscopy ◽  
Cell Culture ◽  
Immunoelectron Microscopy ◽  
Detection Method ◽  
Solid Phase ◽  
Protein A ◽  
Plant Viruses ◽  
Rapid Diagnosis ◽  
Virus Diagnosis ◽  
Antiviral Antibody

Immunoelectron microscopy (IEM) applied to rapid virus diagnosis offers a more sensitive detection method than direct electron microscopy (DEM), and can also be used to serotype viruses. One of several IEM techniques is that introduced by Derrick in 1972, in which antiviral antibody is attached to the support film of an EM specimen grid. Originally developed for plant viruses, it has recently been applied to several animal viruses, especially rotaviruses. We have investigated the use of this solid phase IEM technique (SPIEM) in detecting and identifying enteroviruses (in the form of crude cell culture isolates), and have compared it with a modified “SPIEM-SPA” method in which grids are coated with protein A from Staphylococcus aureus prior to exposure to antiserum.

Chondroitin Reduced Joint Space Narrowing in OA

2006 ◽  
Vol 5 (12) ◽  
pp. 16
Author(s):  
NANCY WALSH
Keyword(s):  
Joint Space Narrowing ◽  
Joint Space

A Fault Detection Approach Based on Sound Signal Analysis for Equipment Monitoring

2020 ◽  
pp. 129-139
Author(s):  
Weihai Sun ◽  
Lemei Han
Keyword(s):  
Fault Detection ◽  
Signal Analysis ◽  
Energy Analysis ◽  
Detection Method ◽  
Sound Signal ◽  
Practical Significance ◽  
Time Frequency ◽  
Detection Approach ◽  
Machine Fault ◽  
Learning Data

Machine fault detection has great practical significance. Compared with the detection method that requires external sensors, the detection of machine fault by sound signal does not need to destroy its structure. The current popular audio-based fault detection often needs a lot of learning data and complex learning process, and needs the support of known fault database. The fault detection method based on audio proposed in this paper only needs to ensure that the machine works normally in the first second. Through the correlation coefficient calculation, energy analysis, EMD and other methods to carry out time-frequency analysis of the subsequent collected sound signals, we can detect whether the machine has fault.

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