Automatic extraction of multiple-study X-ray images

Author(s):  
Stella Dumencic ◽  
Sebastian Tschauner ◽  
Franko Hrzic ◽  
Ivan Stajduhar
Author(s):  
Kwang Baek Kim ◽  
Doo Heon Song ◽  
Sang-Seok Yun

Early detection of subtle fracture is important particularly for the senior citizens’ quality of life. Naked eye examination from X-ray image may cause false negatives due to operator subjectivity thus computer vision based automatic detection software is much needed in practice.  In this paper, we propose an automatic extraction method for suspisious wrist fracture regions. We apply K-means in pixel clustering to form the candidate part of possible fracture from wrist X-ray image automatically. This method can recover previously detected patterned false cases with edge detection method after fuzzy stretching. The proposed method is successful in 16 out of 20 tested cases in experiment.


Author(s):  
Daisuke Wakamiya ◽  
Toshiyuki Tanaka ◽  
Isao Kabaya ◽  
Mikiya Kano ◽  
Isamu Iwayoshi

2018 ◽  
Vol 20 (29) ◽  
pp. 19560-19571 ◽  
Author(s):  
Pietro Guccione ◽  
Luca Palin ◽  
Benny Danilo Belviso ◽  
Marco Milanesio ◽  
Rocco Caliandro

A new algorithm to extract in an automatic way kinetic parameters from a set of measurements from in situ experiments is presented and applied to X-ray powder diffraction and Raman spectroscopy.


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