Automatic extraction of femur contours from calibrated x-ray images: A Bayesian inference approach

2008 ◽  
Author(s):  
Xiao Dong ◽  
Guoyan Zheng
Keyword(s):  
Bayesian Inference ◽  
Automatic Extraction ◽  
X Ray

scholarly journals Automatic segmentation of wrist bone fracture area by K-means pixel clustering from X-ray image

2019 ◽  
Vol 9 (6) ◽  
pp. 5205
Author(s):  
Kwang Baek Kim ◽  
Doo Heon Song ◽  
Sang-Seok Yun
Keyword(s):  
Automatic Segmentation ◽  
Wrist Fracture ◽  
Automatic Extraction ◽  
False Negatives ◽  
X Ray ◽  
Fracture Area ◽  
Eye Examination ◽  
Detection Software ◽  
Edge Detection Method

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.

Automatic extraction of tumor region on X-ray image of animals

2006 ◽  
Author(s):  
Daisuke Wakamiya ◽  
Toshiyuki Tanaka ◽  
Isao Kabaya ◽  
Mikiya Kano ◽  
Isamu Iwayoshi
Keyword(s):  
Automatic Extraction ◽  
X Ray ◽  
Tumor Region

scholarly journals Wilson statistics: derivation, generalization and applications to electron cryomicroscopy

2021 ◽  
Vol 77 (5) ◽  
Author(s):  
Amit Singer
Keyword(s):  
Bayesian Inference ◽  
Theoretical Foundation ◽  
Three Dimensional ◽  
Electron Cryomicroscopy ◽  
High Frequencies ◽  
X Ray ◽  
X Ray Crystallography ◽  
Bayesian Inference Framework ◽  
Higher Order Spectra ◽  
Mathematical Derivation

The power spectrum of proteins at high frequencies is remarkably well described by the flat Wilson statistics. Wilson statistics therefore plays a significant role in X-ray crystallography and more recently in electron cryomicroscopy (cryo-EM). Specifically, modern computational methods for three-dimensional map sharpening and atomic modelling of macromolecules by single-particle cryo-EM are based on Wilson statistics. Here the first rigorous mathematical derivation of Wilson statistics is provided. The derivation pinpoints the regime of validity of Wilson statistics in terms of the size of the macromolecule. Moreover, the analysis naturally leads to generalizations of the statistics to covariance and higher-order spectra. These in turn provide a theoretical foundation for assumptions underlying the widespread Bayesian inference framework for three-dimensional refinement and for explaining the limitations of autocorrelation-based methods in cryo-EM.

scholarly journals Efficient nonparametric Bayesian inference for $X$-ray transforms

2019 ◽  
Vol 47 (2) ◽  
pp. 1113-1147 ◽  
Author(s):  
François Monard ◽  
Richard Nickl ◽  
Gabriel P. Paternain
Keyword(s):  
Bayesian Inference ◽  
Nonparametric Bayesian ◽  
X Ray ◽  
Ray Transforms

Principal component analysis for automatic extraction of solid-state kinetics from combined in situ experiments

2018 ◽  
Vol 20 (29) ◽  
pp. 19560-19571 ◽  
Author(s):  
Pietro Guccione ◽  
Luca Palin ◽  
Benny Danilo Belviso ◽  
Marco Milanesio ◽  
Rocco Caliandro
Keyword(s):  
Principal Component Analysis ◽  
Raman Spectroscopy ◽  
Solid State ◽  
Powder Diffraction ◽  
Principal Component ◽  
Automatic Extraction ◽  
X Ray ◽  
Solid State Kinetics ◽  
In Situ Experiments

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.

Automatic extraction of multiple-study X-ray images

2021 ◽  
Author(s):  
Stella Dumencic ◽  
Sebastian Tschauner ◽  
Franko Hrzic ◽  
Ivan Stajduhar
Keyword(s):  
Automatic Extraction ◽  
X Ray ◽  
Multiple Study
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