COMPUTER-AIDED IMAGE ANALYSIS AND EPR CHARACTERIZATION OF TRANSFORMED ASBESTOS CONTAINING WASTES

Residual stresses significantly influence the strength and lifetime of the glass products, therefore their qualification and quantification during production is basically important for evaluating their probable reliability in application. The current paper aims at introducing a novel procedure of the suggested automatic glass quality test based on instrumented scratch test completed with computer aided image analysis. A special emphasis is put on the problem of limited reproducibility and reliability of the image processing, arisen in the first stage of the research work. The latest results consisting in the development of a new algorithm, providing a more reliable evaluation of the test data will be described.

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COMPUTER-AIDED CHARACTERIZATION OF THYROID NODULES BY IMAGE ANALYSIS METHODS

Computational Methods in Sciences and Engineering 2003 ◽

10.1142/9789812704658_0140 ◽

2003 ◽

Author(s):

S. TSANTIS ◽

I. KALATZIS ◽

N. PILIOURAS ◽

D. CAVOURAS ◽

N. DIMITROPOULOS ◽

...

Keyword(s):

Image Analysis ◽

Thyroid Nodules ◽

Analysis Methods ◽

Computer Aided

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A computer-aided measuring system for the characterization of yeast populations combining 2D-image analysis, electronic particle counter, and flow cytometry

Biotechnology and Bioengineering ◽

10.1002/bit.260390313 ◽

1992 ◽

Vol 39 (3) ◽

pp. 343-350 ◽

Cited By ~ 25

Author(s):

P. G. Huls ◽

N. Nanninga ◽

E. A. van Spronsen ◽

J. A. C. Valkenburg ◽

N. O. E. Vishcer ◽

...

Keyword(s):

Flow Cytometry ◽

Image Analysis ◽

Measuring System ◽

Particle Counter ◽

Computer Aided ◽

Electronic Particle Counter

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The effectiveness of surgical treatment of strabismus on the basis of standard and advanced diagnostic algorithm with the use of computer-aided image analysis eyes

Oftalmologicheskii Zhurnal ◽

10.31288/oftalmolzh2015249 ◽

2015 ◽

Vol 54 (2) ◽

pp. 4-9

Author(s):

D. Romanenko ◽

◽

N. Bushuyeva ◽

Sh. Duhayer ◽

O. Pelypenko ◽

...

Keyword(s):

Image Analysis ◽

Surgical Treatment ◽

Diagnostic Algorithm ◽

Computer Aided

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Native mitochondrial creatine kinase forms octameric structures. II. Characterization of dimers and octamers by ultracentrifugation, direct mass measurements by scanning transmission electron microscopy, and image analysis of single mitochondrial creatine kinase octamers.

Journal of Biological Chemistry ◽

10.1016/s0021-9258(18)37483-0 ◽

1988 ◽

Vol 263 (32) ◽

pp. 16954-16962 ◽

Cited By ~ 8

Author(s):

T Schnyder ◽

A Engel ◽

A Lustig ◽

T Wallimann

Keyword(s):

Electron Microscopy ◽

Transmission Electron Microscopy ◽

Image Analysis ◽

Creatine Kinase ◽

Scanning Transmission Electron Microscopy ◽

Mitochondrial Creatine Kinase ◽

Mass Measurements ◽

Transmission Electron ◽

Scanning Transmission

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Application of artificial intelligence in pancreaticobiliary diseases

Therapeutic Advances in Gastrointestinal Endoscopy ◽

10.1177/2631774521993059 ◽

2021 ◽

Vol 14 ◽

pp. 263177452199305

Author(s):

Hemant Goyal ◽

Rupinder Mann ◽

Zainab Gandhi ◽

Abhilash Perisetti ◽

Zhongheng Zhang ◽

...

Keyword(s):

Artificial Intelligence ◽

Response To Treatment ◽

Endoscopic Retrograde ◽

Artificial Intelligence Techniques ◽

Computer Aided ◽

Rapid Pace ◽

Cystic Pancreatic Lesions ◽

Aided Diagnosis

The role of artificial intelligence and its applications has been increasing at a rapid pace in the field of gastroenterology. The application of artificial intelligence in gastroenterology ranges from colon cancer screening and characterization of dysplastic and neoplastic polyps to the endoscopic ultrasonographic evaluation of pancreatic diseases. Artificial intelligence has been found to be useful in the evaluation and enhancement of the quality measure for endoscopic retrograde cholangiopancreatography. Similarly, artificial intelligence techniques like artificial neural networks and faster region-based convolution network are showing promising results in early and accurate diagnosis of pancreatic cancer and its differentiation from chronic pancreatitis. Other artificial intelligence techniques like radiomics-based computer-aided diagnosis systems could help to differentiate between various types of cystic pancreatic lesions. Artificial intelligence and computer-aided systems also showing promising results in the diagnosis of cholangiocarcinoma and the prediction of choledocholithiasis. In this review, we discuss the role of artificial intelligence in establishing diagnosis, prognosis, predicting response to treatment, and guiding therapeutics in the pancreaticobiliary system.

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