International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


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Informative Article | Physics Science | Egypt | Volume 4 Issue 5, May 2015


Diagnosis and Classification of Liver Cancer using LIBS Technique and Artificial Neural Network

Ashraf M. EL Sherbini | Mohamed M. Hagras | Hania H. Farag | Mohamed R.M. Rizk


Abstract: (LIBS) technique was used to diagnose liver cancer. Radiation from Nd YAG laser at 532 nm with 5.7x108 W/cm2 was used to initiate plasma on surface of liver tissue. The light emitted was analyzed which allowed detection of trace elements in malignant tissue. Twenty six malignant samples in the age range from 6 to 56 years were categorized into 4 sets with different levels of malignancy depending on histological analysis. The following trace elements Mg, K, Ca, Na, Fe, Mn and Cu were identify. The concentration of the different trace elements was found to steeply rise with category #1 in the malignant tissues in comparison to the normal (Zero) ones by a factors of x 6.5, 2.5, 7, 4.5, 7, 6.5, 2.5, respectively with a further increase as we pass from category #2 to #4, with much slower rates. The results from the LIBS-Technique were fed-back to an artificial neural network (ANN) to take a decision about the classification of the cancer. A confirmation of about 80 % was found in close agreement with standard documented international values.


Keywords: LIBS, Liver Cancer, ANN, OES


Edition: Volume 4 Issue 5, May 2015,


Pages: 1153 - 1158


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How to Cite this Article?

Ashraf M. EL Sherbini, Mohamed M. Hagras, Hania H. Farag, Mohamed R.M. Rizk, "Diagnosis and Classification of Liver Cancer using LIBS Technique and Artificial Neural Network", International Journal of Science and Research (IJSR), Volume 4 Issue 5, May 2015, pp. 1153-1158, https://www.ijsr.net/get_abstract.php?paper_id=SUB154404

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