超音波画像におけるニューラルネットワークを用いた慢性C型肝炎の進行度診断(J06-2 イメージベースト達成バイオメカニクス解析(2),J06 イメージベースト達成バイオメカニクス解析)

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  • Tissue Characterization of Chronic Hepatitis C under Ultrasonography using Neural Network

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The use of the ultrasound-imaging platform in medical facilities has significantly increased in recent years due to its superior capability, namely high resolution, small influence to the human body and so on. Though the doctors diagnose a tissue characterization of a liver by observing an image obtained by ultrasound, a diagnostic result seems to make a difference with experience of doctors. Therefore a quantitative analysis method concerning ultrasonography is required. This paper proposes a CAD (Computer Aided Diagnosis) by a neural network, which diagnoses a tissue characterization of liver. This system studies three kinds of teacher signal (conditions of liver: normal, chronic hepatitis and liver cirrhosis). As a result, this system is confirmed that it can distinguish between normal of liver and liver cirrhosis. Our future purpose is the discriminate accuracy improved by increasing the pattern of neural network system.

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