Liying Wang1 , Zhiqiang Xu2, Shuihua Wang3,4,5,*
CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.3, pp. 1001-1015, 2020, DOI:10.32604/cmes.2020.010753
- 21 August 2020
Abstract Artificial Intelligence (AI) becomes one hotspot in the field of the medical images analysis and provides rather promising solution. Although some
research has been explored in smart diagnosis for the common diseases of urinary
system, some problems remain unsolved completely A nine-layer Convolutional
Neural Network (CNN) is proposed in this paper to classify the renal Computed
Tomography (CT) images. Four group of comparative experiments prove the
structure of this CNN is optimal and can achieve good performance with average
accuracy about 92.07 ± 1.67%. Although our renal CT data is not very large, we
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