Using convolutional neural networks to detect the tumor size and lymph node metastasis of colon cancer patients in MRI
Subject Areas : Biomedical Engineering
Mohammadreza Hedyehzadeh
1
*
,
Mahdi Yousefi
2
1 - Department of Biomedical Engineering, Dezful Branch, Islamic Azad University, Dezful, Iran
2 - Department of Electrical Engineering, Najafabad branch, Islamic Azad University, Najafabad, Iran
Keywords: Colon cancer, VGG-16, Magnetic resonance imaging, Tumor size, Lymph node metastasis,
Abstract :
Colon cancer is the third most common cancer from all cancers in 2020. In determining the appropriate treatment, the oncologist has to know the stage of the tumor, which is the most common method of the “Tumour, Node, Metastasis” staging system. Therefore, in this study, an attempt is made to estimate the size of the tumor and the extent of its spread to the lymph nodes with the help of magnetic resonance images. The data of this study was collected from the TCIA portal and in the first processing step, after improving the image quality, segmentation was done to separate the tumor region from the whole image. In this study, in order to extract and classify the features, the convolutional neural network VGG-16 was used and for the validation, the 10-fold method was applied. The results of this study indicate an accuracy of 94.2%, which is better than pathological and CT methods with accuracy of 91% and 77%. It should be noted that the effectiveness of the implemented algorithm in separating the 1st class was higher than the other class. Still, no significant difference was seen between the average values of the parameters in the three classes.
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