Liver Tumor Detection in CT Images by VGG16 Convolutional Neural Network
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Abstract
Automatic tumor detection and segmentation is essential for computer-aided diagnosis of liver tumors in CT images. However, it is a challenging task in low-contrast images as the low-level images are too weak to detect. In this project, we propose a new method for the automatic detection of liver tumors. VGG16 CNN has been used as a powerful tool for liver cancer analysis. Whereas the CT-based lesion-type definition defines the diagnosis and therapeutic strategy, the distinction between cancer and non-cancer lesions is crucial. It demands highly qualified experience, expertise, and resources. However, a deep end-to-end learning approach to help discrimination in abdominal CT images of the liver between liver metastases of colorectal cancer and benign cysts has been analyzed.
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