Automatic Liver Cancer Detection Using Deep Convolution Neural Network

Automatic liver cancer detection (ALCD) is very crucial in automatic biomedical image analysis diagnosis as it the largest organ body and plays a significant role metabolic process well elimination of toxins. In last decade, various machine deep learning schemes have been investigated for ALCD using computed tomography (CT) images. However, CT images challenging because noise, intricate structure abdominal images, textural changes throughout making segmentation vital challenge that may result both under-segmentation (u-seg) over-segmentation (o-seg) organ. This paper presents based on proposed Edge Strengthening Parallel UNet (ESP-UNet) to avoid u-seg o-seg Further, offered lightweight sequential Deep Convolution Neural Networks (DCNN). The consequences ESP-UNet DCNN-based are evaluated accuracy, recall, precision, F1-score. suggested approach provides noteworthy improvement over traditional state arts.