Deep learning-based methods, in particular, convolutional neural networks and fully
convolutional networks are now widely used in the medical image analysis domain. The …

Deep learning has become a thriving force in the computer aided diagnosis of liver cancer,
as it solves extremely complicated challenges with high accuracy over time and facilitates …

BACKGROUND Artificial intelligence, such as convolutional neural networks (CNNs), has
been used in the interpretation of images and the diagnosis of hepatocellular cancer (HCC) …

Current research on computer-aided diagnosis (CAD) of liver cancer is based on traditional
feature engineering methods, which have several drawbacks including redundant features …

Liver cancer is one of the world's largest causes of death to humans. It is a difficult task and
time consuming to identify the cancer tissue manually in the present scenario. The …

The liver is a frequent site of benign and malignant, primary and metastatic tumors.
Hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC) are the most …

An estimated 9.6 million deaths, or one in every six deaths, were attributed to cancer in
2018, making it the second highest cause of death worldwide. Men are more likely to …

Artificial intelligence (AI), particularly deep learning algorithms, is gaining extensive attention
for its excellent performance in image-recognition tasks. They can automatically make a …

Background Medical image processing has a strong footprint in radio diagnosis for the
detection of diseases from the images. Several computer-aided systems were researched in …

Liver cancer is one of the leading causes of death worldwide. Computer-aided diagnoses
play an important role in liver lesion diagnoses (classification). Recently, several deep …