AI Medical Compendium Topic:
Liver Neoplasms

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Low-Dose CT With a Residual Encoder-Decoder Convolutional Neural Network.

IEEE transactions on medical imaging
Given the potential risk of X-ray radiation to the patient, low-dose CT has attracted a considerable interest in the medical imaging field. Currently, the main stream low-dose CT methods include vendor-specific sinogram domain filtration and iterativ...

Laparoscopic versus robotic surgery for hepatocellular carcinoma: the first 46 consecutive cases.

The Journal of surgical research
BACKGROUND: Hepatocellular carcinoma has a growing incidence worldwide, and represents a leading cause of death in patients with cirrhosis. Nowadays, minimally invasive approaches are spreading in every field of surgery and in liver surgery as well.

Automatic segmentation of liver tumors from multiphase contrast-enhanced CT images based on FCNs.

Artificial intelligence in medicine
This paper presents a novel, fully automatic approach based on a fully convolutional network (FCN) for segmenting liver tumors from CT images. Specifically, we designed a multi-channel fully convolutional network (MC-FCN) to segment liver tumors from...

Joint multiple fully connected convolutional neural network with extreme learning machine for hepatocellular carcinoma nuclei grading.

Computers in biology and medicine
Accurate cell grading of cancerous tissue pathological image is of great importance in medical diagnosis and treatment. This paper proposes a joint multiple fully connected convolutional neural network with extreme learning machine (MFC-CNN-ELM) arch...

Drug repositioning based on triangularly balanced structure for tissue-specific diseases in incomplete interactome.

Artificial intelligence in medicine
Finding new uses for existing drugs has become a new strategy for decades to treat more patients. Few traditional approaches consider the tissue specificities of diseases. Moreover, disease genes, drug targets and protein interaction (PPI) networks r...

Disease-free survival assessment by artificial neural networks for hepatocellular carcinoma patients after radiofrequency ablation.

Journal of the Formosan Medical Association = Taiwan yi zhi
BACKGROUND/PURPOSE: Radiofrequency ablation (RFA) provides an effective treatment for patients who exhibit early hepatocellular carcinoma (HCC) stages or are waiting for liver transplantation. It is important to assess patients after RFA. The goal of...

A novel microchip electrophoresis-based chemiluminescence immunoassay for the detection of alpha-fetoprotein in human serum.

Talanta
A sensitive immunoassay method based on microchip electrophoresis chemiluminescence (MCE-CL) detection technology was developed for the detection of tumor marker alpha-fetoprotein (AFP). This method adopts the non-competitive immunoassay mode, and wa...

Dosimetric Implications of Residual Tracking Errors During Robotic SBRT of Liver Metastases.

International journal of radiation oncology, biology, physics
PURPOSE: Although the metric precision of robotic stereotactic body radiation therapy in the presence of breathing motion is widely known, we investigated the dosimetric implications of breathing phase-related residual tracking errors.

Automatic 3D liver segmentation based on deep learning and globally optimized surface evolution.

Physics in medicine and biology
The detection and delineation of the liver from abdominal 3D computed tomography (CT) images are fundamental tasks in computer-assisted liver surgery planning. However, automatic and accurate segmentation, especially liver detection, remains challeng...