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Liver Neoplasms

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Classification of focal liver lesions in CT images using convolutional neural networks with lesion information augmented patches and synthetic data augmentation.

Medical physics
PURPOSE: We propose a deep learning method that classifies focal liver lesions (FLLs) into cysts, hemangiomas, and metastases from portal phase abdominal CT images. We propose a synthetic data augmentation process to alleviate the class imbalance and...

Pure laparoscopic versus robotic liver resections: Multicentric propensity score-based analysis with stratification according to difficulty scores.

Journal of hepato-biliary-pancreatic sciences
BACKGROUND: The benefits of pure laparoscopic and robot-assisted liver resections (LLR and RALR) are known in comparison to open surgery. The aim of the present retrospective comparative study is to investigate the role of RALR and LLR according to d...

Robotic resection for hydatid disease of the liver.

BMJ case reports
Robotic-assisted surgery for the management of hepatic echinococcosis was introduced in 2016. The advantage it offers over laparoscopy is less rigidity with the use of the 360° rotation of the Endo-Wrist technology, thus allowing the preservation of ...

Single-breath-hold T2WI liver MRI with deep learning-based reconstruction: A clinical feasibility study in comparison to conventional multi-breath-hold T2WI liver MRI.

Magnetic resonance imaging
OBJECTIVE: To investigate the clinical feasibility of single-breath-hold (SBH) T2-weighted (T2WI) liver MRI with deep learning-based reconstruction in the evaluation of image quality and lesion delineation, compared with conventional multi-breath-hol...

Application of machine learning to large in-vitro databases to identify cancer cell characteristics: telomerase reverse transcriptase (TERT) expression.

Oncogene
Advances in biotechnology and machine learning have created an enhanced environment for unearthing and exploiting previously unrecognized relationships between genomic and epigenetic data with potential therapeutic implications. We applied advanced a...

Image texture, low contrast liver lesion detectability and impact on dose: Deep learning algorithm compared to partial model-based iterative reconstruction.

European journal of radiology
OBJECTIVES: To compare deep learning (True Fidelity, TF) and partial model based Iterative Reconstruction (ASiR-V) algorithm for image texture, low contrast lesion detectability and potential dose reduction.

LiverNet: efficient and robust deep learning model for automatic diagnosis of sub-types of liver hepatocellular carcinoma cancer from H&E stained liver histopathology images.

International journal of computer assisted radiology and surgery
PURPOSE: Liver cancer is one of the most common types of cancers in Asia with a high mortality rate. A common method for liver cancer diagnosis is the manual examination of histopathology images. Due to its laborious nature, we focus on alternate dee...

Artificial intelligence assists identifying malignant versus benign liver lesions using contrast-enhanced ultrasound.

Journal of gastroenterology and hepatology
BACKGROUND AND AIM: This study aims to construct a strategy that uses assistance from artificial intelligence (AI) to assist radiologists in the identification of malignant versus benign focal liver lesions (FLLs) using contrast-enhanced ultrasound (...

A novel multi-DoF surgical robotic system for brachytherapy on liver tumor: Design and control.

International journal of computer assisted radiology and surgery
PURPOSE: Radioactive seed implantation is an effective invasive treatment method for malignant liver tumors in hepatocellular carcinomas. However, challenges of the manual procedure may degrade the efficacy of the technique, such as the high accuracy...