AIMC Topic: Liver Neoplasms

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Liver tissue segmentation in multiphase CT scans using cascaded convolutional neural networks.

International journal of computer assisted radiology and surgery Apr 30, 2019
PURPOSE: We address the automatic segmentation of healthy and cancerous liver tissues (parenchyma, active and necrotic parts of hepatocellular carcinoma (HCC) tumor) on multiphase CT images using a deep learning approach.
Necrosis Biomarkers Tomography, X-Ray Computed Reproducibility of Results Deep Learning Image Processing, Computer-Assisted Liver Pattern Recognition, Automated Liver Neoplasms Carcinoma, Hepatocellular Humans Neural Networks, Computer Algorithms
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A Novel Method for Classifying Liver and Brain Tumors Using Convolutional Neural Networks, Discrete Wavelet Transform and Long Short-Term Memory Networks.

Sensors (Basel, Switzerland) Apr 28, 2019
Rapid classification of tumors that are detected in the medical images is of great importance in the early diagnosis of the disease. In this paper, a new liver and brain tumor classification method is proposed by using the power of convolutional neur...
Support Vector Machine Pituitary Neoplasms Wavelet Analysis Meningioma Sensitivity and Specificity Brain Neoplasms Liver Neoplasms Glioma Humans Neural Networks, Computer Tomography, X-Ray Computed
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Machine Learning for Medical Imaging.

Journal of healthcare engineering Apr 28, 2019
Support Vector Machine Algorithms Humans Reproducibility of Results Principal Component Analysis Neural Networks, Computer Deep Learning Diagnostic Imaging Machine Learning Liver Neoplasms Alzheimer Disease Software
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Deep learning for liver tumor diagnosis part I: development of a convolutional neural network classifier for multi-phasic MRI.

European radiology Apr 23, 2019
OBJECTIVES: To develop and validate a proof-of-concept convolutional neural network (CNN)-based deep learning system (DLS) that classifies common hepatic lesions on multi-phasic MRI.
Middle Aged Deep Learning ROC Curve Liver Neoplasms Aged Adult Sensitivity and Specificity Male Bile Duct Neoplasms Cholangiocarcinoma Bile Ducts, Intrahepatic Carcinoma, Hepatocellular United States Magnetic Resonance Imaging Image Interpretation, Computer-Assisted Humans Neural Networks, Computer Female Reproducibility of Results
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Deep learning reconstruction improves image quality of abdominal ultra-high-resolution CT.

European radiology Apr 11, 2019
OBJECTIVES: Deep learning reconstruction (DLR) is a new reconstruction method; it introduces deep convolutional neural networks into the reconstruction flow. This study was conducted in order to examine the clinical applicability of abdominal ultra-h...
Humans Algorithms Middle Aged Deep Learning Liver Neoplasms Abdomen Retrospective Studies Aged Radiographic Image Interpretation, Computer-Assisted Aged, 80 and over Tomography, X-Ray Computed Adult Female Male Reproducibility of Results
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Improving Outcomes Defending Patient Safety: The Learning Journey in Robotic Liver Resections.

BioMed research international Apr 8, 2019
BACKGROUND: While laparoscopy is currently adopted for hepatic resections, robotic approaches to the liver have not gained wide acceptance. We decided to analyze the learning curve in the field of robotic liver surgery comparing short-term outcomes b...
Length of Stay Liver Neoplasms Blood Loss, Surgical Humans Liver Hepatectomy Patient Safety Male Surgeons Learning Curve Retrospective Studies Middle Aged Female Postoperative Complications Operative Time Robotics Laparoscopy Robotic Surgical Procedures
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Automated classification of hepatocellular carcinoma differentiation using multiphoton microscopy and deep learning.

Journal of biophotonics Apr 1, 2019
In the case of hepatocellular carcinoma (HCC) samples, classification of differentiation is crucial for determining prognosis and treatment strategy decisions. However, a label-free and automated classification system for HCC grading has not been yet...
Liver Neoplasms Carcinoma, Hepatocellular Image Processing, Computer-Assisted Automation Microscopy, Fluorescence, Multiphoton Humans Deep Learning
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A deep learning- and partial least square regression-based model observer for a low-contrast lesion detection task in CT.

Medical physics Apr 1, 2019
PURPOSE: This work aims to develop a new framework of image quality assessment using deep learning-based model observer (DL-MO) and to validate it in a low-contrast lesion detection task that involves CT images with patient anatomical background.
Image Processing, Computer-Assisted Models, Statistical Least-Squares Analysis Radiotherapy Planning, Computer-Assisted Retrospective Studies Tomography, X-Ray Computed Deep Learning Observer Variation Liver Neoplasms Humans Radiotherapy Dosage Neural Networks, Computer Algorithms
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Diagnosis of focal liver lesions from ultrasound using deep learning.

Diagnostic and interventional imaging Mar 27, 2019
PURPOSE: The purpose of this study was to create an algorithm that simultaneously detects and characterizes (benign vs. malignant) focal liver lesion (FLL) using deep learning.
Datasets as Topic Deep Learning Ultrasonography Liver Neoplasms Liver Humans Algorithms
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Five simultaneous artificial intelligence data challenges on ultrasound, CT, and MRI.

Diagnostic and interventional imaging Mar 15, 2019
PURPOSE: The goal of this data challenge was to create a structured dynamic with the following objectives: (1) teach radiologists the new rules of General Data Protection Regulation (GDPR), while building a large multicentric prospective database of ...
Breast Neoplasms Communication Thyroid Neoplasms Ultrasonography Liver Neoplasms Magnetic Resonance Imaging Neoplasm Invasiveness Datasets as Topic Humans Artificial Intelligence Tomography, X-Ray Computed Kidney Cortex Computer Security Tibial Meniscus Injuries Interprofessional Relations Thyroid Cartilage
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