AIMC Topic: Liver

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Data augmentation using generative adversarial networks (CycleGAN) to improve generalizability in CT segmentation tasks.

Scientific reports Nov 15, 2019
Labeled medical imaging data is scarce and expensive to generate. To achieve generalizable deep learning models large amounts of data are needed. Standard data augmentation is a method to increase generalizability and is routinely performed. Generati...
Neural Networks, Computer Algorithms Research Design Humans Kidney Liver Organ Size Tomography, X-Ray Computed Deep Learning Image Processing, Computer-Assisted Anatomy, Cross-Sectional Datasets as Topic Image Enhancement Spleen
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Incorporating prior shape knowledge via data-driven loss model to improve 3D liver segmentation in deep CNNs.

International journal of computer assisted radiology and surgery Nov 4, 2019
PURPOSE: Convolutional neural networks (CNNs) have obtained enormous success in liver segmentation. However, there are several challenges, including low-contrast images, and large variations in the shape, and appearance of the liver. Incorporating pr...
Humans Image Processing, Computer-Assisted Liver Models, Anatomic Neural Networks, Computer Algorithms Tomography, X-Ray Computed
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A Commentary on "Robotic versus laparoscopic liver resection in complex cases of left lateral sectionectomy" (Int J Surg 2019; 67: 54-60).

International journal of surgery (London, England) Nov 2, 2019
Laparoscopy Robotic Surgical Procedures Hepatectomy Liver Robotics
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Unsupervised 3D End-to-End Medical Image Registration With Volume Tweening Network.

IEEE journal of biomedical and health informatics Nov 1, 2019
3D medical image registration is of great clinical importance. However, supervised learning methods require a large amount of accurately annotated corresponding control points (or morphing), which are very difficult to obtain. Unsupervised learning m...
Liver Unsupervised Machine Learning Databases, Factual Tomography, X-Ray Computed Humans Imaging, Three-Dimensional Neural Networks, Computer Algorithms
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Deep Learning-Based Classification of Liver Cancer Histopathology Images Using Only Global Labels.

IEEE journal of biomedical and health informatics Oct 28, 2019
Liver cancer is a leading cause of cancer deaths worldwide due to its high morbidity and mortality. Histopathological image analysis (HIA) is a crucial step in the early diagnosis of liver cancer and is routinely performed manually. However, this pro...
Liver Humans Image Interpretation, Computer-Assisted Algorithms Histological Techniques Databases, Factual Deep Learning Liver Neoplasms Early Detection of Cancer
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Fully automated convolutional neural network-based affine algorithm improves liver registration and lesion co-localization on hepatobiliary phase T1-weighted MR images.

European radiology experimental Oct 26, 2019
BACKGROUND: Liver alignment between series/exams is challenged by dynamic morphology or variability in patient positioning or motion. Image registration can improve image interpretation and lesion co-localization. We assessed the performance of a con...
Magnetic Resonance Imaging Liver Retrospective Studies Female Aged Adult Male Middle Aged Humans Neural Networks, Computer Algorithms
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Simulation of hyperelastic materials in real-time using deep learning.

Medical image analysis Oct 2, 2019
The finite element method (FEM) is among the most commonly used numerical methods for solving engineering problems. Due to its computational cost, various ideas have been introduced to reduce computation times, such as domain decomposition, parallel ...
Humans Computer Simulation Tomography, X-Ray Computed Datasets as Topic Finite Element Analysis Biomechanical Phenomena Elastic Modulus Deep Learning Liver
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GoogLeNet-Based Ensemble FCNet Classifier for Focal Liver Lesion Diagnosis.

IEEE journal of biomedical and health informatics Sep 20, 2019
Transfer learning techniques are recently preferred for the computer aided diagnosis (CAD) of variety of diseases, as it makes the classification feasible from limited training dataset. In this work, an ensemble FCNet classifier is proposed to classi...
Humans Radiographic Image Interpretation, Computer-Assisted Tomography, X-Ray Computed Neural Networks, Computer Liver Neoplasms Algorithms Liver
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Detection and Monitoring of Thermal Lesions Induced by Microwave Ablation Using Ultrasound Imaging and Convolutional Neural Networks.

IEEE journal of biomedical and health informatics Sep 6, 2019
Microwave ablation (MWA) for cancer treatment is frequently monitored by ultrasound (US) B-mode imaging in the clinic, which often fails due to the low intrinsic contrast between the thermal lesion and normal tissue. Deep learning, especially convolu...
Microwaves Radiation Injuries Radiofrequency Ablation Liver Surgery, Computer-Assisted Image Interpretation, Computer-Assisted Swine Deep Learning Neural Networks, Computer Ultrasonography Animals
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Radiomics machine-learning signature for diagnosis of hepatocellular carcinoma in cirrhotic patients with indeterminate liver nodules.

European radiology Aug 23, 2019
PURPOSE: To enhance clinician's decision-making by diagnosing hepatocellular carcinoma (HCC) in cirrhotic patients with indeterminate liver nodules using quantitative imaging features extracted from triphasic CT scans.
Aged Contrast Media Retrospective Studies Male Liver Neoplasms Humans Tomography, X-Ray Computed Liver Middle Aged Carcinoma, Hepatocellular Female Artificial Intelligence Diagnosis, Differential Liver Cirrhosis Machine Learning
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