AIMC Topic: Liver

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Medical lesion segmentation by combining multimodal images with modality weighted UNet.

Medical physics Apr 7, 2022
PURPOSE: Automatic segmentation of medical lesions is a prerequisite for efficient clinic analysis. Segmentation algorithms for multimodal medical images have received much attention in recent years. Different strategies for multimodal combination (o...
Humans Neural Networks, Computer Image Processing, Computer-Assisted Abdomen Liver Algorithms Tomography, X-Ray Computed
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Deep Learning-Based Assessment of Functional Liver Capacity Using Gadoxetic Acid-Enhanced Hepatobiliary Phase MRI.

Korean journal of radiology Apr 4, 2022
OBJECTIVE: We aimed to develop and test a deep learning algorithm (DLA) for fully automated measurement of the volume and signal intensity (SI) of the liver and spleen using gadoxetic acid-enhanced hepatobiliary phase (HBP)-magnetic resonance imaging...
Humans Liver Gadolinium DTPA Adult Male Liver Neoplasms Contrast Media Middle Aged Magnetic Resonance Imaging Retrospective Studies Deep Learning Female
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Multi-Scale Attention Convolutional Network for Masson Stained Bile Duct Segmentation from Liver Pathology Images.

Sensors (Basel, Switzerland) Mar 31, 2022
In clinical practice, the Ishak Score system would be adopted to perform the evaluation of the grading and staging of hepatitis according to whether portal areas have fibrous expansion, bridging with other portal areas, or bridging with central veins...
Neural Networks, Computer Image Processing, Computer-Assisted Liver Bile Ducts
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Large scale simulation of labeled intraoperative scenes in unity.

International journal of computer assisted radiology and surgery Mar 30, 2022
PURPOSE: The use of synthetic or simulated data has the potential to greatly improve the availability and volume of training data for image guided surgery and other medical applications, where access to real-life training data is limited.
Humans Computer Simulation Deep Learning Image Processing, Computer-Assisted Liver Surgery, Computer-Assisted
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A Lightweight Convolutional Neural Network Model for Liver Segmentation in Medical Diagnosis.

Computational intelligence and neuroscience Mar 30, 2022
Liver segmentation and recognition from computed tomography (CT) images is a warm topic in image processing which is helpful for doctors and practitioners. Currently, many deep learning methods are used for liver segmentation that takes a long time t...
Liver Tomography, X-Ray Computed Neural Networks, Computer Image Processing, Computer-Assisted Algorithms
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Advancements of Artificial Intelligence in Liver-Associated Diseases and Surgery.

Medicina (Kaunas, Lithuania) Mar 22, 2022
The advancement of artificial intelligence (AI) based technologies in medicine is progressing rapidly, but the majority of its real-world applications has not been implemented. The establishment of an accurate diagnosis with treatment has now transi...
Mass Screening Liver PubMed Humans Artificial Intelligence
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Diagnosis of significant liver fibrosis in patients with chronic hepatitis B using a deep learning-based data integration network.

Hepatology international Mar 21, 2022
BACKGROUND AND AIMS: Chronic hepatitis B virus (CHB) infection remains a major global health burden and the non-invasive and accurate diagnosis of significant liver fibrosis (≥ F2) in CHB patients is clinically very important. This study aimed to ass...
Elasticity Imaging Techniques ROC Curve Liver Cirrhosis Humans Biopsy Liver Deep Learning Hepatitis B, Chronic
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Robot-Assisted Liver Resection and Cholecystectomy Using Indocyanine-Green for Intrahepatic Cholangiocarcinoma, in a Very Rare Anatomical Anomaly of 'Bipartite Liver'.

Surgical innovation Mar 20, 2022
Robotic hepatobiliary surgery has significantly developed worldwide with substantial clinical results. Hepatobiliary anatomical anomalies increase the complexity of hepatobiliary resection with a relevant risk of iatrogenic lesions. Among congenital ...
Bile Ducts, Intrahepatic Cholecystectomy Indocyanine Green Hepatectomy Bile Duct Neoplasms Cholangiocarcinoma Liver Robotics Humans
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Characteristics of Computed Tomography Images for Patients with Acute Liver Injury Caused by Sepsis under Deep Learning Algorithm.

Contrast media & molecular imaging Mar 20, 2022
This study was aimed at exploring the application of image segmentation based on full convolutional neural network (FCN) in liver computed tomography (CT) image segmentation and analyzing the clinical features of acute liver injury caused by sepsis. ...
Humans Image Processing, Computer-Assisted Deep Learning Algorithms Sepsis Liver Tomography, X-Ray Computed
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A deep learning framework for automated detection and quantitative assessment of liver trauma.

BMC medical imaging Mar 8, 2022
BACKGROUND: Both early detection and severity assessment of liver trauma are critical for optimal triage and management of trauma patients. Current trauma protocols utilize computed tomography (CT) assessment of injuries in a subjective and qualitati...
Humans Neural Networks, Computer Image Processing, Computer-Assisted Liver Tomography, X-Ray Computed Deep Learning
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