AIMC Topic: Liver

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Robot-assisted liver resection: the real benefit so far.

Langenbeck's archives of surgery
BACKGROUND: Minimally invasive liver resection is associated with lower perioperative morbidity and shorter hospital stay. However, the added benefit of the robotic platform over conventional laparoscopy is a matter of ongoing investigation.

Using deep learning to predict abdominal age from liver and pancreas magnetic resonance images.

Nature communications
With age, the prevalence of diseases such as fatty liver disease, cirrhosis, and type two diabetes increases. Approaches to both predict abdominal age and identify risk factors for accelerated abdominal age may ultimately lead to advances that will d...

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

Medical physics
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...

Deep Learning-Based Assessment of Functional Liver Capacity Using Gadoxetic Acid-Enhanced Hepatobiliary Phase MRI.

Korean journal of radiology
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...

Multi-Scale Attention Convolutional Network for Masson Stained Bile Duct Segmentation from Liver Pathology Images.

Sensors (Basel, Switzerland)
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...

Large scale simulation of labeled intraoperative scenes in unity.

International journal of computer assisted radiology and surgery
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.

A Lightweight Convolutional Neural Network Model for Liver Segmentation in Medical Diagnosis.

Computational intelligence and neuroscience
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...

Advancements of Artificial Intelligence in Liver-Associated Diseases and Surgery.

Medicina (Kaunas, Lithuania)
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...

Diagnosis of significant liver fibrosis in patients with chronic hepatitis B using a deep learning-based data integration network.

Hepatology international
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...

Robot-Assisted Liver Resection and Cholecystectomy Using Indocyanine-Green for Intrahepatic Cholangiocarcinoma, in a Very Rare Anatomical Anomaly of 'Bipartite Liver'.

Surgical innovation
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 ...