AIMC Topic: Liver

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Feature-guided deep learning reduces signal loss and increases lesion CNR in diffusion-weighted imaging of the liver.

Zeitschrift fur medizinische Physik
PURPOSE: This research aims to develop a feature-guided deep learning approach and compare it with an optimized conventional post-processing algorithm in order to enhance the image quality of diffusion-weighted liver images and, in particular, to red...

Preoperative planning and intraoperative real-time navigation with indocyanine green fluorescence in robotic liver surgery.

Langenbeck's archives of surgery
PURPOSE: We aimed at exploring indocyanine green (ICG) fluorescence wide spectrum of applications in hepatobiliary surgery as can result particularly useful in robotic liver resections (RLR) in order to overcome some technical limitations, increasing...

Deep Learning for Inference of Hepatic Proton Density Fat Fraction From T1-Weighted In-Phase and Opposed-Phase MRI: Retrospective Analysis of Population-Based Trial Data.

AJR. American journal of roentgenology
The confounder-corrected chemical shift-encoded MRI (CSE-MRI) sequence used to determine proton density fat fraction (PDFF) for hepatic fat quantification is not widely available. As an alternative, hepatic fat can be assessed by a two-point Dixon m...

Transfer-learning is a key ingredient to fast deep learning-based 4D liver MRI reconstruction.

Scientific reports
Time-resolved volumetric magnetic resonance imaging (4D MRI) could be used to address organ motion in image-guided interventions like tumor ablation. Current 4D reconstruction techniques are unsuitable for most interventional settings because they ar...

Predicting the Mitochondrial Toxicity of Small Molecules: Insights from Mechanistic Assays and Cell Painting Data.

Chemical research in toxicology
Mitochondrial toxicity is a significant concern in the drug discovery process, as compounds that disrupt the function of these organelles can lead to serious side effects, including liver injury and cardiotoxicity. Different in vitro assays exist to ...

AutoFibroNet: A deep learning and multi-photon microscopy-derived automated network for liver fibrosis quantification in MAFLD.

Alimentary pharmacology & therapeutics
BACKGROUND: Liver fibrosis is the strongest histological risk factor for liver-related complications and mortality in metabolic dysfunction-associated fatty liver disease (MAFLD). Second harmonic generation/two-photon excitation fluorescence (SHG/TPE...

Deep learning-based affine medical image registration for multimodal minimal-invasive image-guided interventions - A comparative study on generalizability.

Zeitschrift fur medizinische Physik
Multimodal image registration is applied in medical image analysis as it allows the integration of complementary data from multiple imaging modalities. In recent years, various neural network-based approaches for medical image registration have been ...

Robotic versus laparoscopic versus open major hepatectomy - an analysis of costs and postoperative outcomes in a single-center setting.

Langenbeck's archives of surgery
PURPOSE: In the era of minimal-invasive surgery, the introduction of robotic liver surgery (RS) was accompanied by concerns about the increased financial expenses of the robotic technique in comparison to the established laparoscopic (LS) and convent...