4.7 Article

Automated imaging-based abdominal organ segmentation and quality control in 20,000 participants of the UK Biobank and German National Cohort Studies

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Radiology, Nuclear Medicine & Medical Imaging

Deep Learning-Based Automated Abdominal Organ Segmentation in the UK Biobank and German National Cohort Magnetic Resonance Imaging Studies

Turkay Kart et al.

Summary: The study aimed to train and evaluate deep learning models for automated segmentation of abdominal organs in whole-body MR images from UKBB and GNC datasets, showing high qualitative and quantitative accuracy in over 90% of the data sets. The results suggest that automated segmentation using deep learning models can be a reliable method for analyzing MR data sets.

INVESTIGATIVE RADIOLOGY (2021)

Article Biochemical Research Methods

nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation

Fabian Isensee et al.

Summary: nnU-Net is a deep learning-based image segmentation method that automatically configures itself for diverse biological and medical image segmentation tasks, offering state-of-the-art performance as an out-of-the-box tool.

NATURE METHODS (2021)

Article Biology

Genetic architecture of 11 organ traits derived from abdominal MRI using deep learning

Yi Liu et al.

Summary: The study used deep learning to analyze MRI data, quantify the volume, fat, and iron content of organs and tissues, and demonstrated that these imaging-derived features can reflect health status. The research found that these traits have a substantial heritable component and identified multiple significant genetic associations related to liver traits.
Proceedings Paper Computer Science, Artificial Intelligence

Pancreas Volumetry in UK Biobank: Comparison of Models and Inference at Scale

James Owler et al.

Summary: The study accurately measured pancreas volume using whole-body 3D MRI images and deep learning technology, comparing different model architectures. Based on the results, this is the largest pancreas volumetry study to date and the first to utilize whole-body MRI images for measuring pancreas volume.

MEDICAL IMAGE UNDERSTANDING AND ANALYSIS (MIUA 2021) (2021)

Article Multidisciplinary Sciences

Large-scale Quality Control of Cardiac Imaging in Population Studies: Application to UK Biobank

Giacomo Tarroni et al.

SCIENTIFIC REPORTS (2020)

Review Multidisciplinary Sciences

The UK Biobank imaging enhancement of 100,000 participants:rationale, data collection, management and future directions

Thomas J. Littlejohns et al.

NATURE COMMUNICATIONS (2020)

Article Biochemistry & Molecular Biology

A population-based phenome-wide association study of cardiac and aortic structure and function

Wenjia Bai et al.

NATURE MEDICINE (2020)

Article Multidisciplinary Sciences

Kidney segmentation in neck-to-knee body MRI of 40,000 UK Biobank participants

Taro Langner et al.

SCIENTIFIC REPORTS (2020)

Article Computer Science, Artificial Intelligence

Fully Automated and Standardized Segmentation of Adipose Tissue Compartments via Deep Learning in 3D Whole-Body MRI of Epidemiologic Cohort Studies

Thomas Kuestner et al.

RADIOLOGY-ARTIFICIAL INTELLIGENCE (2020)

Review Radiology, Nuclear Medicine & Medical Imaging

Machine learning in whole-body MRI: experiences and challenges from an applied study using multicentre data

I Lavdas et al.

CLINICAL RADIOLOGY (2019)

Article Cardiac & Cardiovascular Systems

Automated quality control in image segmentation: application to the UK Biobank cardiovascular magnetic resonance imaging study

Robert Robinson et al.

JOURNAL OF CARDIOVASCULAR MAGNETIC RESONANCE (2019)

Review Neurosciences

Mindcontrol: A web application for brain segmentation quality control

Anisha Keshavan et al.

NEUROIMAGE (2018)

Article Mathematical & Computational Biology

Pipeline for Analyzing Lesions After Stroke (PALS)

Kaori L. Ito et al.

FRONTIERS IN NEUROINFORMATICS (2018)

Article Radiology, Nuclear Medicine & Medical Imaging

Population-based imaging biobanks as source of big data

Sergios Gatidis et al.

RADIOLOGIA MEDICA (2017)

Article Oncology

Computational Radiomics System to Decode the Radiographic Phenotype

Joost J. M. van Griethuysen et al.

CANCER RESEARCH (2017)

Article Multidisciplinary Sciences

Feasibility of MR-Based Body Composition Analysis in Large Scale Population Studies

Janne West et al.

PLOS ONE (2016)

Article Radiology, Nuclear Medicine & Medical Imaging

Whole-Body MR Imaging in the German National Cohort:Rationale, Design, and Technical Background

Fabian Bamberg et al.

RADIOLOGY (2015)