AIMC Topic: Body Composition
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Editorial Comment: The Future Value of Automated CT-Derived Body Composition in Oncologic Patients.
AJR. American journal of roentgenology
Jun 8, 2022
CT-Derived Body Composition Assessment as a Prognostic Tool in Oncologic Patients: From Opportunistic Research to Artificial Intelligence-Based Clinical Implementation.
AJR. American journal of roentgenology
Jun 1, 2022
CT-based body composition measures are well established in research settings as prognostic markers in oncologic patients. Numerous retrospective studies have shown the role of objective measurements extracted from abdominal CT images of skeletal musc...
Deep learning body-composition analysis of clinically acquired CT-scans estimates creatinine excretion with high accuracy in patients and healthy individuals.
Scientific reports
May 30, 2022
Assessment of daily creatinine production and excretion plays a crucial role in the estimation of renal function. Creatinine excretion is estimated by creatinine excretion equations and implicitly in eGFR equations like MDRD and CKD-EPI. These equati...
Automated segmentation of whole-body CT images for body composition analysis in pediatric patients using a deep neural network.
European radiology
May 7, 2022
OBJECTIVES: To develop an automatic segmentation algorithm using a deep neural network with transfer learning applicable to whole-body PET-CT images in children.
Deep learning-based fully automated body composition analysis of thigh CT: comparison with DXA measurement.
European radiology
Apr 18, 2022
OBJECTIVES: To compare volumetric CT with DL-based fully automated segmentation and dual-energy X-ray absorptiometry (DXA) in the measurement of thigh tissue composition.
Clinical practice guideline for body composition assessment based on upper abdominal magnetic resonance images annotated using artificial intelligence.
Chinese medical journal
Mar 20, 2022
Body fat prediction through feature extraction based on anthropometric and laboratory measurements.
PloS one
Feb 22, 2022
Obesity, associated with having excess body fat, is a critical public health problem that can cause serious diseases. Although a range of techniques for body fat estimation have been developed to assess obesity, these typically involve high-cost test...
Agreement of anthropometric and body composition measures predicted from 2D smartphone images and body impedance scales with criterion methods.
Obesity research & clinical practice
Jan 31, 2022
BACKGROUND/OBJECTIVES: Body composition and anthropometry assessment from two-dimensional smartphone images is possible through advancement of computational hardware and artificial intelligence (AI) techniques. This study established agreement of a n...
Artificial neural network model effectively estimates muscle and fat mass using simple demographic and anthropometric measures.
Clinical nutrition (Edinburgh, Scotland)
Nov 24, 2021
BACKGROUND & AIMS: Lean muscle and fat mass in the human body are important indicators of the risk of cardiovascular and metabolic diseases. Techniques such as dual-energy X-ray absorptiometry (DXA) accurately measure body composition, but they are c...
Automated CT-Based Body Composition Analysis: A Golden Opportunity.
Korean journal of radiology
Oct 26, 2021
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