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To search for items containing ALL of the words you enter, separate the words with the keyword "AND."
Example: Searching on brain AND tumor will ensure that your results contain both words.
To search for items containing ANY of the words you enter, separate them with the keyword "OR."
Example: Searching on brain OR tumor returns articles containing EITHER of the words "brain" or "tumor." Searching on brain tumor also returns articles containing either of the words "brain" or "tumor." If the words appear together, they will be ranked above the results that contain only one of the words.
To search for EXACT PHRASES, type quotes around the phrase.
Example: Using search terms "brain tumor" AND imaging returns any articles containing the phrase "brain tumor" and the word imaging.
Search Rank Order
By default, search results are displayed in date order, with newer items appearing toward the top of the list of results. Your search results can be sorted in rank order by selecting the "Sort by rank" link at the top of the page. Rank is determined in part by how close the search terms appear toward the top of the page and also by the frequency with which the terms appear on the page.
![Overview of the study design. (A) The fully automated deep learning framework was developed to estimate body composition (BC) (defined as subcutaneous adipose tissue [SAT] in liters; visceral adipose tissue [VAT] in liters; skeletal muscle [SM] in liters; SM fat fraction [SMFF] as a percentage; and intramuscular adipose tissue [IMAT] in deciliters) from MRI. The fully automated framework comprised one model (model 1) to quantify different BC measures (SAT, VAT, SM, SMFF, and IMAT) as three-dimensional (3D) measures from whole-body MRI scans. The second model (model 2) was trained to identify standardized anatomic landmarks along the craniocaudal body axis (z coordinate field), which allowed for subdividing the whole-body measures into different subregions typically examined on clinical routine MRI scans (chest, abdomen, and pelvis). (B) BC was quantified from whole-body MRI in over 66,000 individuals from two large population-based cohort studies, the UK Biobank (UKB) (36,317 individuals) and the German National Cohort (NAKO) (30,291 individuals). Bar graphs show age distribution by sex and cohort. BMI = body mass index. (C) After the performance assessment of the fully automated framework, the change in BC measures, distributions, and profiles across age decades were investigated. Age-, sex-, and height-adjusted body composition reference curves were calculated and made publicly available in a web-based z-score calculator (https://circ-ml.github.io).](https://img.auntminnieeurope.com/mindful/smg/workspaces/default/uploads/2026/05/body-comp.XgAjTfPj1W.jpg?auto=format%2Ccompress&dpr=2&fit=crop&h=167&q=70&w=250)
