Pooled two-cohort MRI body composition phenotyping with open-source deep learning.

Mertens CJ, Häntze H, Ziegelmayer S, Kather JN, Truhn D, Kim SH, Busch F, Weller D, Wiestler B, Graf M, Bamberg F, Schlett CL, Weiss JB, Ringhof S, Can E, Schulz-Menger J, Niendorf T, Lammert J, Molwitz I, Kader A, Hering A, Meddeb A, Nawabi J, Schulze MB, Keil T, Willich SN, Krist L, Hadamitzky M, Hannemann A, Bassermann F, Rueckert D, Pischon T, Hapfelmeier A, Makowski MR, Bressem KK, Adams LC

Open source

DOI: 10.1038/s43856-026-01888-w
Published: 2026 Aug 29
Container: Communications medicine
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1038/s43856-026-01888-w,
  title = {Pooled two-cohort MRI body composition phenotyping with open-source deep learning.},
  author = {Mertens CJ and Häntze H and Ziegelmayer S and Kather JN and Truhn D and Kim SH and Busch F and Weller D and Wiestler B and Graf M and Bamberg F and Schlett CL and Weiss JB and Ringhof S and Can E and Schulz-Menger J and Niendorf T and Lammert J and Molwitz I and Kader A and Hering A and Meddeb A and Nawabi J and Schulze MB and Keil T and Willich SN and Krist L and Hadamitzky M and Hannemann A and Bassermann F and Rueckert D and Pischon T and Hapfelmeier A and Makowski MR and Bressem KK and Adams LC},
  year = {2026},
  journal = {Communications medicine},
  doi = {10.1038/s43856-026-01888-w},
  url = {https://doi.org/10.1038/s43856-026-01888-w}
}

RIS

TY  - JOUR
TI  - Pooled two-cohort MRI body composition phenotyping with open-source deep learning.
AU  - Mertens CJ
AU  - Häntze H
AU  - Ziegelmayer S
AU  - Kather JN
AU  - Truhn D
AU  - Kim SH
AU  - Busch F
AU  - Weller D
AU  - Wiestler B
AU  - Graf M
AU  - Bamberg F
AU  - Schlett CL
AU  - Weiss JB
AU  - Ringhof S
AU  - Can E
AU  - Schulz-Menger J
AU  - Niendorf T
AU  - Lammert J
AU  - Molwitz I
AU  - Kader A
AU  - Hering A
AU  - Meddeb A
AU  - Nawabi J
AU  - Schulze MB
AU  - Keil T
AU  - Willich SN
AU  - Krist L
AU  - Hadamitzky M
AU  - Hannemann A
AU  - Bassermann F
AU  - Rueckert D
AU  - Pischon T
AU  - Hapfelmeier A
AU  - Makowski MR
AU  - Bressem KK
AU  - Adams LC
PY  - 2026
JO  - Communications medicine
DO  - 10.1038/s43856-026-01888-w
UR  - https://doi.org/10.1038/s43856-026-01888-w
ER  -

APA

CJ, M., H, H., S, Z., JN, K., D, T., SH, K., F, B., D, W., B, W., M, G., F, B., CL, S., JB, W., S, R., E, C., J, S., T, N., J, L., I, M., A, K., A, H., A, M., J, N., MB, S., T, K., SN, W., L, K., M, H., A, H., F, B., D, R., T, P., A, H., MR, M., KK, B., & LC, A. (2026). Pooled two-cohort MRI body composition phenotyping with open-source deep learning.. Communications medicine. https://doi.org/10.1038/s43856-026-01888-w

Source records

pubmed · retrieved 2026-09-26T10:13:00.021Z
europe-pmc · retrieved 2026-09-26T10:13:00.047Z
doaj · retrieved 2026-09-26T10:13:00.015Z