Local MRI-based measures of thigh adipose tissue derived from fully automated deep convolutional neural network-based segmentation show a comparable responsiveness to bidirectional change in body weight as from quality controlled manual segmentation.

Jana Kemnitz; Eva Steidle-Kloc; Wolfgang Wirth; David Fuerst; Anna Wisser; Sebastian Eder; Felix Eckstein

doi:10.1016/j.aanat.2021.151866

Local MRI-based measures of thigh adipose tissue derived from fully automated deep convolutional neural network-based segmentation show a comparable responsiveness to bidirectional change in body weight as from quality controlled manual segmentation.

Jana Kemnitz^* (Erstautor/-in), Eva Steidle-Kloc (Co-Autor/-in), Wolfgang Wirth (Co-Autor/-in), David Fuerst (Co-Autor/-in), Anna Wisser (Co-Autor/-in), Sebastian Eder (Co-Autor/-in), Felix Eckstein (Letztautor/-in)

^*Korrespondierende/r Autor/-in für diese Arbeit

Publikation: Beitrag in Fachzeitschrift › Originalarbeit (Zeitschrift) › Begutachtung

3 Quellenangaben (Web of Science)

Originalsprache	Englisch
Seiten (von - bis)	151866
Fachzeitschrift	ANNALS OF ANATOMY-ANATOMISCHER ANZEIGER
Jahrgang	240
DOIs	https://doi.org/10.1016/j.aanat.2021.151866
Publikationsstatus	Veröffentlicht - 2022

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10.1016/j.aanat.2021.151866

Relationship of muscle strength with pain and function in knee osteoarthritis - a matter of the "brain" or the "body"?
Steidle-Kloc, E. (Leitende(r) Forscher/-in)
1/08/16 → 1/08/18
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Kemnitz, J., Steidle-Kloc, E., Wirth, W., Fuerst, D., Wisser, A., Eder, S., & Eckstein, F. (2022). Local MRI-based measures of thigh adipose tissue derived from fully automated deep convolutional neural network-based segmentation show a comparable responsiveness to bidirectional change in body weight as from quality controlled manual segmentation. ANNALS OF ANATOMY-ANATOMISCHER ANZEIGER , 240, 151866. https://doi.org/10.1016/j.aanat.2021.151866

Kemnitz, Jana ; Steidle-Kloc, Eva ; Wirth, Wolfgang et al. / Local MRI-based measures of thigh adipose tissue derived from fully automated deep convolutional neural network-based segmentation show a comparable responsiveness to bidirectional change in body weight as from quality controlled manual segmentation. in: ANNALS OF ANATOMY-ANATOMISCHER ANZEIGER 2022 ; Jahrgang 240. S. 151866.

@article{d1601d100ba1436890281b9becf5f12e,

title = "Local MRI-based measures of thigh adipose tissue derived from fully automated deep convolutional neural network-based segmentation show a comparable responsiveness to bidirectional change in body weight as from quality controlled manual segmentation.",

keywords = "OSTEOARTHRITIS INITIATIVE OAI, INTERMUSCULAR FAT VOLUME, CROSS-SECTIONAL AREA, MUSCLE, STRENGTH, KNEES, WOMEN",

author = "Jana Kemnitz and Eva Steidle-Kloc and Wolfgang Wirth and David Fuerst and Anna Wisser and Sebastian Eder and Felix Eckstein",

note = "all but Eder: Department of Imaging and Functional Musculoskeletal Research, Institute of Anatomy and Cell Biology, Paracelsus Medical University Salzburg & Nuremberg, Salzburg, Austria.; Eder: First Department of Medicine, Paracelsus Medical University, Salzburg, Austria.",

year = "2022",

doi = "10.1016/j.aanat.2021.151866",

language = "English",

volume = "240",

pages = "151866",

journal = "ANNALS OF ANATOMY-ANATOMISCHER ANZEIGER ",

issn = "0940-9602",

publisher = "Elsevier ",

}

Kemnitz, J , Steidle-Kloc, E , Wirth, W, Fuerst, D, Wisser, A, Eder, S & Eckstein, F 2022, 'Local MRI-based measures of thigh adipose tissue derived from fully automated deep convolutional neural network-based segmentation show a comparable responsiveness to bidirectional change in body weight as from quality controlled manual segmentation.', ANNALS OF ANATOMY-ANATOMISCHER ANZEIGER , Jg. 240, S. 151866. https://doi.org/10.1016/j.aanat.2021.151866

Local MRI-based measures of thigh adipose tissue derived from fully automated deep convolutional neural network-based segmentation show a comparable responsiveness to bidirectional change in body weight as from quality controlled manual segmentation. / Kemnitz, Jana (Erstautor/-in); Steidle-Kloc, Eva (Co-Autor/-in); Wirth, Wolfgang (Co-Autor/-in) et al.
in: ANNALS OF ANATOMY-ANATOMISCHER ANZEIGER , Jahrgang 240, 2022, S. 151866.

Publikation: Beitrag in Fachzeitschrift › Originalarbeit (Zeitschrift) › Begutachtung

TY - JOUR

T1 - Local MRI-based measures of thigh adipose tissue derived from fully automated deep convolutional neural network-based segmentation show a comparable responsiveness to bidirectional change in body weight as from quality controlled manual segmentation.

AU - Kemnitz, Jana

AU - Steidle-Kloc, Eva

AU - Wirth, Wolfgang

AU - Fuerst, David

AU - Wisser, Anna

AU - Eder, Sebastian

AU - Eckstein, Felix

N1 - all but Eder: Department of Imaging and Functional Musculoskeletal Research, Institute of Anatomy and Cell Biology, Paracelsus Medical University Salzburg & Nuremberg, Salzburg, Austria.; Eder: First Department of Medicine, Paracelsus Medical University, Salzburg, Austria.

PY - 2022

Y1 - 2022

KW - OSTEOARTHRITIS INITIATIVE OAI

KW - INTERMUSCULAR FAT VOLUME

KW - CROSS-SECTIONAL AREA

KW - MUSCLE

KW - STRENGTH

KW - KNEES

KW - WOMEN

U2 - 10.1016/j.aanat.2021.151866

DO - 10.1016/j.aanat.2021.151866

M3 - Original Article (Journal)

C2 - 34823014

SN - 0940-9602

VL - 240

SP - 151866

JO - ANNALS OF ANATOMY-ANATOMISCHER ANZEIGER

JF - ANNALS OF ANATOMY-ANATOMISCHER ANZEIGER

ER -

Kemnitz J , Steidle-Kloc E , Wirth W, Fuerst D, Wisser A, Eder S et al. Local MRI-based measures of thigh adipose tissue derived from fully automated deep convolutional neural network-based segmentation show a comparable responsiveness to bidirectional change in body weight as from quality controlled manual segmentation. ANNALS OF ANATOMY-ANATOMISCHER ANZEIGER . 2022;240:151866. doi: 10.1016/j.aanat.2021.151866

Local MRI-based measures of thigh adipose tissue derived from fully automated deep convolutional neural network-based segmentation show a comparable responsiveness to bidirectional change in body weight as from quality controlled manual segmentation.

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Relationship of muscle strength with pain and function in knee osteoarthritis - a matter of the "brain" or the "body"?

Dieses zitieren