Skeletal Muscle Mass Estimation from Lower Leg Digital Images Using Machine Learning

Tomohiko Nagano; Hiroo Matsuse; Yoshio Takano; Ryuki Hashida; Junichi Kawakami; Osamu Taguchi; Kenta Murotani; Shigeaki MATSUO; Koji Hiraoka

doi:10.2490/prm.20260025

January 1, 2026Progress in Rehabilitation MedicineOpen Access

Skeletal Muscle Mass Estimation from Lower Leg Digital Images Using Machine Learning

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Key Points

The study aims to develop a convolutional neural network for estimating skeletal muscle mass from lower leg images.
Developed a convolutional neural network model
Evaluated predictive performance using digital images of lower legs
The CNN model demonstrated a significant accuracy in estimating skeletal muscle index
Findings indicate potential improvements in muscle mass diagnostics with machine learning

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Implication

Evaluates machine learning approach for estimating skeletal muscle mass from images, suggesting improved diagnostics.

Abstract

Objectives: In the current study, a convolutional neural network (CNN) model for estimating the skeletal muscle index (SMI) from lower leg digital images was developed, and its predictive performance was evaluated.

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Cite This Study

Nagano et al. (2026) studied this question.

synapsesocial.com/papers/6a11439848a409a3a49de5f2 https://doi.org/10.2490/prm.20260025

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Skeletal Muscle Mass Estimation from Lower Leg Digital Images Using Machine Learning

Key Points

Ask about this paper

Implication

Abstract

Discussion

Cite This Study

Skeletal Muscle Mass Estimation from Lower Leg Digital Images Using Machine Learning

Key Points

Ask about this paper

Implication

Abstract

Discussion

Cite This Study

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