The parameters of muscle ultrasound images reflect the function and state of muscles. They are of great significance to the diagnosis of muscle diseases. Because manual labeling is time-consuming and laborious, the automatic labeling of muscle ultrasound image parameters has become a research topic. In recent years, there have been many methods that apply image processing and deep learning to automatically analyze muscle ultrasound images. However, these methods have limitations, such as being non-automatic, not applicable to images with complex noise, and only being able to measure a single parameter. This paper proposes a fully automatic muscle ultrasound image analysis method based on image segmentation to solve these problems. This meth...
In vivo measurements of muscle architecture (i.e. the spatial arrangement of muscle fascicles) are r...
Musculoskeletal ultrasound imaging can be used to investigate the skeletal muscle structure in terms...
Background: Muscle anatomical cross-sectional area (ACSA) is an important parameter characterizing m...
Objective B-mode ultrasound can be used to image musculoskeletal tissues, but one major bottleneck ...
Ultrasound imaging is a patient-friendly and robust technique for studying physiological and patholo...
Muscle ultrasound imaging is a convenient technique to visualize normal and pathological muscle tiss...
\u3cp\u3e Ultrasonography allows non-invasive and real time-measurement ...
Ultrasonography allows non-invasive and real time-measurement of the visible cross-sectional area (C...
This paper presents an investigation into the feasibility of using deep learning methods for develop...
Ultrasound imaging for medical applications is considered a cost-effective and non-invasive method o...
Existing approaches for automated tracking of fascicle length (FL) and pennation angle (PA) rely on ...
BACKGROUND: With the promotion and development of ultrasound imaging technology, ultrasound is real-...
Fascicle (fiber bundle) orientation and length are useful parameters to infer the force potential of...
Ultrasound (US) is widely used in the clinical diagnosis and treatment of musculoskeletal diseases. ...
In vivo measurements of muscle architecture (i.e. the spatial arrangement of muscle fascicles) are r...
In vivo measurements of muscle architecture (i.e. the spatial arrangement of muscle fascicles) are r...
Musculoskeletal ultrasound imaging can be used to investigate the skeletal muscle structure in terms...
Background: Muscle anatomical cross-sectional area (ACSA) is an important parameter characterizing m...
Objective B-mode ultrasound can be used to image musculoskeletal tissues, but one major bottleneck ...
Ultrasound imaging is a patient-friendly and robust technique for studying physiological and patholo...
Muscle ultrasound imaging is a convenient technique to visualize normal and pathological muscle tiss...
\u3cp\u3e Ultrasonography allows non-invasive and real time-measurement ...
Ultrasonography allows non-invasive and real time-measurement of the visible cross-sectional area (C...
This paper presents an investigation into the feasibility of using deep learning methods for develop...
Ultrasound imaging for medical applications is considered a cost-effective and non-invasive method o...
Existing approaches for automated tracking of fascicle length (FL) and pennation angle (PA) rely on ...
BACKGROUND: With the promotion and development of ultrasound imaging technology, ultrasound is real-...
Fascicle (fiber bundle) orientation and length are useful parameters to infer the force potential of...
Ultrasound (US) is widely used in the clinical diagnosis and treatment of musculoskeletal diseases. ...
In vivo measurements of muscle architecture (i.e. the spatial arrangement of muscle fascicles) are r...
In vivo measurements of muscle architecture (i.e. the spatial arrangement of muscle fascicles) are r...
Musculoskeletal ultrasound imaging can be used to investigate the skeletal muscle structure in terms...
Background: Muscle anatomical cross-sectional area (ACSA) is an important parameter characterizing m...