Deep learning enables accurate soft tissue tendon deformation estimation in vivo via ultrasound imaging.

ABSTRACT: Image-based deformation estimation is an important tool used in a variety of engineering problems, including crack propagation, fracture, and fatigue failure. These tools have been important in biomechanics research where measuring in vitro and in vivo tissue deformations are important for evaluating tissue health and disease progression. However, accurately measuring tissue deformation in vivo is particularly challenging due to limited image signal-to-noise ratio. Therefore, we created a novel deep-learning approach for measuring deformation from a sequence of images collected in vivo called StrainNet. Utilizing a training dataset that incorporates image artifacts, StrainNet was designed to maximize performance in challenging, in vivo settings. Artificially generated image sequences of hu

SUBMITTER: Huff RD 

PROVIDER: S-EPMC11310354 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature