Fully Automated Wound Tissue Segmentation Using Deep Learning on Mobile Devices: Cohort Study.

ABSTRACT:

Background

Composition of tissue types within a wound is a useful indicator of its healing progression. Tissue composition is clinically used in wound healing tools (eg, Bates-Jensen Wound Assessment Tool) to assess risk and recommend treatment. However, wound tissue identification and the estimation of their relative composition is highly subjective. Consequently, incorrect assessments could be reported, leading to downstream impacts including inappropriate dressing selection, failure to identify wounds at risk of not healing, or failure to make appropriate referrals to specialists.

Objective

This study aimed to measure inter- and intrarater variability in manual tissue segmentation and quantification among a cohort of wound care clinicians and determine if an objective ass

SUBMITTER: Ramachandram D 

PROVIDER: S-EPMC9077502 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature