Deep Learning on Wound Segmentation and Classification: A Short Review and Evaluation of Methods Used

Khairul Ezwan Kaswan, Nursuriati Jamil, Rosniza Roslan

Abstract


The abundance of research on wound segmentation suggests that it is significant in order to provide a good analysis and assistance in the medical field. Although there is some relative dearth of wound segmentation on other approaches, this review finds that deep learning is central to the objective of image segmentation. Here, the review informs on the methods that are credible towards wound segmentation, training, classification, validation of datasets, data collection, and evaluation of segmented images. While the literature establishes a clear connection between the segmentation algorithms of the object, therefore this study seeks to find the segmentation algorithm directly applicable to wound assessment.

Keywords


Deep Learning;Wound Segmentation;Classification;Review;wound assessment

Full Text:

PDF


DOI: http://dx.doi.org/10.21533/scjournal.v9i2.192

Refbacks

  • There are currently no refbacks.


Copyright (c) 2021 Khairul Ezwan Kaswan, Nursuriati Jamil, Rosniza Roslan

ISSN 2233 -1859

Digital Object Identifier DOI: 10.21533/scjournal

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License