Proceedings ArticleDOI
Analysis of Chronic Wound Images Using Factorization Based Segmentation and Machine Learning Methods
I. Kavitha,S. S. Suganthi,S. Ramakrishnan +2 more
- pp 74-78
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TLDR
The obtained results showed that the proposed segmentation method is capable of converging exactly to irregular wound boundaries and seems to be promising for automatic segmentation and classification of pressure ulcers from leg ulcers aiding in the assessment of wound healing status.Abstract:
In this paper, an attempt has been made to perform an accurate assessment of chronic wound images. Pressure, venous and arterial leg ulcers are considered in this study. For this purpose, chronic wound images acquired by digital camera are enhanced using color correction, noise removal and color homogenization. Enhanced images in Cb color channel of YCbCr color space is used to extract wound bed with factorization based segmentation approach. Binary classification is performed to classify pressure ulcers and leg ulcers. The obtained results showed that the proposed segmentation method is capable of converging exactly to irregular wound boundaries. Hence, the suggested pipeline of processes seems to be promising for automatic segmentation and classification of pressure ulcers from leg ulcers aiding in the assessment of wound healing status.read more
Citations
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Journal ArticleDOI
A superpixel-driven deep learning approach for the analysis of dermatological wounds
Gustavo Blanco,Agma J. M. Traina,Caetano Traina,Paulo Mazzoncini de Azevedo-Marques,Ana Elisa Serafim Jorge,Daniel de Oliveira,Marcos V. N. Bedo +6 more
TL;DR: Results indicate QTDU effectiveness for both tissue segmentation and wounded area quantification tasks, when compared to existing machine-learning approaches, the combination of superpixels and deep learning models outperformed the competitors within strong significant levels.
Literature Review of Machine-Learning Algorithms for Pressure Ulcer Prevention: Challenges and Opportunities
Fernando Ribeiro,Filipe Fidalgo,Arlindo Silva,José Carlos Metrôlho,Osvaldo Santos,Rogério Dionisio +5 more
TL;DR: In this article, a review of machine learning algorithms for risk assessment and management of preventive treatments for pressure ulcers is presented, focusing on the use of machine-learning algorithms that combine information from intrinsic and extrinsic pressure-ulcer predisposing factors to produce recommendations/alerts to healthcare professionals.
Proceedings ArticleDOI
A Two-Phase Learning Approach for the Segmentation of Dermatological Wounds
Wellington S. Silva,Daniel L. Jasbick,Rodrigo Erthal Wilson,Paulo Mazzoncini de Azevedo-Marques,Agma J. M. Traina,Lucio F. D. Santos,Ana Elisa Serafim Jorge,Daniel de Oliveira,Marcos V. N. Bedo +8 more
TL;DR: 2PLA is presented, a method that combines supervised and unsupervised learning strategies for enhancing the segmentation of dermatological wounds and uses the elbow criterion for finding the L1-based DBSCAN threshold as 2PLA second phase parameterization.
Journal ArticleDOI
Application of artificial intelligence methodologies to chronic wound care and management: A scoping review.
TL;DR: The implementation of machine learning algorithms in the diagnosis and management of hard-to-heal wounds is a promising approach for improving the wound care delivered to hospitalized patients, while allowing healthcare professionals to manage their working time more efficiently.
References
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Journal ArticleDOI
Scale-space and edge detection using anisotropic diffusion
Pietro Perona,Jitendra Malik +1 more
TL;DR: A new definition of scale-space is suggested, and a class of algorithms used to realize a diffusion process is introduced, chosen to vary spatially in such a way as to encourage intra Region smoothing rather than interregion smoothing.
Journal ArticleDOI
Wound healing and treating wounds: Differential diagnosis and evaluation of chronic wounds.
TL;DR: The initial steps necessary in evaluating a chronic wound and determining its underlying etiology are described, and the broad differential diagnosis of chronic wounds is reviewed.
Journal ArticleDOI
Binary Tissue Classification on Wound Images With Neural Networks and Bayesian Classifiers
TL;DR: A hybrid approach based on neural networks and Bayesian classifiers is used in the design of a computational system for automatic tissue identification in wound images, obtaining high efficiency rates from a binary cascade approach for tissue identification.
Journal ArticleDOI
Factorization-Based Texture Segmentation
TL;DR: A factorization-based approach that efficiently segments textured images using local spectral histograms to discriminate region appearances in a computationally efficient way and at the same time accurately localizes region boundaries is introduced.
Journal Article
A comparison of wound area measurement techniques: visitrak versus photography.
TL;DR: The photographic method is an accurate alternative to Visitrak for measuring wound area, with no statistical difference in wound area measurement demonstrated during this study.