A Systematic Investigation of Models for Color Image Processing in Wound Size Estimation

Ferreira, Filipe; Pires, Ivan Miguel; Costa, Mónica Isabel Teixeira; Ponciano, Vasco; García, Nuno M.; Zdravevski, Eftim; Chorbev, Ivan; Mihajlov, Martin

doi:10.3390/computers10040043

Cited by 9 publications

(8 citation statements)

References 47 publications

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“…Multiple chances for non-invasive wound assessment exist in clinical as well as non-clinical environments thanks to introduction of mobile devices with significant functionality and processing capacities. Current imaging technologies allow for the collection of quantitative data about the size, structure, &color features of wounds via the use of objective and trustworthy approaches (Filipe 2021). These fast algorithms for analyzing images aid in identifying the characteristics of injuries & tracking their recovery.…”

Section: Literature Reviewmentioning

confidence: 99%

Machine Learning Model for Healing Analysis of Human Injury

D C,

Gadgay,

Bhagyashree

2023

Proceedings of the International Conference on Industrial Engineering and Operations Management

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As more tissues are harmed, wounds progress. Measurements of wound's surface area are taken at regular intervals to determine wound's progress toward healing. Measuring this method is time consuming, and routine evaluation is laborious. In general, wound healing may be broken down into two categories: contact & noncontact. Goal of this job is to make a reliable evaluation of wound's progress toward recovery. Taking pictures of the wound is first step in making a proper diagnosis. Pre-processing the wound picture to decrease noise by using effective filters and effective de-noising algorithms, & then segmenting wound region from wound image. Classifying wound pictures requires efficient classifiers. Chronic wounds are a major problem for many individuals. It's a huge issue in healthcare all throughout the globe. Treatments for chronic wounds involve routine examinations of wound's appearance and shape. This assessment frequently occurs via qualitative observation & manual wound measures. Many groups of scientists are now working on methods to evaluate the clinical progress of chronic wounds. The purpose of this research is to examine how imaging techniques may be used to treat chronic wounds. Research on the use of imaging techniques for chronic wounds is discussed. We evaluate their practicability, accuracy, & dependability. Planimetric approaches, volumetric methods, & tissue categorization make up remaining methods.

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Section: Literature Reviewmentioning

confidence: 99%

Machine Learning Model for Healing Analysis of Human Injury

D C,

Gadgay,

Bhagyashree

2023

Proceedings of the International Conference on Industrial Engineering and Operations Management

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“…Meng et al [44] designed a mathematical model for heterogeneous material based on digital image processing by employing the rectangle function. Ferreira et al [45] approximated the rectangle function to model color image processing. The multi-dimensional fractal approach in this study by using the rectangle function was modified.…”

Section: Related Workmentioning

confidence: 99%

Images Enhancement Based on a New Multi-Dimensional Fractal Created by Rectangular Function

Farhan¹

2022

ETJ

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 New Multi-Dimensional Fractal was introduced to improve and enhance the images.  Different images with low gray levels were enhanced by applying the suggested enhancement model.  The improvement brought a 97% rate in PNSR and a 95% rate in RMSD.Digital image processing is a field that is included in many journals due to its importance and the fact that it facilitates the achievement of many scientific and engineering applications worldwide. This specialization is linked with other disciplines, whether medical, engineering, sports, and others, as it facilitates the completion of applications quickly and efficiently. Researchers have discovered and garnered notice as a promising analytic tool in image processing using the idea of fractal dimension. In this effort, a new Multi-Dimensional Fractal (MDF) in view of the rectangle function was introduced a. As an application, the MDF to improve and enhance the images was employed, and found that there is a connection between MDF and image processing, where the self-similarity property, for example, is one of several features in the new definition. Other properties are discussed in the sequel, including image noise reduction. The presence of noise is responsible for properly operating these images in various applications. Several academics have created and applied a strategy for minimizing noise in features multiplicatively throughout the last several years. The outcomes reveal that the proposed strategy is successful. The method is based on the definition of the rectangular function (the elementary component of all digital signals, videos, and images), where this function indicates a rectangular-formed rhythm that is concentrated at the origin. For example, the suggested process received a rate of 97% for PNSR and 95% for RMSD.

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“…The most critical components approached in this study are the saturation, the inversion and filtering of saturation values, and the performance of segmentation with the threshold. Previously, the authors analyzed several studies to measure the wound area [22]. Therefore, many studies were analyzed to gain insight into the best approaches to measuring the wound area.…”

Section: Related Workmentioning

confidence: 99%

Experimental Study on Wound Area Measurement with Mobile Devices

Ferreira

Pires

Ponciano

et al. 2021

Sensors

Self Cite

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Healthcare treatments might benefit from advances in artificial intelligence and technological equipment such as smartphones and smartwatches. The presence of cameras in these devices with increasingly robust and precise pattern recognition techniques can facilitate the estimation of the wound area and other telemedicine measurements. Currently, telemedicine is vital to the maintenance of the quality of the treatments remotely. This study proposes a method for measuring the wound area with mobile devices. The proposed approach relies on a multi-step process consisting of image capture, conversion to grayscale, blurring, application of a threshold with segmentation, identification of the wound part, dilation and erosion of the detected wound section, identification of accurate data related to the image, and measurement of the wound area. The proposed method was implemented with the OpenCV framework. Thus, it is a solution for healthcare systems by which to investigate and treat people with skin-related diseases. The proof-of-concept was performed with a static dataset of camera images on a desktop computer. After we validated the approach’s feasibility, we implemented the method in a mobile application that allows for communication between patients, caregivers, and healthcare professionals.

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A Systematic Investigation of Models for Color Image Processing in Wound Size Estimation

Cited by 9 publications

References 47 publications

Machine Learning Model for Healing Analysis of Human Injury

Machine Learning Model for Healing Analysis of Human Injury

Images Enhancement Based on a New Multi-Dimensional Fractal Created by Rectangular Function

Experimental Study on Wound Area Measurement with Mobile Devices

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