Image processing based wound assessment system for patients with diabetes using six classification algorithms

Kumar, Chiranjeev; Malathy, V.

doi:10.1109/iceeot.2016.7754782

Cited by 5 publications

(3 citation statements)

References 9 publications

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“…With regards to skin burn images, other types of medical images also require segmentation in order to achieve an accurate classification. Past studies that had developed segmentation algorithms to segment their medical images for the purpose of classification were, for example, assessment of skin lesions [10], [12], [13], breast cancer [14], [15], lung cancer [16]- [18], diabetic foot ulcers [19], [20] and brain tumor [21]- [23].…”

Section: Introductionmentioning

confidence: 99%

A Comparative Study of Segmentation Algorithms in the Classification of Human Skin Burn Depth

Kuan

Chua

Safawi

et al. 2020

Int. J. Adv. Sci. Eng. Inf. Technol.

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A correct first assessment of a skin burn depth is essential as it determines a correct first burn treatment provided to the patients. The objective of this paper is to conduct a comparative study of the different segmentation algorithms for the classification of different burn depths. Eight different hybrid segmentation algorithms were studied on a skin burn dataset comprising skin burn images categorized into three burn classes by medical experts; superficial partial thickness burn (SPTB), deep partial thickness burn (DPTB) and full thickness burn (FTB). Different sequences of the algorithm were experimented as each algorithm was able to segment differently, leading to different segmentation in the final output. The performance of the segmentation algorithms was evaluated by calculating the number of correctly segmented images for each burn depth. The empirical results showed that the segmentation algorithm that was able to segment most of the burn depths had achieved 40.24%, 60.42% and 6.25% of correctly segmented image for SPTB, DPTB and FTB respectively. Most of the segmentation algorithms could not segment well for FTB images because of the different nature of the burn wounds as some of the FTB images contained dark brown and black colors. It can be concluded that a good segmentation algorithm is required to ensure that the representative features of each burn depth can be extracted to contribute to higher accuracy of classification of skin burn depth.

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Section: Introductionmentioning

confidence: 99%

A Comparative Study of Segmentation Algorithms in the Classification of Human Skin Burn Depth

Kuan

Chua

Safawi

et al. 2020

Int. J. Adv. Sci. Eng. Inf. Technol.

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“…This method serves the purpose of true border extraction in the domain of relevant to skin images affected by wounds. The radial search method is semiautomatic and thus needs manual initialization of search origin (Kumar & Malathy, 2016). The evolution methods completely depend on the initial curve which has to be pre-delineated either manually or by a well-designed algorithm (Wang et al, 2015).…”

Section: Related Workmentioning

confidence: 99%

“…Since early ulcer diagnosis has proven to be laborious using existing dermatological practices, non-invasive ulcer assessment is possible by using digital images (Kumar & Malathy, 2016).…”

mentioning

confidence: 99%

Development of a fast and accurate method for the segmentation of diabetic foot ulcer images

Mwawado¹

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Globally, Diabetic Foot Ulcers (DFUs) are among the major sources of morbidity and death among people diagnosed with diabetes. Diabetic foot ulcers are the leading diabetes-related complications that result in non-traumatic lower-limb amputations among these patients. Being a serious health concern, DFUs present a significant therapeutic challenge to specialists, particularly in countries with limited health resources and where the vast majority of patients are admitted to healthcare facilities when the ulcers have fully advanced. Clinical practices currently employed to assess and treat DFU are mostly based on the vigilance of both the patient and clinician. These practices have been proved to experience major limitations which include less accurate assessment methods, time-consuming diagnostic procedures, and relatively high treatment costs. Digital image processing is thus a potential solution to address issues of the inaccuracy of visual assessment as well as minimizing consecutive patient visits to the clinics. Image processing techniques for ulcer assessment have thus been a center of study in various works of literature. In the available works of literature, these methods include measuring the ulcer area as well as using a medical digital photography scheme. The most notable drawbacks of such approaches include system complexity, complex-exhaustive training phases, and high computational cost. Inspired by the weaknesses of the existing techniques, this study proposes a segmentation method that incorporates a hybrid diffusion-steered functional derived from the Total variation and the Perona-Malik diffusivities, which have been reported that they can effectively capture semantic features in images. Empirical results from the experiments that were carried out in the MATLAB environment show that the proposed method generates clearer segmented outputs with higher perceptual and objective qualities. More importantly, the proposed method offers lower computational times—an advantage that gives more insights into the possible application of the method in time-sensitive tasks.

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Measuring Decubitus Wounds Using Augmented Reality Glasses - A User Interface Study

Bauer

Leidner

Willhauk

et al. 2022

Communications in Computer and Information Science

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Image processing based wound assessment system for patients with diabetes using six classification algorithms

Cited by 5 publications

References 9 publications

A Comparative Study of Segmentation Algorithms in the Classification of Human Skin Burn Depth

A Comparative Study of Segmentation Algorithms in the Classification of Human Skin Burn Depth

Development of a fast and accurate method for the segmentation of diabetic foot ulcer images

Measuring Decubitus Wounds Using Augmented Reality Glasses - A User Interface Study

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