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https://doi.org/10.1080/00051144.2020.1835108

A robust method for skin cancer diagnosis based on interval analysis

Haohai Zhang ; Communication and Information Engineering Research and Development Center, Institute of Microelectronics of the Chinese Academy of Sciences, Beijing, People’s Republic of China
Zhijun Wang ; Communication and Information Engineering Research and Development Center, Institute of Microelectronics of the Chinese Academy of Sciences, Beijing, People’s Republic of China
Liping Liang ; Communication and Information Engineering Research and Development Center, Institute of Microelectronics of the Chinese Academy of Sciences, Beijing, People’s Republic of China
Fatima Rashid Sheykhahmad ; Young Researchers and Elite Club, Islamic Azad University, Ardabil Branch, Ardabil, Iran


Puni tekst: engleski pdf 2.478 Kb

str. 43-53

preuzimanja: 150

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Sažetak

Early diagnosis of skin cancer from dermoscopy images significantly reduces the mortality due to this cancer. However, several reasons impact the system diagnosis precision. One of the important problems in this process happens during image acquisition. Often, in medical photography, there are some uncertainties like noises and brightness variations, initial digitalization and sampling which affect the image quality. This study presents a new approach for border detection of the cancer area by considering the uncertainties. Interval analysis is utilized to extend the proposed edge detection method and the Hukuhara method is utilized for developing the differentiation formula for edge detection in the interval space. Simulation results are applied to two
different skin cancer atlas and the results are compared with three popular methods by considering two types of noises including Gaussian noise and salt-and-pepper noise. The results showed that the introduced method gives better results than the compared methods.

Ključne riječi

Edge detection; skin cancer; computer-aided diagnosis; uncertainty; interval analysis; Hukuhara difference; Taylor inclusion functions; Gaussian noise

Hrčak ID:

258412

URI

https://hrcak.srce.hr/258412

Datum izdavanja:

30.3.2021.

Posjeta: 667 *