Отрывок: ) ( ) 2     Method I I I I (3) Function (3) is aware of the edges of the image and tries to preserve the important features of the image. (I – I0)2 Section guarantees a certain degree of validity between the evaluated image and the original image, in which the I evaluated image and the I0 image are noisy. I. Parame- ter is the period of adjustment of the sum of the varia- tions,  and  are the balancing parameters and  is the sum of the points in the image. By minimizi...
Название : Noise reduction and mammography image segmentation optimization with novel QIMFT-SSA method
Авторы/Редакторы : Soewondo, W.
Haji, S.O.
Eftekharian, M.
Dorofeev, A.E.
Jalil, A.T.
Jawad, M.A.
Jabbar, A.H.
Ключевые слова : breast cancer
image segmentation
noise reduction
mammography
QIMFT-SSA
Дата публикации : Апр-2022
Издательство : Самарский национальный исследовательский университет
Библиографическое описание : Soewondo W, Haji SO, Eftekharian M, Marhoon HA, Dorofeev AE, Jalil AT, Jawad MA, Jabbar AH. Noise reduction and mammography image segmentation optimization with novel QIMFT-SSA method. Computer Optics 2022; 46(2): 298-307. DOI: 10.18287/2412-6179-CO-808.
Серия/номер : 46;2
Аннотация : Breast cancer is one of the most dreaded diseases that affects women worldwide and has led to many deaths. Early detection of breast masses prolongs life expectancy in women and hence the development of an automated system for breast masses supports radiologists for accurate diagnosis. In fact, providing an optimal approach with the highest speed and more accuracy is an approach provided by computer-aided design techniques to determine the exact area of breast tumors to use a decision support management system as an assistant to physicians. This study proposes an optimal approach to noise reduction in mammographic images and to identify salt and pepper, Gaussian, Poisson and impact noises to determine the exact mass detection operation after these noise reduction. It therefore offers a method for noise reduction operations called Quantum Inverse MFT Filtering and a method for precision mass segmentation called the Optimal Social Spider Algorithm (SSA) in mammographic images. The hybrid approach called QIMFT-SSA is evaluated in terms of criteria compared to previous methods such as peak Signal-to-Noise Ratio (PSNR) and Mean-Squared Error (MSE) in noise reduction and accuracy of detection for mass area recognition. The proposed method presents more performance of noise reduction and segmentation in comparison to state-of-arts methods. supported the work.
URI (Унифицированный идентификатор ресурса) : 10.18287/2412-6179-CO-808
http://repo.ssau.ru/handle/Zhurnal-Komputernaya-optika/Noise-reduction-and-mammography-image-segmentation-optimization-with-novel-QIMFTSSA-method-102110
Другие идентификаторы : Dspace\SGAU\20230220\102110
Располагается в коллекциях: Журнал "Компьютерная оптика"

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