An accurate method of breast cancer detection from ultra sound images using probabilistic fuzzy clustering algorithm

Author(s):  
V K Vidya ◽  
Santo Mathew
2018 ◽  
Vol 7 (3.27) ◽  
pp. 471
Author(s):  
C Jayapriya ◽  
K Meena Alias Jeyanthi ◽  
. .

Ultra Wideband (UWB) radar is assuring technology for breast cancer detection based on the dielectric constant between normal and tumor tissues at Microwave frequencies. A Suitable design of a Microstrip Patch in Ultrawideband is proposed for microwave imaging in biomedical applications. Currently used clinical diagnostic methods, such as X-ray Mammography, Ultra-Sound and Magnetic Resonance Imaging, are limited by cost and reliability issues. These limitations have motivated researchers to develop a more effective, low-cost diagnostic method and involving lower ionization for cancer detection. The literature suggests a Side Slotted Vivaldi Antenna (SSVA) is clustered around 2.4GHz as the ISM band which is used for breast phantom measurement. Experimental validation is done mainly by using an antenna for detecting tumor cells inside a breast which is highly demanded as comfortable approach.   


2021 ◽  
Vol 11 (22) ◽  
pp. 10753
Author(s):  
Ahmad Ashraf Abdul Halim ◽  
Allan Melvin Andrew ◽  
Mohd Najib Mohd Yasin ◽  
Mohd Amiruddin Abd Rahman ◽  
Muzammil Jusoh ◽  
...  

Breast cancer is the most leading cancer occurring in women and is a significant factor in female mortality. Early diagnosis of breast cancer with Artificial Intelligent (AI) developments for breast cancer detection can lead to a proper treatment to affected patients as early as possible that eventually help reduce the women mortality rate. Reliability issues limit the current clinical detection techniques, such as Ultra-Sound, Mammography, and Magnetic Resonance Imaging (MRI) from screening images for precise elucidation. The capability to detect a tumor in early diagnosis, expensive, relatively long waiting time due to pandemic and painful procedure for a patient to perform. This article aims to review breast cancer screening methods and recent technological advancements systematically. In addition, this paper intends to explore the progression and challenges of AI in breast cancer detection. The next state of the art between image and signal processing will be presented, and their performance is compared. This review will facilitate the researcher to insight the view of breast cancer detection technologies advancement and its challenges.


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