Bari, Bifta Sama and Sabira, Khatun and Kamarul Hawari, Ghazali and Fa-kir, Md. Moslemuddin and Wan Nur Azhani, W. Samsudin and Mohd Falfazli, Mat Jusof and Rashid, Mamunur and Islam, Minarul and M. Z., Ibrahim (2019) Ultra wide Band (UWB) Based Early Breast Cancer Detection using Artificial Intelligence. In: 5th International Conference On Electrical, Control And Computer Engineering (INECCE2019) , 29-30 July 2019 , Kuantan, Pahang, Malaysia. pp. 1-11.. (Unpublished)
|
Pdf
Ultra wide Band (UWB) Based Early Breast Cancer CONF1.pdf Download (110kB) | Preview |
|
![[img]](http://umpir.ump.edu.my/style/images/fileicons/other.png) |
Pdf
Ultra wide Band (UWB) Based Early Breast Cancer CONF.pdf Restricted to Repository staff only Download (495kB) | Request a copy |
Abstract
Breast cancer is a silent killer malady among women community all over the world. The death rate is increased as it has no syndrome at early stage. There is no remedy; hence, detection at the early stage is crucial. Usually, women do not go to clinic/hospital for regular breast health checkup unless they are sick. This is due to long queue and waiting time in hospital, high cost, people‟s busy schedule, and so on. Recently, several research works has been done on early breast cancer detection using Ultra Wide Band (UWB) technolo-gy because of its non-invasive and health-friendly nature. Each proposed UWB system has its own limitation including system complexity, expensive, expert operable in clinic. To overcome these problems, a system is required which should be simple, cost-effective and user-friendly. This chapter presents the de-velopment of a user friendly and affordable UWB system for early breast can-cer detection utilizing Artificial Neural Network (ANN). A feed-forward back propagation Neural Network (NN) with 'feedforwardnet' function is utilized to detect the cancer existence, size as well as location in 3-dimension (3D). The hardware incorporates UWB transceiver and a pair of pyramidal shaped patch antenna to transmit and receive the UWB signals. The extracted features from the received signals have been fed into the NN module to train, validate, and test. The average system‟s performance efficiency in terms of tumor/cancer ex-istence, size and location are approximately 100%, 92.43% and 91.31 % respec-tively. Here, in our system, use of „feedforwardnet‟ function; detection-combination of tumor/cancer existence, size and location in 3D along with im-proved performance is a new addition compared to other related researches and/or existing systems. This may become as a promising user-friendly system in near future for early breast cancer detection in domestic environment with low cost and to save precious life.
| Item Type: | Conference or Workshop Item (Lecture) |
|---|---|
| Uncontrolled Keywords: | Early Breast Cancer, Ultra Wideband (UWB), Neural Network (NN), Feed Forward Back Propagation. |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Faculty/Division: | Centre of Excellence: Centre of Excellence for Advanced Research in Fluid Flow Faculty of Chemical & Natural Resources Engineering Faculty of Electrical & Electronic Engineering Institute of Postgraduate Studies |
| Depositing User: | Noorul Farina Arifin |
| Date Deposited: | 17 Jan 2020 04:30 |
| Last Modified: | 15 Jun 2022 04:09 |
| URI: | http://umpir.ump.edu.my/id/eprint/27509 |
| Download Statistic: | View Download Statistics |
Actions (login required)
 |
View Item |