The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Comparative Analysis of Proposed Artificial Neural Network (ANN) Algorithm With Other Techniques
|
|
Author(s): Deepak Chatha (Department of Computer Science and Engineering, Panipat Institute of Engineering and Technology, Samalkha, India), Alankrita Aggarwal (Department of Computer Science and Engineering, Panipat Institute of Engineering and Technology, Samalkha, India)and Rajender Kumar (Department of Computer Science and Engineering, Panipat Institute of Engineering and Technology, Samalkha, India)
Copyright: 2022
Pages: 6
Source title:
Research Anthology on Artificial Neural Network Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-6684-2408-7.ch058
Purchase
|
Abstract
The mortality rate among women is increasing progressively due to cancer. Generally, women around 45 years old are vulnerable from this disease. Early detection is hope for patients to survive otherwise it may reach to unrecoverable stage. Currently, there are numerous techniques available for diagnosis of such a disease out of which mammography is the most trustworthy method for detecting early cancer stage. The analysis of these mammogram images are difficult to analyze due to low contrast and nonuniform background. The mammogram images are scanned and digitized for processing that further reduces the contrast between Region of Interest and background. Presence of noise, glands and muscles leads to background contrast variations. Boundaries of suspected tumor area are fuzzy & improper. Aim of paper is to develop robust edge detection technique which works optimally on mammogram images to segment tumor area. Output results of proposed technique on different mammogram images of MIAS database are presented and compared with existing techniques in terms of both Qualitative & Quantitative parameters.
Related Content
|
Vinod Kumar, Himanshu Prajapati, Sasikala Ponnusamy.
© 2023.
18 pages.
|
|
Sougatamoy Biswas.
© 2023.
14 pages.
|
|
Ganga Devi S. V. S..
© 2023.
10 pages.
|
|
Gotam Singh Lalotra, Ashok Sharma, Barun Kumar Bhatti, Suresh Singh.
© 2023.
15 pages.
|
|
Nimish Kumar, Himanshu Verma, Yogesh Kumar Sharma.
© 2023.
16 pages.
|
|
R. Soujanya, Ravi Mohan Sharma, Manish Manish Maheshwari, Divya Prakash Shrivastava.
© 2023.
12 pages.
|
|
Nimish Kumar, Himanshu Verma, Yogesh Kumar Sharma.
© 2023.
22 pages.
|
|
|