|Table of Contents|

Neural Network- based Detection of Masses in Mammograms

《哈尔滨理工大学学报》[ISSN:1007-2683/CN:23-1404/N]

Issue:
2008年06期
Page:
101-104
Research Field:
计算机与控制工程
Publishing date:

Info

Title:
Neural Network- based Detection of Masses in Mammograms
Author(s):
SHI Sheng -jun SONG Li-xin ZHAO Yang
(School of Electrical and Electronic Engineering, Harbin University of Science and Technology. Harbin 150040, China)
Keywords:
mammogram mass detection wavelet transform histogram equalization BP Neural Network
PACS:
-
DOI:
-
Abstract:
To solve the pvoblem that the masses on the and have the fuzzy boundaries, the paper presents a method gram equalization theory firstly, and extract four features of mammograms exhibit poor contrast to the background to enhance the image by wavelet transform and histoevery pixel. According to the principle that artificial neural network can implement classification through training, the paper presents the method to classify every pixel to the masses or not by BP neural network to achieve the detection of the masses. The method has simple operation, and is evaluated by 30 mammograms images in the MIAS, and the effectiveness is 83%.

References:

Memo

Memo:
-
Last Update: 2017-06-27