An Efficient Method for Contrast Enhancement of Digital Mammographic Images

Kumar, Sanjeev; Chandra, Mahesh

doi:10.1007/978-3-319-04693-8_5

Cited by 2 publications

(1 citation statement)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Since the contrast of digital mammogram images is low, it is necessary to improve the quality of the image by pre-processing it. The digital mammogram images are pre-processed by using the wavelet based adaptive modified sigmoid function (WBAMSF) [35]. The pre-processing of digital mammogram images consists of the following three steps: in the first step wavelet decomposition is done.…”

Section: Pre-processingmentioning

confidence: 99%

Detection of Microcalcification Using the Wavelet Based Adaptive Sigmoid Function and Neural Network

2015

J Inf Process Syst

View full text Add to dashboard Cite

Mammogram images are sensitive in nature and even a minor change in the environment affects the quality of the images. Due to the lack of expert radiologists, it is difficult to interpret the mammogram images. In this paper an algorithm is proposed for a computer-aided diagnosis system, which is based on the wavelet based adaptive sigmoid function. The cascade feed-forward back propagation technique has been used for training and testing purposes. Due to the poor contrast in digital mammogram images it is difficult to process the images directly. Thus, the images were first processed using the wavelet based adaptive sigmoid function and then the suspicious regions were selected to extract the features. A combination of texture features and graylevel co-occurrence matrix features were extracted and used for training and testing purposes. The system was trained with 150 images, while a total 100 mammogram images were used for testing. A classification accuracy of more than 95% was obtained with our proposed method.

show abstract

Section: Pre-processingmentioning

confidence: 99%