enhancement of mammogram images ppt

1. A Presentation
on
Enhancement of Mammogram Images
DEPARTMENT OF COMPUTER SCIENCE ENGINEERING &INFORMATION
TECHNOLOGY
Submitted to: Submitted by:
Ms Meenakshi Gujral Punit Karnani
Mr. Gaurav Saxena Himanshu Sharma

2. MAMMOGRAM IMAGES
 For the detection of breast cancer mammofram
images are taken which is the leading cause of
death in women. Radiologist look for certain
features to analyse mammogram but due to its
fuzzy nature , low contrast and low differentiability it
is not possible to analyse and provide diagnosis.

3. OBJECTIVE OF IMAGE ENHANCEMENT
 The principle objective of Image enhancement is to
process an image so that result is more suitable
than original image for specific application
 This technology aims to gain the advantages of
enhance and sharpening process that aims to
highlight sudden changes in the image intensity.

4. FEATURES OF IMAGE ENHANCEMENT
 The main feature of mammography is the primary
imaging technique for detection and diagnosis of
breast cancer.
 It highlights the certain characteristics of an image.

5. AIM OF PROJECT
 Our main main aim of project is to enhance the
mammogram images.
 Proccesing of images to bring out specific feature
from previous image after applying some methods
of given mammogram.

6. METHODS USED IN PROJECT
 PSNR ratio
 Filteration by various filters like weiner filter, median
filter and linear filter.
 Wavelet transformation
 Mean square error
 Spatial domain method

7. PSNR RATIO
 PSNR ratio is Peak signal to noise ratio, in our
project it is calculated for comparison of different
filters value.
 The more will be the PSNR , lesser will be noise
and image would be clear and more easier to
visualize.

8. WAVELET TRANSFORMATION
 In our project wavelet transformation is used to
decomposing the noisy image and reconstructing
the resutling paramters of image after applying
filteration proces.

9. SPATIAL DOMAIN METHOD
 Contrast and dynamic range modification
 Noise reduction
 Edge Enhancement and detection

10. MEAN SQURE ERROR
 Usually in many techniques mean square error
calculation is not necessary but in case of
evaluation and comparative purpose, it will be
essential to judge previous and reconstructed
image.

11. CONCLUSION
 On the basis of PSNR we find out are own
proposed linear filter in which we used various
image proccessing technique like wavelet
transformation.
 We find out the mean square error between original
image and noisy image.
 Reduced noise in original image to get better
quality of image.

12. THANK YOU!