Fusion of images in ultrasound

1. FUSION OF ULTRASOUND AND
DOPPLER ULTRASOUND
IMAGES FOR IDENTIFICATION
OF BREAST LESIONS.
Rajeshwari R
Assistant Professor/BME
ICA052

2. Abstract
This paper we are taking the advantage of fusion based
image processing for identifying the lesion or tumour in breast
images taken using B mode ultrasound and 2D Doppler ultrasound
technique. The ultrasound images are preferred because of their
low cost, ready availability, radiation free source without
compromising the quality. The techniques involve the concept of
anisotropic filtering to filter and wiener filtering to remove the
common region in both the images. The suspicious region is
highlighted and the blood vessels associated with that region is
also extracted and both details are fused to form a single image.

3. Objective
• To detect breast lesions without using harmful
radiation.
• To get a clear picture of the disease progress.
• To understand the blood flow in the region of
interest.
• To create a model of the organ with underlying
vascular structures.
• Guidance of breast biopsy and other interventional
procedures; ƒTreatment planning for radiation
therapy.

4. Problem Statement
• Breast cancer is the frequently diagnosed cancer and
second important cause of mortality in women. Early
detection of Breast leison is essential for both patient
care and effective treatment.
• Mammography cannot be used for younger
women's.
• Study of blood flow is important for understanding
disease prognosis and classify into malignant or
benign.

5. Introduction
• Several biomarkers such as mammography, Ultrasound
or sonography, US elastography and power Doppler
imaging techniques are being used for screening and
early detection of Breast Cancer.
• Breast US imaging shows increasing interest in breast
cancer diagnosis as an adjacent tool to mammography.
• US image interpretation heavily depends on
radiologist’s experience and skill. Visual screening of
BUS image is tedious, subjective and time consuming.
• Utilizing sophisticated algorithms in BUS images
enhances radiologist’s accuracy in differentiating
benign from malignant lesions.

6. Introduction-Ultrasound Imaging
• Ultrasound (US) is an imaging technology that uses high-frequency sound
waves to characterize tissue. It is a useful and flexible modality in medical
imaging, and often provides an additional or unique characterization of
tissues, compared with other modalities such as conventional radiography
or CT.
• Ultrasound relies on properties of acoustic physics
(compression/rarefaction, reflection, impedance, etc.) to localize and
characterize different tissue types. The frequency of the sound waves used
in medical ultrasound is in the range of millions of cycles per second
(megahertz, MHz).
A linear 12–5MHz transducer is commonly used

7. Introduction-Doppler Imaging
• The use of color flow Doppler (CFD) or color Doppler imaging
(CDI) (or simply color Doppler) sonography allows the
visualization of flow direction and velocity within a user defined
area. A region of interest is defined by the sonographer, and the
Doppler shifts of returning ultrasound waves within are color-
coded based on average velocity and direction.

8. Characteristic of Ultrasound Images-B
Mode
Image can be of hyperechoic, hypoechoic, anechoic
The majority of breast lesions detected by
ultrasound are hypoechoic. A hyperechoic lesion is
defined by an echogenicity greater than that of
subcutaneous fat or equal to that of fibro glandular
parenchyma.
Speckle noise is multiplicative in nature. This type of
noise is an inherent property of medical ultrasound
imaging and because of this noise the image resolution
and contrast become reduced, which effects the
diagnostic value of this imaging modality.

9. Characteristic of Doppler Ultrasound
Images
• Positive Doppler Shift
Frequency of received sound waves is greater than emitted sound
waves.
Source of reflecting sound wave is moving towards
the emitting source (red).
• Negative Doppler Shift
Frequency of received sound waves is lesser than emitted sound
waves.
Source of reflecting sound wave is moving away from the emitting
source (blue).

10. Existing system
• Mammography is used to screen.
• CT and MRI Image fusion is done to locate the
region.
• Contrast agents are used to scan the functionality
from that vascular nature of the organ can be
studied.
• Wiener filtering approach is used only for noise
removal.

11. Proposed methodology
• Wiener filtering for removing of common regions in
images taken from same patients under 12’o clock
position using normal ultrasound and Doppler
imaging principle.
• On removing two images are fused to overlap the
vascular information with anatomy of the organ.
Thing to note: Images should be taken from single patient at same time and same
position to improve the prediction accuracy.

12. Steps to Incorporate Wiener Filtering
• Wiener Filtering in shearlet domain.
• Shearlets are a multiscale framework which allows efficient
encoding of anisotropic features in multivariate domain.
• Anisotropic Features - is the property of a material which
allows it to change or assume different properties in different
directions.(Eg.,Soft Tissues ).
• Image is divided into shearlet bands using shearlet transform.
• Image is divided into low pass ST band and high pass ST band.
• Remove/mask the high frequency region.

13. Steps to Implement Proposed methodology
Step 1: Acquire the normal sonogram image of the breast tissue.
Step 2: Acquire the Doppler ultra sonograph of the patient.
Step3: Convert the images format into JPEG.
Step 4: Convert the image RGB to GRAY values.
Step 5: Convert the image into .png format.
Step 6: Resize the image by reading the size of the image .if equal
size then the step can be skipped.(=512 X 512)
Step 7: Despeckle the image if speckle noise dominates in the image.
(Speckle reducing anisotropic diffusion has the ability of detecting edges and suppress the
smooth at edge by using the separability of images)
Step 8:Implement the concept of Wiener filter to remove the
unwanted region around the suspected area.
Step 9: Subtract the common regions in both image to fuse the
areas of interest taken using two modalities.

14. Experimental results
Ultrasound Image of Breast after
Despeckling using anistropic filtering.
Color Doppler Ultrasound Image of Breast
after Despeckling using anistropic
filtering.
Extraction of region of interest from
ultrasound images.

15. Experimental results
Extraction of region of interest Doppler
ultrasound image
Fusion of two uncommon region
In this work, a total of 76 patients with 76 B mode US and Doppler images obtained by a Philips iU22 US machine
at the Thammasat University Hospital . The database includes 14 benign lesions and 62 malignant lesions.

16. Conclusion
• The same procedure to be repeated from 12 ‘o clock position to 120
degree .Once fused all the images taken at various degrees information
can be modelled using CAD tools like Auto Desk 3D.Elastography of the
region can be incorporated to improve the accuracy.

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20. THANKYOU