DETECTION OF LUNGS NODULE CANDIDATES IN CHEST RADIOGRAPHS

SUPERVISED BY: Dr. ASMATULLAH KHAN

GROUP MEMBERSSAJID KHAN O7-0094RIAZ AHMED 07-0100MAJID ALI 07-0106

What is nodule?

• A pulmonary nodule is a small, roundish growth on the lung, sometimes called a spot on the lung.

• Pulmonary nodules turn up in about one of every 500 chest x-rays

• From literature review it is observed that lung nodule causes cancer that is the second most common cancer in humans with mortality rate more than 90 %.

XRAY OF NODULE EFFECTED LUNG

NODULE DETECTED BY RADIOLOGIST

PROJECT OVERVIEW

• In this project we desire to make the lung nodule visible to a machine. To make it happen we implemented and applied geometric filters which exploits geometry of nodule for its enhancment. These filters are reffered to as Convergence Index and Iris Filter and SBF.

• In addition we also included the application of Lindberg’s blob detection technique along with another technique of marking boundary of nodules.

IDEAL NODULE

GRADIENT VECTOR

• The definition of gradient in physics is the rate at which any physical quantity whether it is temperature, pressure, or such other things decreases or increases with respect to a given variable.

• According to mathematics, gradient is a vector whose coordinate components are the partial derivatives of a function with respect to the variables that affects it.

• Gradient(x)= Gradient(y)=

• Lung image

GRADIENT VECTOR (CONT: )

HOW GRADIENT VECTOR CAN BE HELPFUL

• In case of nodule, almost all of the gradients in its region of support points towards its center.• The angles between gradient vector at every pixel in the neighborhood of the center the nodule, and the

distance vector from center towards these pixels are nearly equal to 180 degree.

• This concept can be used to calculate degree of convergence of any filter.

Degree of convergence

• In case of noduleGradient vector

Distance vector

Degree of convergence

• In case of non nodule

Gradient vector

Distance vector

SEGMENTATION OF X-RAY

SEGMENTATION OF X-RAY

Convergence index filter

• The convergence index filter, mainly differing on the region of support used for calculating the convergence degree. The Equation of Convergence index filter is given below.

Region of support.

• The region of support is small piece of an image, in this piece we calculate the convergence degree of a pixel of interest, then we shift the region of support pixel by pixel and calculate the convergence degree of that pixel.

Zero Padding

• shows zero padding mechanism for the mask or region of support of 3×3.

RESULTS OF CONVERGENCE FILTER

ORIGINAL IMAGE CONVERGENCE INDEX FILTER

IRIS FILTER

• Working of IRIS filter is almost same but the main difference is the number of lines radiating away from the pixel of interest that is used in IRIS filter.

• Equation of IRIS filter is given below:

Region of support in Iris Filter

RESULT OF IRIS FILTER

ORIGINAL IMAGE IRIS FILTER

Sliding band filter (SBF)

• Sliding band filter (SBF), is also a member of the CI filter class as its output is also a measure of the degree of convergence of gradient vectors. The main difference between this new filter and the iris filter is that the SBF searches in each radial direction the band of fixed width that corresponds to the maximum degree of convergence.

• The SBF equation is given below.

Region of support in SBF

RESULT OF SBF

COMPARISION

USE OF LINDBERG’S BLOB DETECTION

• We can use Lindberg’s blob detection technique to mark those regions from where we can get strong nodular candidate.

• Lindberg’s blob detection technique is used to draw circles across those areas where contrast changes.

• In such a way we can save the processing time for the detection of lung nodule candidates BY by first applying Lindberg’s blob detection and then applying our filters on circled areas only.

CONT…

MARKING BOUNDARIES OF CANDIDATES