An intelligent CAD system for automated detection of pulmonary tuberculosis
#1

Presented By
Rashmi G Belahunasi
Satish Kumar Singh
Shekhar Shukla
Srividhya T D

[attachment=13367]
An intelligent CAD system for automated detection of pulmonary tuberculosis on CT scan images
Purpose of Project
To take as input a set of CT images and de-noise them before passing them to our algorithm.
To provide an algorithm for early detection of tuberculosis.
Flow Diagram of Project
Image Enhancement
Each image can be represented in coordinate system where in part of the image is given by a set of (x, y) coordinates.
Each coordinate in the image represents a pixel and the pixels will be consisting of RGB component.
Image Enhancement (contd..)
We are focusing on the grey scaling method to enhance the quality of the image.
The CT scan image of the lungs will be having the lungs with the white color and the surrounded fluid with dense intensity of RGB component.
Image Enhancement (contd..)
In Grey scale method, we describe a code such that the CT scan image with higher RGB component intensity will be turned to black and removed. This is the fluid present around the lungs.
The lung portion is turned to grey which is of almost white composition.Thus the ROI (region of interest), the lungs is extracted successfully.
Image Enhancement
Image enhancement technique
involves recovering
the image using a filtering
function adapted to the
image content. Definition
of such a function relies
on the computation of
similarity between pixels
of a given neighborhood.
Image Enhancement (contd..)
Noise reduction is achieved through the modification of the coefficients with limited importance in the reconstruction process.
Image segmentation
The goal of image
segmentation is to
cluster pixels into
salient image
regions,i.e., regions
of interest.
Segmentation (contd..)
Feature Extraction
In pattern recognition and in image processing, feature extraction is a special form of dimensionality reduction
When the input data to an algorithm is too large to be processed and is suspected to be redundant then the input data will be transformed into a reduced representation set of features. Transforming the input data into the set of features is called feature extraction.
Feature Extraction (contd..)
It has two fundamental tasks: description and classification. Given an object to analyze, the system first generates a description and then classifies the object based on that description.
Pattern Recognition
Pattern recognition is a branch of science that helps develop "classifiers" that can recognize unknown instances of objects.
Pattern recognition in image processing is identifying characters of the image that need to be quantified for generating results through appropriate algorithm or neural network.
Neural Network
The main aim of our project is to develop a probabilistic neural network structure designed for estimating the parameters of CT image analysis for early detection of tuberculosis.
Neural Network
We can utilize the neural network to approximate to the continuous quantity, because any continuous quantity can be express by the combinations of linear and nonlinear function.
The new technology can help us solve the technical problem of clear visual communication and the problem of high compression ratio, etc.
Decision Box
Once an efficient neural network scale is done ,we proceed with a decision box according to scale value whether tuberculosis is there or not.
Work Flow of the team
21/02/11 to 03/03/11 Image Enhancement by Satish Kumar Singh.
25/02/11 to 12/03/11 Image segmentation by Srividhya.T.D.
25/02/11 to 12/03/11 Feature extraction
by Rashmi G.B.
Beginning from 25/02/11Shekhar Shukla will be working on Neural network parallely.
As and when a teammate finishes his part of the work, he will assist in the work on neural network.
Reply

Important Note..!

If you are not satisfied with above reply ,..Please

ASK HERE

So that we will collect data for you and will made reply to the request....OR try below "QUICK REPLY" box to add a reply to this page
Popular Searches: future of cad, poster presentation on tuberculosis, cad system, multidrug resistance in mycobacterium tuberculosis, 3d cad browser, cad applications, need for intelligent vehicle automated highways,

[-]
Quick Reply
Message
Type your reply to this message here.

Image Verification
Please enter the text contained within the image into the text box below it. This process is used to prevent automated spam bots.
Image Verification
(case insensitive)

Possibly Related Threads...
Thread Author Replies Views Last Post
  OBJECT TRACKING AND DETECTION full report project topics 9 30,647 06-10-2018, 12:20 PM
Last Post: jntuworldforum
  Host-Based Intrusion Detection Using user signatures nit_cal 2 2,374 06-10-2016, 10:27 AM
Last Post: ijasti
  DETECTION OF THE MALARIAL PARASITE INFECTED BLOOD IMAGES BY 3D-ANALYSIS project report tiger 2 2,387 26-09-2016, 10:55 AM
Last Post: ijasti
  ULTRA SONIC TECHNIQUES FOR THE DETECTION OF HIDDEN CORROSION IN AIR CRAFT WING SKIN seminar projects crazy 5 6,073 15-04-2016, 08:04 PM
Last Post: knagpur
Heart wireless intelligent network(win) (Download Full Report And Abstract) computer science crazy 7 15,240 10-02-2015, 05:52 PM
Last Post: seminar report asees
  Automated Storage/Retrieval System seminar class 3 3,017 02-09-2013, 11:09 AM
Last Post: uchconveyor
  ARTIFICIAL INTELLIGENCE IN VIRUS DETECTION AND RECOGNITION seminar project explorer 2 3,345 22-07-2013, 11:44 AM
Last Post: computer topic
  Layered Approach Using Conditional Random Fields for Intrusion Detection project report helper 11 7,739 01-03-2013, 11:58 AM
Last Post: [email protected]
  A Seminar Report On INTRUSION DETECTION SYSTEM Computer Science Clay 1 5,749 23-11-2012, 01:13 PM
Last Post: seminar details
  Image Edge Detection based on FPGA seminar class 1 3,961 18-10-2012, 11:43 AM
Last Post: seminar details

Forum Jump: