MULTI-THRESHOLD IMAGE SEGMENTATION FOR LUNG CANCER IMAGE MINING
Principal Investigator
Name
samatha gamidi
Degrees
M.tech(cse)
Institution
kiet
Position Title
student
Email
About this CDAS Project
Study
NLST
(Learn more about this study)
Project ID
NLST-33
Initial CDAS Request Approval
Aug 9, 2013
Title
MULTI-THRESHOLD IMAGE SEGMENTATION FOR LUNG CANCER IMAGE MINING
Summary
Author wish to develop a unique software tool to process and analyse lung cancer CT image data base in order to facilitate the early diagnosis of the cancer tumor in patients. System is also intended to carryout research on the Lung cancer CT image data base to figure out the various hidden patterns by implementing few advanced signal processing tools. These advanced digital signal processing techniques help us extracting hidden features from the raw CT images. A few statistical methods to implement on the extracted data from the CT images to figure out the underlying patterns of the cancer data base, based on the given geographical area or a period of time.
Aims
To implement various advanced image signal processing techniques to extract the feature and to apply some novel statistical and data mining techniques to figure out the hidden pattern in the Lung Cancer Data Base.
Collaborators
Name: samathagamidi
Institution:KAKINADA INSTITUTE OF ENGINEERING & TECHNOLOGY