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[QUOTE=Guest;155503]ANSIF. F U
 ansiffasil AT gmail.com 
[b]CAREER OBJECTIVE [/b]:
- To join a firm that believes in me and my workability and to be a part of a team that takes the firm to new heights. To implement my syllabus with innovative ideas that shall be well appreciated by the organization.
[b]EDUCATIONAL QUALIFICATION [/b]:
- B.E (ECE) from PET Engineering College aggregate with 70%, Apr 2011.
- Higher Secondary from LMS Govt. Higher Secondary School aggregate with 71%, 
Mar 2007.
- SSLC from T.E.M.V.H.S School aggregate with 70%, Mar 2005.
[b]TECHNICAL SKILLS [/b]:
[b]- Operating Systems  [/b]: Win (98-2000&XP,7)
[b]- Languages  [/b]: C,C++,PHP
[b]- Package  [/b]: Ms Office 
[b]AREA OF INEREST [/b]:
- Electron Devices and Circuits.
- Data structures.
- Digital image processing.
- VLSI.
[b]ACHIEVEMENTS [/b]:
- Won First prize in intra College paper presentation.
- Won First prize in intra College Quiz competition.
- Won First prize in intra College Cricket tournament.
[b]TRAINING & COURSES [/b]:
- Implant training in KELTRON at Trivandrum.
[b]KEY STRENGTHS [/b]: 
- Communication Skills.
- Hard working and self-confident.
- Leadership Qualities.
[b]PROJECT DESCRIPTION [/b]:
IMPROVED HYBRID SEGMENTATION OF BRAIN MRI TISSUE AND TUMOR USING STATISTICAL FEATURES
[b]- Domain  [/b]: Digital Image Processing
[b]- Platform  [/b]: MATLAB
[b]- Version  [/b]: MATLAB 6.5
[b]- Duration  [/b]: 2 months
[b]- Team members  [/b]: 3
[b]Description [/b]: 
 Medical image segmentation is the most essential and crucial process in order to facilitate the characterization and visualization of the structure of interest in medical images. Relevant application in neuroradiology is the segmentation of MRI data sets of the human brain into the structure classes gray matter, white matter and cerebrospinal fluid (CSF) and tumor. In this paper, brain image segmentation algorithms such as Fuzzy C means (FCM) segmentation and Kohonen means (K means) segmentation were implemented. In addition to this, new hybrid segmentation technique, namely, Fuzzy Kohonen means of image segmentation based on statistical feature clustering is proposed and implemented along with standard pixel value clustering method. The clustered segmented tissue images are compared with the Ground truth and its performance metric found more improved than pixel based segmentation.
[b]DECLARATION [/b]:
- I hereby declare that the above mentioned information is correct up to my knowledge and I bear the responsibility for the correctness of the above mentioned particulars
 
[b]PLACE [/b]: MEEYANA Yours Faithfully
[b]DATE  [/b]: 22/08/2011 (ANSIF.F U)[/QUOTE]

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