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I'm doing thesis writing the content of 6 chapters are below
CHAPTER 1 INTRODUCTION
1.1 Introduction 1.2 Problem Background 1.3 Problem Statement
1.4 Research Goal 1.4.1 Research Objectives 1.5 Scope of the Study
1.6 Significance of the Study 1.7 Organization of Thesis
CHAPTER 2 LITERATURE REVIEW
2.1 Introduction 2.2 MRI imaging 2.3 Image Enhancement 2.4 Segmentation 2.4.1 Performance of Segmentation
2.4.2 Fundamental rules for Segmentation 2.4.3 Histogram 2.4.4 Dominant grey level 2.4.5 Feature selection 2.4.6 Range Filter
2.4.7 Feature Extraction 2.4.8 Morphological operation 2.4.9 Region of interest 2.5 Segmentation detection 2.5.1 Point, line and Edge detection
2.5.2 Background 2.5.3 First Order Derivative 2.5.4 Second order Derivative 2.5.5 Partial Derivative 2.5.6 Line Detection 2.5.7 Point Detection
2.5.8 Edge Detection 2.5.8.1 Edge detection Model 2.6 Thresholding 2.6.1 Thresholding and its types 2.6.2 Region based Segmentation Algorithm
2.6.3 Split and Merge segmentation 2.7 Comparative study 2.8 Comparative accuracy parameters for segmentation 2.9 Summary
CHAPTER 3 RESEARCH METHODOLOGY
3.1 Introduction 3.2 Main Framework 3.3 MACCAI Brats brain tumor Segmentation challenge data set
3.4 Hardware and Software Requirement 3.5 Evaluation metrics 3.6 Summary
CHAPTER 4 PRE PROCESSING
4.1 The Big Picture 4.2 Analytical Proofs 4.3 MATERIAL 4.3.1 Intensity Adjustment 4.3.2 Biggest blob area of input image
4.3.3 Combination of biggest blobs 4.3.4 COLOR the pixels in region of interest, FINAL biggest Blob and check with ground truth reality with confidence
4.3.5 LEVEL SETTING FOR CELLS SEPERATION 4.4 Summary 4.5 Result and Discussion 4.6 Chapter Summary
CHAPTER 5 FEATURE SELECTION WITH UPATED SELF ORGANISATION FEATURE MAP (SOFM)
5.1 Introduction 5.2 FEATURE EXTRACTION 5.3 SOM Feature map reduction in SOM architecture 5.4 Reduce Feature and segmentation
5.5 Future Works 5.6 Chapter summary
CHAPTER 6 HYBRID SEGMENTATION
6.1 INTRODUCTION 6.2 SOM_KMEAN_FCM 6.3 KMEAN 6.4 Fuzzy C Mean 6.5 Inclusion of SOM with KMEAN_FCM