Detection of Hepatolithiasis in CT Images for Image-Guided S

发布时间：2021-10-26 03:55

　　Hepatolithiasis is endemic in the Asia-Pacific region,where its prevalence can be as high as 30-50%.Complete cure of hepatolithiasis requires both extraction of the stones and elimination of bile stasis through surgery,and therefore it is essential to detect hepatolithiasis at an earlier stage.The easiest way to diagnose hepatolithiasis is by Computed Tomography（CT）images.The detection and segmentation of hepatolithiasis from CT images is an important prerequisite for computer-aided diagnosis,tr... 

【文章来源】：沈阳建筑大学辽宁省

【文章页数】：68 页

【学位级别】：硕士

【文章目录】：
Abstract
Chapter 1 Introduction
    1.1 Motivation and Scope
    1.2 Hepatolithiasis
    1.3 Image Guided Surgery
    1.4 Medical Background
        1.4.1 The Liver
        1.4.2 Anatomy
    1.5 Medical Imaging
    1.6 CT Imaging
    1.7 Main Research Contributions
    1.8 Organization of Thesis
Chapter 2 Literature Review
Chapter 3 Imaging Modalities for Image-Guided Surgeries
    3.1 Ultrasound Imaging
        3.1.1 Ultrasound Wavelength and Frequency
        3.1.2 Ultrasound-Tissue Interaction
    3.2 Generation of Ultrasound Images from CT
    3.3 Image Guided Surgery with Closed Loop Feedback
    3.4 Contour Delineation in Medical Applications
    3.5 Thermo-Sensitive Imaging for Treatment Monitoring
Chapter 4 Proposed Methodology
    4.1 Image acquisition
    4.2 Image Preprocessing
        4.2.1 Contrast Enhancement
            4.2.1.1 Histogram equalization
            4.2.1.2 Adaptive Histogram equalization
            4.2.1.3 Contrast Limited Adaptive Histogram Equalization
    4.3 Image Segmentation
        4.3.1 K-means Clustering
        4.3.2 Gradient Calculations
        4.3.3 Watershed Transform Segmentation
            4.3.3.1 Watershed Definition: Continuous Case
            4.3.3.2 Watershed definitions: discrete case
    4.4 Sequential Watershed Algorithms
        4.4.1 Vincent-Soille algorithm
        4.4.2 Components Graph Algorithm
    4.5 Morphological Operations
        4.5.1 Structuring Elements
        4.5.2 Dilation
        4.5.3 Erosion
        4.5.4 Opening
        4.5.5 Closing
    4.6 The Proposed Algorithm Outline
        4.6.1 Evaluation of the Proposed Method through Experiments
        4.6.2 Implementation of DICOM image acquisition
        4.6.3 Implementation of the CLAHE Method
        4.6.4. K-means Clustering Implementation
        4.6.5 Watershed and Morphological Operations Implementation
    4.7 Conclusive Remarks
Chapter 5 Analysis And Discussions
    5.1 The FROC Analysis
    5.2 Obtained FROC Results
        5.2.1 Accuracy
        5.2.2 Sensitivity
    5.3 Conclusive Remarks
Chapter 6 Conclusions
    6.1 Conclusions
    6.2 Scope for Future Study
References
About the Author
Acknowledgments



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