Lungs Segmentation and Nodule Detection using Machine Learning: Medical Image Segmentation and Classification using Machine Learning
Lungs Segmentation and Nodule Detection using Machine Learning: Medical Image Segmentation and Classification using Machine Learning — back cover
Lungs Segmentation and Nodule Detection using Machine Lea...
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    Lungs Segmentation and Nodule Detection using Machine Learning: Medical Image Segmentation and Classification using Machine Learning

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    Book Details

    Format
    Paperback
    Language
    English
    Category
    Computers & Technology
    Condition
    New
    ISBN-13
    9783639342802
    ISBN-10
    3639342801

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    Product description

    ISBN: 3639342801

    Author: Jaffar, Arfan

    Condition: New

    Segmentation of images has become an important and effective tool for many technological applications like lungs segmentation from CT scan images. The objective of this book is to develop a new fully automated system that segment the lungs part from CT scan images and detect nodules automatically. A fully automatic un-supervised strategy has been developed for the segmentation of lungs. Technique employs a novel background removal operator based on histogram of the image to remove the background very intelligently and automatically. The methodology utilizes spatial Fuzzy C-Mean (FCM) clustering to ensure robustness against the noise. Also a fuzzy histogram based image filtering technique has been used to remove the noise, which preserves the image details for low as well as highly corrupted images. Segments have been validated by using different cluster validity functions. The proposed technique finds out optimal and dynamic threshold by using fuzzy entropy and genetic algorithms. A directional approach has been used to extract the Region of Interests (ROIs) and FCM have been used to classify ROIs that contain nodule.

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    Lungs Segmentation and Nodule Detection using Machine Learning: Medical Image Segmentation and Classification using Machine Learning

    $167.00 CAD
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