Lungs Segmentation and Nodule Detection using Machine Learning Contributor(s): Jaffar, Arfan (Author), M. Mirza, Anwar (Author), Sun Choi, Tae (Author) |
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ISBN: 3639342801 ISBN-13: 9783639342802 Publisher: VDM Verlag OUR PRICE: $69.77 Product Type: Paperback Published: April 2011 |
Additional Information |
BISAC Categories: - Computers | Information Technology |
Physical Information: 0.38" H x 6" W x 9" (0.55 lbs) 164 pages |
Descriptions, Reviews, Etc. |
Publisher Description: 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. |