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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I am interested in conducting research in areas related with image processing, machine learning, computer vision, artificial intelligence and medical imaging. I am specially interests in biologically inspired ideas like genetic algorithms, artificial neural networks, and soft-computing applications in Medial Imaging and Image processing.
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Kartoniert / Broschiert. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Jaffar ArfanI am interested in conducting research in areas related with image processing, machine learning, computer vision, artificial intelligence and medical imaging. I am specially interests in biologically inspired ideas li. Seller Inventory # 4979325
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Taschenbuch. Condition: Neu. Lungs Segmentation and Nodule Detection using Machine Learning | Medical Image Segmentation and Classification using Machine Learning | Arfan Jaffar (u. a.) | Taschenbuch | Englisch | VDM Verlag Dr. Müller | EAN 9783639342802 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Seller Inventory # 107037240
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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. Seller Inventory # 9783639342802