Feature Extraction in Medical Image by Aswini Kumar Samantaray (.PDF)+

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Feature Extraction in Medical Image Retrieval: A New Design of Wavelet Filter Banks by Aswini Kumar Samantaray, Amol D. Rahulkar
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Overview: Medical imaging is fundamental to modern healthcare, and its widespread use has resulted in creation of image databases. These repositories contain images from a diverse range of modalities, multidimensional as well as co-aligned multimodality images. These image collections offer opportunity for evidence-based diagnosis, teaching, and research. Advances in medical image analysis over last two decades shows there are now many algorithms and ideas available that allow to address medical image analysis tasks in commercial solutions with sufficient performance in terms of accuracy, reliability and speed. Content-based image retrieval (CBIR) is an image search technique that complements the conventional text-based retrieval of images by using visual features, such as color, texture, and shape, as search criteria. This book emphasizes the design of wavelet filter-banks as efficient and effective feature descriptors for medical image retrieval. Firstly, a generalized novel design of a family of multiplier-free orthogonal wavelet filter-banks is presented. In this, the dyadic filter coefficients are obtained based on double-shifting orthogonality property with allowable deviation from original filter coefficients. Next, a low complex symmetric Daub-4 orthogonal wavelet filter-bank is presented. A computer based system used for browsing, searching, and retrieving images from a sizable collection of digital images is called a content-based image retrieval (CBIR) system. Large archives of images and multimedia content have been created in recent years due to the rapid rise of digital computers, multimedia, and storage technologies.
Genre: Non-Fiction > Tech & Devices

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