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Segmentation and Characterization of White Matter Lesions in FLAIR Magnetic Resonance Imaging
Published in de Azevedo-Marques Paulo Mazzoncini, Mencattini Arianna, Salmeri Marcello, Rangayyan Rangaraj M., Medical Image Analysis and Informatics: Computer-Aided Diagnosis and Therapy, 2018
Brittany Reiche, Jesse Knight, Alan R. Moody, April Khademi
Shape analysis techniques refer to a set of image processing tools that focus on characterizing segmented objects based on their shape. Shape analysis has typically been used for object recognition and matching, boundary filtering, and general shape characterization (Loncarica, 1988). These methods will be used to differentiate between different types of WML.
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Published in Phillip A. Laplante, Dictionary of Computer Science, Engineering, and Technology, 2017
shape analysis the analysis of shapes of objects in binary images, with a view to object or feature recognition. Typically, shape analysis is carried out by measurement of skeleton topology or by boundary tracking procedures including analysis of centroidal profiles.
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Published in Philip A. Laplante, Comprehensive Dictionary of Electrical Engineering, 2018
shielding effectiveness Shannon's source coding theorem a major result of Claude Shannon's information theory. For lossy source coding, it gives a bound to the optimal source coding performance at a particular rate ("rate" corresponds to "resolution"). The theorem also says that the bound can be met by using vector quantization of (infinitely) high dimension. For lossless source coding, the theorem states that data can be represented (without loss of information) at a rate arbitrarily close to (but not lower than) the entropy of the data. See also rate-distortion theory. shape analysis the analysis of shapes of objects in binary images, with a view to object or feature recognition. Typically, shape analysis is carried out by measurement of skeleton topology or by boundary tracking procedures including analysis of centroidal profiles. shape from . . . the recovery of the 3-D shape of an object based on some feature (e.g., shading) of its (2-D) image. shape measure a measure such as circularity measure (compactness measure), aspect ratio, or number of skeleton nodes, which may be used to help characterize shapes as a preliminary to, or as a quick procedure for, object recognition. shape-gain vector quantization (SGVQ) a method for vector quantization where the magnitude (the gain) and the direction (the shape) of the source vector are coded separately. Such an approach gives advantages for sources where the magnitude of the input vector varies in time. shape-memory effect mechanism by which a plastically deformed object in the low-temperature martensitic condition regains its original shape when the external stress is removed and heat is applied. shape-memory smart materials include three categories, namely shape-memory alloys (SMA), shape-memory hybrid composites (SMHC), and shape-memory polymers (SMP). shaping a traffic policing process that controls the traffic generation process at the source to force a required traffic profile. shared memory characteristic of a multiprocessor system: all processors in the system share the access to main memory. In a physically shared-memory system, any processor has access to any memory location through the interconnection network. shared memory architecture a computer system having more than one processor in which each processor can access a common main memory. sharpening the enhancement of detail in an image. Processes that sharpen an image also tend to strengthen the noise in it. See edge enhancement, gradient, image enhancement, Laplacian operator, noise, Sobel operator. SHDTV See super high definition television.
Osteoarthritis detection by applying quadtree analysis to human joint knee X-ray imagery
Published in International Journal of Computers and Applications, 2022
Sophal Chan, Kwankamon Dittakan, Subhieh El Salhi
OA classification has been attracted for many researchers with the application of applying image processing [6–10]. With respect to the study purpose, shape analysis is one of the famous techniques in image processing field which can analyze the shape of the geometric or statistical shape of an object. In addition, shape analysis have been applied in various research fields include: (i) remote sensing [11–13], (ii) chemistry and biology research [14], (iii) agricultural products [15–17], (iv) industrial products [18,19], and (v) medical [3–5]. There are many techniques of shape analysis for the classification tasks include: (i) shape boundary [20–22], (ii) medial axis transform (MAT)[23,24], (iii) shape decomposition(image decomposition) [12,25,26], etc. With reference to the research purpose, the image decomposition is focused. In image decomposition consist of (i) quadtree, (ii) wavelet, (iii) scale space, and (iv) pyramid (both Gaussian and Laplacian pyramid). To be more evidence of the methodology of image composition in term of medical image, the work [27] have been proposed wavelet parameter to MRI and CT images classification, in the study [28] have applied the Laplacian pyramid for image fusion with the application of CT and MRI image. In addition, quadtree which is the famous technique in shape decomposition is divided the region of interest into four equal square (quadrant) regions until the smallest region [29]. Quadtree have been applied in various field of research including: (i) remote sensing [12,30], (ii) medical image [31,32], (iii) geographic [33], (iv) Cell-center detection [34], etc. Based on the literature reviews, there are very few researchers applied the quadtree technique with OA detection. Thus, this proposed framework maybe the new framework for OA detection with quadtree application in X-ray image modality.