By Khin Wee Lai, Yan Chai Hum, Maheza Irna Mohamad Salim, Sang-Bing Ong, Nugraha Priya Utama, Yin Mon Myint, Norliza Mohd Noor, Eko Supriyanto
This booklet presents the latest findings and information in complicated diagnostics expertise, protecting a large spectrum together with mind job research, breast and lung melanoma detection, echocardiography, laptop aided skeletal overview to mitochondrial biology imaging on the mobile point. The authors explored magneto acoustic methods and tissue elasticity imaging for the aim of breast melanoma detection. views in fetal echocardiography from a picture processing perspective are incorporated. Diagnostic imaging within the box of mitochondrial illnesses in addition to using Computer-Aided approach (CAD) also are mentioned within the booklet. This booklet could be necessary for college kids, teachers or expert researchers within the box of biomedical sciences and snapshot processing.
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2009). Therefore, in recent years, a lot of computerized system of BAA has been developed especially for TW2 method due to its nature that is more suitable for computational execution (Pietka et al. 2001; Hsieh et al. 2007; Thodberg et al. 2009a, b). However, this kind of computerized system is still developing and far from being perfect due to the system instability and the need for manual operator to execute the system (Jonsson 2002). In this chapter, the aim is to discuss the very first step of this computerized system: the segmentation of hand bone.
2003). Substantial efforts have been devoted to research on the preprocessing of hand skeletal bone from background and soft tissue region. Most of the works involve the application of threshold setting which is considered ineffective in the hand bone segmentation due to the fact that the soft tissue region contains pixel intensity that similar to spongy bone of the hand skeletal bone (Smyth et al. 1997; Pietka et al. 2001; Aja-Fernández et al. 2004; Buie et al. 2007). Besides, most of the work, after obtaining the region of interest (ROI), implements the active contour model (Kass et al.
2000) c-means clustering algorithm, Gibbs random fields, and estimation of the intensity function have been proposed by Pietka et al. They also proposed Gao et al. (2010) segmentation of hand bone during preprocessing using the analysis on histogram. By inspecting the peak of the histogram, the authors identify the soft tissue region and the background. Hsieh et al. (2007) incorporate adaptive segmentation method with Gibbs random field at the preprocessing stage. Zhang et al. (2007) suggest segmenting the carpal by non-liner filter as preprocessing follows by adaptive image threshold setting, binary image labeling, and small object removal.