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 ebook offers the latest findings and information in complicated diagnostics know-how, protecting a large spectrum together with mind task research, breast and lung melanoma detection, echocardiography, machine aided skeletal overview to mitochondrial biology imaging on the mobile point. The authors explored magneto acoustic techniques and tissue elasticity imaging for the aim of breast melanoma detection. views in fetal echocardiography from a picture processing perspective are integrated. Diagnostic imaging within the box of mitochondrial ailments in addition to using Computer-Aided approach (CAD) also are mentioned within the booklet. This publication may be worthy for college students, academics or expert researchers within the box of biomedical sciences and photo processing.
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Extra resources for Advances in Medical Diagnostic Technology
Transform the manual and rigid adaptive division scheme into an automated adaptive quadruple division scheme that embodies human cognitive ability. This transformation is significant not only in a narrow sense of hand bone segmentation, but most importantly, it is of a generic breakthrough in the field of image segmentation. This implicit modeling of human intuition and prior knowledge solves the problem of high dependency on explicit human resources to operate the algorithm. Furthermore, the scheme itself is a building block or framework for other segmentation algorithm to determine the optimum region size for algorithm implementation.
Fuzzy quadruple division scheme to optimize the central segmentation algorithm, and finally, the process ends with an additional quality assurance scheme. The designed segmentation framework works without the need of resources such as training sets and skillful operator. The quantitative and qualitative analysis of the resultant images have both shown that the designed framework is capable of separating the soft tissue and background from the hand bone with relatively high accuracy despite omitting the above-mentioned resources.
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. However, it involves user-specified threshold and Canny edge detection that are not robust in segmentation.
Advances in Medical Diagnostic Technology 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