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1. Osteoporosis
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Over the 50 percents of women who are older than 45
years have osteoporosis
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People hardly recognize this disease by themselves
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Measuring BMD(Bone Mineral Density) have been done
widely to detect osteoporosis in the early stage
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To measure BMD correctly, it is important to segment
bone area and measure de-noised biomedical signal
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2. Mammography
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X-ray image is obtained from absorption or scattering
effect of photons that is emitted from X-ray energy source based on
characteristic or distribution of materials that consist of the object
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DEXA is the method based on two different X-ray energy
levels obtained high energy and low energy level
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¡¡DEXA is an effective tool to minimize anatomic noise
which is main problem in medical X-ray analysis by two district X-ray
energy images
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Fig 1. Principle of DEXA Image
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3. Body DEXA Image Decomposition based on Attenuation
Coefficient
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Materials composing human body roughly divide into bone
and soft tissue region which have the unique attenuation coefficient
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Attenuation in permeation of X-ray can be represented by
combination of bone and soft tissue
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Fig 2. DEXA Image Decomposition
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4. DEXA Image Noise Modeling and Reduction
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A) DEXA image noise modeling
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DEXA image noise modeling based on the analysis of
characteristics of system input/output noise
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DEXA image noise model
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1)Source noise
characteristics of DEXA image
2)Detector noise
characteristics of DEXA image
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B) DEXA Image Denoising
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Noise exists multiplicative and linear additive noise in DEXA image
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Denoising method consists of two : Linear noise
reduction and multiplicative noise reduction using logarithm and
wavelet shrinkage method
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Fig 3. DEXA Image Noise Reduction Method
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Example of Denoised DEXA Image
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5. Segmentation for distal radius bone
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Active
Shape Model (ASM) is effective technique in bone segmentation
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Chamfer
matching find the initial
rotation, scale, and translation of ASM
segmentation
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Using
DXA decomposition, we eliminate effect of the soft tissue
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Weight
based on decomposition provide the solution for multi edge problem for
ASM in distal radius bone
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Fig 4. ASM segmentation system in multi edge environment
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Segmemtation Result for example image
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Fig 6. Segmentation result
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