Computerized analysis of mammographic parenchymal patterns using fractal analysis

Li, Hui; Giger, Maryellen L.; Huo, Zhimin; Olopade, Olufunmilayo I.; Chinander, Michael R.; Li, Lan; Bonta, Ioana

doi:10.1117/12.481359

Cited by 1 publication

(2 citation statements)

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“…The first feature, which will be called ''fractal dimension,'' was calculated using the box-counting technique. 4,19,20 The surface area of each ROI was calculated with gray level of the effective pixel being regarded as height and effective pixel size being regarded as length and width. This area was calculated using all possible square effective pixel sizes, starting with the pixel size itself.…”

Section: Fractal-based Feature Calculationmentioning

confidence: 99%

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Comparison of radiographic texture analysis from computed radiography and bone densitometry systems

et al. 2004

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Osteoporosis is a disease that results in an increased risk of bone fracture due to a loss of bone mass and deterioration of bone structure. Bone mineral density (BMD) provides a measure of bone mass and is frequently measured by bone densitometry systems to diagnose osteoporosis. In addition, computerized radiographic texture analysis (RTA) is currently being investigated as a measure of bone structure and as an additional diagnostic predictor of osteoporosis. In this study, we assessed the ability of a peripheral bone densitometry (PD) system to yield images useful for RTA. The benefit of such a system is that it measures BMD by dual-energy x-ray absorptiometry and therefore provides high- and low-energy digital radiographic images. The bone densitometry system investigated was the GE/Lunar PIXI, which provides 512 x 512 digital images of the heel or forearm (0.2 mm pixels). We compared texture features of heel images obtained with this PD system to those obtained on a Fuji computed radiography (CR) system (0.1 mm pixels). Fourier and fractal-based texture features of images from 24 subjects who had both CR and BMD exams were calculated, and correlation between the two systems was analyzed. Fourier-based texture features characterize the magnitude, frequency content, and orientation of the trabecular bone pattern. Good correlation was found between the two modalities for the first moment (FMP) with r=0.71 (p value<0.0001) and for minimum FMP with r=0.52 (p value=0.008). Root-mean-square (RMS) did not correlate with r=0.31 (p value>0.05), while the standard deviation of the RMS did correlate with r=0.79 (p value<0.0001). Good correlation was also found between the two modalities for the fractal-based texture features with r=0.79 (p value<0.0001) for the global Minkowski dimension and r=0.63 (p value=0.0007) for the fractal dimension from a box counting method. The PD system therefore may have the potential for yielding heel images suitable for RTA.

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Section: Fractal-based Feature Calculationmentioning

confidence: 99%

“…The second fractal-based texture feature employs the global Minkowski dimension, 7,19,20 which is based on ''volume'' differences between two processed versions of an ROI using morphological operators. This volume difference, V g (r) is calculated by…”

Section: Fractal-based Feature Calculationmentioning

confidence: 99%