1998
DOI: 10.2214/ajr.171.6.9843308
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Quantitative analysis of pulmonary emphysema: three-dimensional fractal analysis of single-photon emission computed tomography images obtained with a carbon particle radioaerosol.

Abstract: OBJECTIVE. Thepurpose ofthisstudy wastoquantify theheterogeneous distribution of a carbon particle radioaerosol in the lungs of patients with pulmonary emphysema using sin gle-photon emission computed tomography (SPECT) and fractal analysis.

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Cited by 25 publications
(31 citation statements)
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“…As described previously [27,28], familiar matrices from classical geometry such as length, area, and volume depend on the scale at which we decide to examine an object. In fractal geometry, the relationship between a measure (M) and the scale (a) is expressed as…”
Section: S Fractal Analysismentioning
confidence: 99%
“…As described previously [27,28], familiar matrices from classical geometry such as length, area, and volume depend on the scale at which we decide to examine an object. In fractal geometry, the relationship between a measure (M) and the scale (a) is expressed as…”
Section: S Fractal Analysismentioning
confidence: 99%
“…Each patch has overlap with marked ROI. It can be understood from the work [4], [5], [11], [12] that GLCM, GLRLM and histogram of local binary patterns can give more discriminative information about ILD patterns. Fig.…”
Section: Proposed Methodsmentioning
confidence: 99%
“…[19] proposed texture classification, based on wavelet features. Also various study has been carried out on classification of ILD patterns using textural information [3]- [5][6], [7]. Information from HRCT scan can be used to accurately classify the ILD patterns.…”
Section: Introductionmentioning
confidence: 99%
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“…ttempts have been made to quantify the spatial distribution of radioaerosol in the lungs during ventilation nuclear medicine examinations for the diagnosis of pulmonary diseases such as emphysema [1][2][3]. In pulmonary emphysema with functional impairments of the alveoli, ventilation images indicate focal areas of decreasing pixel intensity [4].…”
mentioning
confidence: 99%