2007
DOI: 10.1016/j.compmedimag.2007.06.004
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Computerized segmentation and diagnostics of whole-body bone scintigrams

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Cited by 17 publications
(14 citation statements)
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“…An alternative approach for lesion extraction was proposed by Shiraishi et al [10], who presented a temporal subtraction-based interval change detection algorithm. Sajn et al [11] proposed a classification method to classify a bone scan examination into no pathology or pathology using support vector machine with features derived from segmented bones. Sadik et al [12][13][14] presented several algorithms which addressed skeleton segmentation, hot spot detection and classification of bone scan examinations.…”
Section: Introductionmentioning
confidence: 99%
“…An alternative approach for lesion extraction was proposed by Shiraishi et al [10], who presented a temporal subtraction-based interval change detection algorithm. Sajn et al [11] proposed a classification method to classify a bone scan examination into no pathology or pathology using support vector machine with features derived from segmented bones. Sadik et al [12][13][14] presented several algorithms which addressed skeleton segmentation, hot spot detection and classification of bone scan examinations.…”
Section: Introductionmentioning
confidence: 99%
“…With normal Canny edge filter too many peaks were obtained. Our approach is based on orthogonal twoway Gaussian filtering [12]. The algorithm (1) works as shown in the pseudocode.…”
Section: The Algorithmmentioning
confidence: 99%
“…thresholds, spatial and intensity ratios) were initially set by physicians and further refined on a separate tuning set. More details can be found in [12].…”
Section: Figure 1: Examples Of Body Scan Varietymentioning
confidence: 99%
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“…For instance, previous work on bone segmentation with 99m Tc bone scintigrams in [26,27] based on detecting edges is not applicable as a general rule in paediatric neuroblastoma 123 I-mIBG scintigraphies because bones are not always visible. Skeletal uptake is only visible in neuroblastoma in those patients with bone metastases.…”
Section: Related Workmentioning
confidence: 99%