2009 International Joint Conference on Neural Networks 2009
DOI: 10.1109/ijcnn.2009.5178627
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Evaluation and visual exploratory analysis of DCE-MRI Data of breast lesions based on morphological features and novel dimension reduction methods

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Cited by 4 publications
(3 citation statements)
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“…Furthermore, non-mass-enhancing lesions such as DCIS or ICS can be better differentiated based on morphological properties [25]. In a previous work [37], we have considered features that describe the geometric characteristics of the shape and local moments such as Krawtchouk to identify the non-smooth surface.…”
Section: Morphological Featuresmentioning
confidence: 99%
“…Furthermore, non-mass-enhancing lesions such as DCIS or ICS can be better differentiated based on morphological properties [25]. In a previous work [37], we have considered features that describe the geometric characteristics of the shape and local moments such as Krawtchouk to identify the non-smooth surface.…”
Section: Morphological Featuresmentioning
confidence: 99%
“…Furthermore, non-mass enhancing lesions such as DCIS or ICS can be better differentiated based on morphologic properties [20]. In the previous work [21], we have considered features that describe the geometric characteristics of the shape and local moments such as that of Krawtchouk to identify the non-smooth surface.…”
Section: Features Describing the Lesion Morphologymentioning
confidence: 99%
“…Furthermore, non-mass enhancing lesions such as DCIS or ICS can be better differentiated based on morphological properties. 8 In previous work, 9 we have considered features that describe the geometric characteristics of the shape and local moments such as Krawtchouk to identify the non-smooth surface.…”
Section: Features Describing the Lesion Morphologymentioning
confidence: 99%