Segmentation of Liver in Low-Contrast Images Using K-Means Clustering and Geodesic Active Contour Algorithms.
Amir Hossein ForuzanYen-Wei ChenReza Aghaeizadeh ZoroofiAkira FurukawaYoshinobu SatoMasatoshi HoriNoriyuki TomiyamaPublished in: IEICE Trans. Inf. Syst. (2013)
Keyphrases
- low contrast
- high contrast
- accurate segmentation
- fully automatic
- cell segmentation
- gray value
- cell nuclei
- geodesic active contours
- image gradient
- prior shape knowledge
- watershed transform
- segmentation algorithm
- segmentation method
- image analysis
- background noise
- level set
- image segmentation
- contrast enhancement
- mr images
- edge detection
- high noise
- test images
- speckle noise
- image data
- automatic segmentation
- enhanced image
- image registration
- blood vessels
- segmented images
- phase contrast
- input image
- intensity variations
- multiple objects
- multiscale
- medical images
- active contours
- automated analysis
- imaging modalities
- gray level
- energy function
- image quality
- co occurrence
- image enhancement
- region growing
- computational complexity
- shape prior