Title
Simultaneous segmentation and bias field estimation using local fitted images.
Abstract
•In this paper, a new region-based active contour model is proposed by defining a hybrid region image fitting (HRIF) energy functional based on two different local fitted images.•Two different local fitted images are constructed to approximate the original image and its square version, respectively. The first fitted image is an extension version of local fitted image (LFI) defined in paper “K.H. Zhang, H.H. Song, L. Zhang, Active contours driven by local image fitting energy, Pattern Recognition, 43 (4) (2010) 1199–1206“ and called extended fitted image (EFI); the second one is originally introduced and called square fitted image (SFI).•Experimental results on synthetic images and a publicly available dataset demonstrate that the proposed model has the capability of handling intensity inhomogeneity and is competent for segmenting the regions of interest and estimating the bias field.
Year
DOI
Venue
2018
10.1016/j.patcog.2017.08.031
Pattern Recognition
Keywords
Field
DocType
Level set,Image segmentation,Local fitted images,Intensity inhomogeneity,Bias field
Computer vision,Scale-space segmentation,Pattern recognition,Segmentation,Level set method,Level set,Image segmentation,Artificial intelligence,Energy functional,Mathematics,Bias field
Journal
Volume
Issue
ISSN
74
C
0031-3203
Citations 
PageRank 
References 
4
0.39
26
Authors
6
Name
Order
Citations
PageRank
Lei Wang1401111.60
Jianbing Zhu280.81
Mao Sheng340.39
Adriena Cribb440.39
Shaocheng Zhu540.39
Jiantao Pu627723.12