Document Detail


A new background distribution-based active contour model for three-dimensional lesion segmentation in breast DCE-MRI.
MedLine Citation:
PMID:  25086552     Owner:  NLM     Status:  In-Data-Review    
Abstract/OtherAbstract:
PURPOSE: To develop and evaluate a computerized semiautomatic segmentation method for accurate extraction of three-dimensional lesions from dynamic contrast-enhanced magnetic resonance images (DCE-MRIs) of the breast.
METHODS: The authors propose a new background distribution-based active contour model using level set (BDACMLS) to segment lesions in breast DCE-MRIs. The method starts with manual selection of a region of interest (ROI) that contains the entire lesion in a single slice where the lesion is enhanced. Then the lesion volume from the volume data of interest, which is captured automatically, is separated. The core idea of BDACMLS is a new signed pressure function which is based solely on the intensity distribution combined with pathophysiological basis. To compare the algorithm results, two experienced radiologists delineated all lesions jointly to obtain the ground truth. In addition, results generated by other different methods based on level set (LS) are also compared with the authors' method. Finally, the performance of the proposed method is evaluated by several region-based metrics such as the overlap ratio.
RESULTS: Forty-two studies with 46 lesions that contain 29 benign and 17 malignant lesions are evaluated. The dataset includes various typical pathologies of the breast such as invasive ductal carcinoma, ductal carcinomain situ, scar carcinoma, phyllodes tumor, breast cysts, fibroadenoma, etc. The overlap ratio for BDACMLS with respect to manual segmentation is 79.55% ± 12.60% (mean ± s.d.).
CONCLUSIONS: A new active contour model method has been developed and shown to successfully segment breast DCE-MRI three-dimensional lesions. The results from this model correspond more closely to manual segmentation, solve the weak-edge-passed problem, and improve the robustness in segmenting different lesions.
Authors:
Hui Liu; Yiping Liu; Zuowei Zhao; Lina Zhang; Tianshuang Qiu
Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Medical physics     Volume:  41     ISSN:  0094-2405     ISO Abbreviation:  Med Phys     Publication Date:  2014 Aug 
Date Detail:
Created Date:  2014-08-04     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  0425746     Medline TA:  Med Phys     Country:  United States    
Other Details:
Languages:  eng     Pagination:  082303     Citation Subset:  IM    
Export Citation:
APA/MLA Format     Download EndNote     Download BibTex
MeSH Terms
Descriptor/Qualifier:

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


Previous Document:  CT substitutes derived from MR images reconstructed with parallel imaging.
Next Document:  A 3D MR-acquisition scheme for nonrigid bulk motion correction in simultaneous PET-MR.