Analyzing the evolution of breast tumors through flow fields and strain tensors

•We propose a method to quantify and visualize the changes of breast tumors.•Flow fields and strain tensors were used in this method.•We used OWA operators to aggregate robust optical flow methods.•The proposed method provides a good quantification and visualization of breast tumor. [Display omitted...

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Bibliographic Details
Published in:Pattern recognition letters 2017-07, Vol.93, p.162-171
Main Authors: Abdel-Nasser, Mohamed, Moreno, Antonio, A. Rashwan, Hatem, Puig, Domenec
Format: Article
Language:English
Subjects:
Biomarkers
Breast cancer
Chemotherapy
Computer programs
Error analysis
Ground truth
Health services
Landmarks
Mathematical analysis
Optical flow
Optical flow (image analysis)
OWA operators
Pathology
Physicians
Software
Statistical analysis
Strain tensors
Tensors
Tumors
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Summary:•We propose a method to quantify and visualize the changes of breast tumors.•Flow fields and strain tensors were used in this method.•We used OWA operators to aggregate robust optical flow methods.•The proposed method provides a good quantification and visualization of breast tumor. [Display omitted] Breast cancer is one of the most perilous diseases that annually attack thousands of women. Physicians usually monitor the breast tumor changes during the course of a chemotherapy treatment. Computer programs may help physicians to predict the pathological response in order to adjust the medical treatment to produce the intended effects. This paper proposes a method for quantifying and visualizing the changes of breast tumors of cases undergoing medical treatment through strain tensors. The proposed method determines the displacement fields between each follow-up mammogram and its baseline. To compute the displacement fields, we evaluated the performance of eight robust and recent optical flow methods through landmark-based error and statistical analysis. Since, there is no ground truth to evaluate the optical flow methods when they are applied to mammograms, we propose to aggregate the best optical flow methods using ordered weighted averaging operators. The aggregated optical flow methods using the ‘as many as possible’ operator yields the smallest landmark-based error among three aggregation approaches analyzed with the proposed algorithm. The resulting optical flow is then used to estimate the strain tensors. The proposed method provides a good quantification and visualization for breast tumor changes and that helps physicians to plan treatment for their patients.
ISSN:0167-8655
1872-7344
DOI:10.1016/j.patrec.2016.11.003