NDLI: Quantitative analysis of cell morphology based on the contourlet transform

Content Provider	IET Digital Library
Author	Huang, Yali Hu, Xuefang Hao, Lei Gao, Yuehua Liu, Zhiwen Wang, Peiguang
Abstract	Cellular morphology analysis has been widely used to detect abnormalities in biological processes. Clinicians have observed that lymphocytes become highly deformable under special conditions, particularly when graft rejection occurs. The characterisation of lymphocyte boundary deformation provides important quantitative parameters to assist clinical rejection diagnosis. To evaluate the dynamic features of the boundaries of target lymphocyte when a graft rejection occurs, a contourlet transform-based method is proposed to extract the characteristics of cell boundary variation. First, the lymphocyte is segmented and tracked to obtain their edge-to-centroid distance signals. Subsequently, a contourlet transform is performed on these signals, during which the edge-to-centroid distance signals of the lymphocyte is decomposed at multiple scales using the Laplacian pyramid; a multi-directional decomposition is then performed using a direction filter to merge the singularities distributed along the same direction and obtain the contourlet transform coefficients. Finally, statistical parameters of the cell dynamic boundaries are calculated, then fed into the support vector machine for classification of the cell deformation. Our findings demonstrate that contourlet transform has better performance in representing image features such as cell boundaries than wavelet transform for its prosperities of multi-scale and multi-directional decomposition for cell images.
Starting Page	2826
Ending Page	2832
Page Count	7
ISSN	17519659
Volume Number	14
e-ISSN	17519667
Issue Number	Issue 12, Oct (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/14/12
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2019.0909
Journal	IET Image Processing
Publisher Date	2020-05-06
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Biological Processes Biology And Medical Computing Biomedical Measurement And Imaging Cell Boundary Variation Cell Deformation Classification Cell Dynamic Boundaries Cell Image Cellular Biophysics Cellular Morphology Analysis Clinical Rejection Diagnosis Computer Vision And Image Processing Technique Contourlet Transform-based Method Direction Filter Edge-to-centroid Distance Signal Feature Extraction Function Theory And Analysis Graft Rejection Health Physics Image Classification Image Feature Representation Image Representation Image Segmentation Integral Transforms Knowledge Engineering Technique Laplacian Pyramid Lymphocyte Boundary Deformation Medical And Biomedical Uses of Field Medical Image Processing Multidirectional Decomposition Optical, Image And Video Signal Processing Patient Diagnostic Method And Instrumentation Probability Theory Quantitative Analysis Radiations Radioactivity Statistical Analysis Statistical Parameter Statistics Stochastic Linearised SCUC Support Vector Machine Wavelet Transform
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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