Tongue Image Alignment via Conformal Mapping for Disease Detection
Tongue image analysis has been an active study in medical imaging. Existing tongue image processing approaches deal with the issue of image alignment in oversimplified ways. These approaches mainly extract patches or simple regions on pre-defined positions, which are severely sensitive to tongue def...
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IEEE
2020-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/8936408/ |
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| author | Jian Wu Bob Zhang Yong Xu David Zhang |
| author_facet | Jian Wu Bob Zhang Yong Xu David Zhang |
| author_sort | Jian Wu |
| collection | DOAJ |
| description | Tongue image analysis has been an active study in medical imaging. Existing tongue image processing approaches deal with the issue of image alignment in oversimplified ways. These approaches mainly extract patches or simple regions on pre-defined positions, which are severely sensitive to tongue deformations. In this paper, we present a conformal mapping method for tongue image alignment, the principle of which is to determine the interior mapping based on the boundary mapping so that it is robust to the deformations. The conformal alignment consists of two stages: the mapping on the boundary is firstly established via the Fourier descriptor before the mapping is extended onto the interior region via Cauchy’s integral and finite-difference method. Average tongues and eigen-tongues are constructed based on the conformal alignment for feature extraction. Experiments show that the proposed alignment is robust against tongue deformations and can be employed to correct existing rigid partition methods. Numerical evaluations on time efficiency and accuracy also show that our method is considerably fast and very accurate, compared with several baseline methods in this field. For the task of disease detection, the features based on the aligned images outperform some state-of-the-art features. The results reveal that the proposed method provides an efficient and accurate tool for deformable medical image alignment and disease diagnosis. A MatLab script of the proposed algorithm is available on <monospace><uri>https://codeocean.com/capsule/4382908/tree/v1</uri></monospace>. |
| format | Article |
| id | doaj-art-4efce4c2cd5146c3b6067af4a926df90 |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-4efce4c2cd5146c3b6067af4a926df902025-01-15T00:01:10ZengIEEEIEEE Access2169-35362020-01-0189796980810.1109/ACCESS.2019.29605788936408Tongue Image Alignment via Conformal Mapping for Disease DetectionJian Wu0https://orcid.org/0000-0003-0421-0112Bob Zhang1Yong Xu2https://orcid.org/0000-0003-0530-2123David Zhang3https://orcid.org/0000-0002-5027-5286School of Computer Science and Technology, Harbin Institute of Technology at Shenzhen, Shenzhen, ChinaDepartment of Computer and Information Science, University of Macau, Macau, ChinaSchool of Computer Science and Technology, Harbin Institute of Technology at Shenzhen, Shenzhen, ChinaSchool of Science and Engineering, The Chinese University of Hong Kong at Shenzhen, Shenzhen, ChinaTongue image analysis has been an active study in medical imaging. Existing tongue image processing approaches deal with the issue of image alignment in oversimplified ways. These approaches mainly extract patches or simple regions on pre-defined positions, which are severely sensitive to tongue deformations. In this paper, we present a conformal mapping method for tongue image alignment, the principle of which is to determine the interior mapping based on the boundary mapping so that it is robust to the deformations. The conformal alignment consists of two stages: the mapping on the boundary is firstly established via the Fourier descriptor before the mapping is extended onto the interior region via Cauchy’s integral and finite-difference method. Average tongues and eigen-tongues are constructed based on the conformal alignment for feature extraction. Experiments show that the proposed alignment is robust against tongue deformations and can be employed to correct existing rigid partition methods. Numerical evaluations on time efficiency and accuracy also show that our method is considerably fast and very accurate, compared with several baseline methods in this field. For the task of disease detection, the features based on the aligned images outperform some state-of-the-art features. The results reveal that the proposed method provides an efficient and accurate tool for deformable medical image alignment and disease diagnosis. A MatLab script of the proposed algorithm is available on <monospace><uri>https://codeocean.com/capsule/4382908/tree/v1</uri></monospace>.https://ieeexplore.ieee.org/document/8936408/Image alignmentconformal mappingdisease detection |
| spellingShingle | Jian Wu Bob Zhang Yong Xu David Zhang Tongue Image Alignment via Conformal Mapping for Disease Detection IEEE Access Image alignment conformal mapping disease detection |
| title | Tongue Image Alignment via Conformal Mapping for Disease Detection |
| title_full | Tongue Image Alignment via Conformal Mapping for Disease Detection |
| title_fullStr | Tongue Image Alignment via Conformal Mapping for Disease Detection |
| title_full_unstemmed | Tongue Image Alignment via Conformal Mapping for Disease Detection |
| title_short | Tongue Image Alignment via Conformal Mapping for Disease Detection |
| title_sort | tongue image alignment via conformal mapping for disease detection |
| topic | Image alignment conformal mapping disease detection |
| url | https://ieeexplore.ieee.org/document/8936408/ |
| work_keys_str_mv | AT jianwu tongueimagealignmentviaconformalmappingfordiseasedetection AT bobzhang tongueimagealignmentviaconformalmappingfordiseasedetection AT yongxu tongueimagealignmentviaconformalmappingfordiseasedetection AT davidzhang tongueimagealignmentviaconformalmappingfordiseasedetection |