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Multi-Focus Image Fusion for Full-Field Optical Angiography
by
Li, Xiaosong
, Tan, Haishu
, Jie, Yuchan
, Wang, Mingyi
in
Algorithms
/ Angiography
/ Bandpass
/ Biological research
/ Blood flow
/ Computer vision
/ contrast spatial frequency
/ Datasets
/ Depth of field
/ Design
/ Dictionaries
/ full-field optical angiography
/ Image acquisition
/ Image contrast
/ image fusion
/ Image reconstruction
/ Imaging techniques
/ Medical imaging
/ Medical imaging equipment
/ nonsubsampled contourlet transform
/ sparse representation
/ Tissues
2023
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Multi-Focus Image Fusion for Full-Field Optical Angiography
by
Li, Xiaosong
, Tan, Haishu
, Jie, Yuchan
, Wang, Mingyi
in
Algorithms
/ Angiography
/ Bandpass
/ Biological research
/ Blood flow
/ Computer vision
/ contrast spatial frequency
/ Datasets
/ Depth of field
/ Design
/ Dictionaries
/ full-field optical angiography
/ Image acquisition
/ Image contrast
/ image fusion
/ Image reconstruction
/ Imaging techniques
/ Medical imaging
/ Medical imaging equipment
/ nonsubsampled contourlet transform
/ sparse representation
/ Tissues
2023
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Multi-Focus Image Fusion for Full-Field Optical Angiography
by
Li, Xiaosong
, Tan, Haishu
, Jie, Yuchan
, Wang, Mingyi
in
Algorithms
/ Angiography
/ Bandpass
/ Biological research
/ Blood flow
/ Computer vision
/ contrast spatial frequency
/ Datasets
/ Depth of field
/ Design
/ Dictionaries
/ full-field optical angiography
/ Image acquisition
/ Image contrast
/ image fusion
/ Image reconstruction
/ Imaging techniques
/ Medical imaging
/ Medical imaging equipment
/ nonsubsampled contourlet transform
/ sparse representation
/ Tissues
2023
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Multi-Focus Image Fusion for Full-Field Optical Angiography
Journal Article
Multi-Focus Image Fusion for Full-Field Optical Angiography
2023
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Overview
Full-field optical angiography (FFOA) has considerable potential for clinical applications in the prevention and diagnosis of various diseases. However, owing to the limited depth of focus attainable using optical lenses, only information about blood flow in the plane within the depth of field can be acquired using existing FFOA imaging techniques, resulting in partially unclear images. To produce fully focused FFOA images, an FFOA image fusion method based on the nonsubsampled contourlet transform and contrast spatial frequency is proposed. Firstly, an imaging system is constructed, and the FFOA images are acquired by intensity-fluctuation modulation effect. Secondly, we decompose the source images into low-pass and bandpass images by performing nonsubsampled contourlet transform. A sparse representation-based rule is introduced to fuse the lowpass images to effectively retain the useful energy information. Meanwhile, a contrast spatial frequency rule is proposed to fuse bandpass images, which considers the neighborhood correlation and gradient relationships of pixels. Finally, the fully focused image is produced by reconstruction. The proposed method significantly expands the range of focus of optical angiography and can be effectively extended to public multi-focused datasets. Experimental results confirm that the proposed method outperformed some state-of-the-art methods in both qualitative and quantitative evaluations.
Publisher
MDPI AG,MDPI
Subject
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