An adaptive non-local means filter for denoising live-cell images and improving particle detection.
Fluorescence imaging of dynamical processes in live cells often results in a low signal-to-noise ratio. We present a novel feature-preserving non-local means approach to denoise such images to improve feature recovery and particle detection. The commonly used non-local means filter is not optimal fo...
| Main Authors: | , , , , , , |
|---|---|
| Format: | Journal article |
| Language: | English |
| Published: |
2010
|
| _version_ | 1797083645828136960 |
|---|---|
| author | Yang, L Parton, R Ball, G Qiu, Z Greenaway, A Davis, I Lu, W |
| author_facet | Yang, L Parton, R Ball, G Qiu, Z Greenaway, A Davis, I Lu, W |
| author_sort | Yang, L |
| collection | OXFORD |
| description | Fluorescence imaging of dynamical processes in live cells often results in a low signal-to-noise ratio. We present a novel feature-preserving non-local means approach to denoise such images to improve feature recovery and particle detection. The commonly used non-local means filter is not optimal for noisy biological images containing small features of interest because image noise prevents accurate determination of the correct coefficients for averaging, leading to over-smoothing and other artifacts. Our adaptive method addresses this problem by constructing a particle feature probability image, which is based on Haar-like feature extraction. The particle probability image is then used to improve the estimation of the correct coefficients for averaging. We show that this filter achieves higher peak signal-to-noise ratio in denoised images and has a greater capability in identifying weak particles when applied to synthetic data. We have applied this approach to live-cell images resulting in enhanced detection of end-binding-protein 1 foci on dynamically extending microtubules in photo-sensitive Drosophila tissues. We show that our feature-preserving non-local means filter can reduce the threshold of imaging conditions required to obtain meaningful data. |
| first_indexed | 2024-03-07T01:44:22Z |
| format | Journal article |
| id | oxford-uuid:97ebce26-1a07-4c70-a6f5-6577972e5b66 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T01:44:22Z |
| publishDate | 2010 |
| record_format | dspace |
| spelling | oxford-uuid:97ebce26-1a07-4c70-a6f5-6577972e5b662022-03-27T00:03:18ZAn adaptive non-local means filter for denoising live-cell images and improving particle detection.Journal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:97ebce26-1a07-4c70-a6f5-6577972e5b66EnglishSymplectic Elements at Oxford2010Yang, LParton, RBall, GQiu, ZGreenaway, ADavis, ILu, WFluorescence imaging of dynamical processes in live cells often results in a low signal-to-noise ratio. We present a novel feature-preserving non-local means approach to denoise such images to improve feature recovery and particle detection. The commonly used non-local means filter is not optimal for noisy biological images containing small features of interest because image noise prevents accurate determination of the correct coefficients for averaging, leading to over-smoothing and other artifacts. Our adaptive method addresses this problem by constructing a particle feature probability image, which is based on Haar-like feature extraction. The particle probability image is then used to improve the estimation of the correct coefficients for averaging. We show that this filter achieves higher peak signal-to-noise ratio in denoised images and has a greater capability in identifying weak particles when applied to synthetic data. We have applied this approach to live-cell images resulting in enhanced detection of end-binding-protein 1 foci on dynamically extending microtubules in photo-sensitive Drosophila tissues. We show that our feature-preserving non-local means filter can reduce the threshold of imaging conditions required to obtain meaningful data. |
| spellingShingle | Yang, L Parton, R Ball, G Qiu, Z Greenaway, A Davis, I Lu, W An adaptive non-local means filter for denoising live-cell images and improving particle detection. |
| title | An adaptive non-local means filter for denoising live-cell images and improving particle detection. |
| title_full | An adaptive non-local means filter for denoising live-cell images and improving particle detection. |
| title_fullStr | An adaptive non-local means filter for denoising live-cell images and improving particle detection. |
| title_full_unstemmed | An adaptive non-local means filter for denoising live-cell images and improving particle detection. |
| title_short | An adaptive non-local means filter for denoising live-cell images and improving particle detection. |
| title_sort | adaptive non local means filter for denoising live cell images and improving particle detection |
| work_keys_str_mv | AT yangl anadaptivenonlocalmeansfilterfordenoisinglivecellimagesandimprovingparticledetection AT partonr anadaptivenonlocalmeansfilterfordenoisinglivecellimagesandimprovingparticledetection AT ballg anadaptivenonlocalmeansfilterfordenoisinglivecellimagesandimprovingparticledetection AT qiuz anadaptivenonlocalmeansfilterfordenoisinglivecellimagesandimprovingparticledetection AT greenawaya anadaptivenonlocalmeansfilterfordenoisinglivecellimagesandimprovingparticledetection AT davisi anadaptivenonlocalmeansfilterfordenoisinglivecellimagesandimprovingparticledetection AT luw anadaptivenonlocalmeansfilterfordenoisinglivecellimagesandimprovingparticledetection AT yangl adaptivenonlocalmeansfilterfordenoisinglivecellimagesandimprovingparticledetection AT partonr adaptivenonlocalmeansfilterfordenoisinglivecellimagesandimprovingparticledetection AT ballg adaptivenonlocalmeansfilterfordenoisinglivecellimagesandimprovingparticledetection AT qiuz adaptivenonlocalmeansfilterfordenoisinglivecellimagesandimprovingparticledetection AT greenawaya adaptivenonlocalmeansfilterfordenoisinglivecellimagesandimprovingparticledetection AT davisi adaptivenonlocalmeansfilterfordenoisinglivecellimagesandimprovingparticledetection AT luw adaptivenonlocalmeansfilterfordenoisinglivecellimagesandimprovingparticledetection |