Maximum precision closed-form solution for localizing diffraction-limited spots in noisy images.
Super-resolution techniques like PALM and STORM require accurate localization of single fluorophores detected using a CCD. Popular localization algorithms inefficiently assume each photon registered by a pixel can only come from an area in the specimen corresponding to that pixel (not from neighbori...
| Main Authors: | , |
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| 格式: | Journal article |
| 語言: | English |
| 出版: |
2012
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| _version_ | 1826299654525943808 |
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| author | Larkin, J Cook, P |
| author_facet | Larkin, J Cook, P |
| author_sort | Larkin, J |
| collection | OXFORD |
| description | Super-resolution techniques like PALM and STORM require accurate localization of single fluorophores detected using a CCD. Popular localization algorithms inefficiently assume each photon registered by a pixel can only come from an area in the specimen corresponding to that pixel (not from neighboring areas), before iteratively (slowly) fitting a Gaussian to pixel intensity; they fail with noisy images. We present an alternative; a probability distribution extending over many pixels is assigned to each photon, and independent distributions are joined to describe emitter location. We compare algorithms, and recommend which serves best under different conditions. At low signal-to-noise ratios, ours is 2-fold more precise than others, and 2 orders of magnitude faster; at high ratios, it closely approximates the maximum likelihood estimate. |
| first_indexed | 2024-03-07T05:05:14Z |
| format | Journal article |
| id | oxford-uuid:d9b3d985-aab2-4bdb-9c04-912a28b46271 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T05:05:14Z |
| publishDate | 2012 |
| record_format | dspace |
| spelling | oxford-uuid:d9b3d985-aab2-4bdb-9c04-912a28b462712022-03-27T08:57:47ZMaximum precision closed-form solution for localizing diffraction-limited spots in noisy images.Journal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:d9b3d985-aab2-4bdb-9c04-912a28b46271EnglishSymplectic Elements at Oxford2012Larkin, JCook, PSuper-resolution techniques like PALM and STORM require accurate localization of single fluorophores detected using a CCD. Popular localization algorithms inefficiently assume each photon registered by a pixel can only come from an area in the specimen corresponding to that pixel (not from neighboring areas), before iteratively (slowly) fitting a Gaussian to pixel intensity; they fail with noisy images. We present an alternative; a probability distribution extending over many pixels is assigned to each photon, and independent distributions are joined to describe emitter location. We compare algorithms, and recommend which serves best under different conditions. At low signal-to-noise ratios, ours is 2-fold more precise than others, and 2 orders of magnitude faster; at high ratios, it closely approximates the maximum likelihood estimate. |
| spellingShingle | Larkin, J Cook, P Maximum precision closed-form solution for localizing diffraction-limited spots in noisy images. |
| title | Maximum precision closed-form solution for localizing diffraction-limited spots in noisy images. |
| title_full | Maximum precision closed-form solution for localizing diffraction-limited spots in noisy images. |
| title_fullStr | Maximum precision closed-form solution for localizing diffraction-limited spots in noisy images. |
| title_full_unstemmed | Maximum precision closed-form solution for localizing diffraction-limited spots in noisy images. |
| title_short | Maximum precision closed-form solution for localizing diffraction-limited spots in noisy images. |
| title_sort | maximum precision closed form solution for localizing diffraction limited spots in noisy images |
| work_keys_str_mv | AT larkinj maximumprecisionclosedformsolutionforlocalizingdiffractionlimitedspotsinnoisyimages AT cookp maximumprecisionclosedformsolutionforlocalizingdiffractionlimitedspotsinnoisyimages |