Quantitative differential phase contrast phase reconstruction for sparse samples
Quantitative differential phase contrast (qDPC) microscopy can achieve phase imaging of unlabeled cell samples with high spatial resolution. However, qDPC imaging is easily affected by the noise generated in the experiments. In this manuscript, the L0-norm regularization was introduced into qDPC pha...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Peng, Tao [verfasserIn] Ke, Zeyu [verfasserIn] Zhang, Shuhe [verfasserIn] He, Jun [verfasserIn] Wang, Peng [verfasserIn] Wang, Fengsong [verfasserIn] Zhong, Zhensheng [verfasserIn] Fang, Shu [verfasserIn] Shi, Hui [verfasserIn] Lu, Rongsheng [verfasserIn] Zhou, Jinhua [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2023 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Optics and lasers in engineering - Amsterdam [u.a.] : Elsevier Science, 1980, 163 |
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| Übergeordnetes Werk: |
volume:163 |
| DOI / URN: |
10.1016/j.optlaseng.2023.107478 |
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| Katalog-ID: |
ELV009196722 |
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| 520 | |a Quantitative differential phase contrast (qDPC) microscopy can achieve phase imaging of unlabeled cell samples with high spatial resolution. However, qDPC imaging is easily affected by the noise generated in the experiments. In this manuscript, the L0-norm regularization was introduced into qDPC phase reconstruction for sparse samples (L0-qDPC), including the quantitative phase target and cell samples. After the detailed comparison of phase fidelity, imaging contrast, resolution, and convergence rate, L0-qDPC method can provide a stable qDPC phase imaging without parameter adjustment for sparse samples due to strong constraint and good robustness of L0-norm based on sparse prior, compared with the L2-norm and total variation regularization. | ||
| 650 | 4 | |a Quantitative differential phase contrast imaging | |
| 650 | 4 | |a Phase reconstruction | |
| 650 | 4 | |a Regularization | |
| 650 | 4 | |a Image denoising | |
| 700 | 1 | |a Ke, Zeyu |e verfasserin |0 (orcid)0000-0003-4348-6808 |4 aut | |
| 700 | 1 | |a Zhang, Shuhe |e verfasserin |0 (orcid)0000-0002-3115-7364 |4 aut | |
| 700 | 1 | |a He, Jun |e verfasserin |4 aut | |
| 700 | 1 | |a Wang, Peng |e verfasserin |4 aut | |
| 700 | 1 | |a Wang, Fengsong |e verfasserin |4 aut | |
| 700 | 1 | |a Zhong, Zhensheng |e verfasserin |4 aut | |
| 700 | 1 | |a Fang, Shu |e verfasserin |4 aut | |
| 700 | 1 | |a Shi, Hui |e verfasserin |4 aut | |
| 700 | 1 | |a Lu, Rongsheng |e verfasserin |0 (orcid)0000-0002-9794-9428 |4 aut | |
| 700 | 1 | |a Zhou, Jinhua |e verfasserin |0 (orcid)0000-0002-3704-4459 |4 aut | |
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10.1016/j.optlaseng.2023.107478 doi (DE-627)ELV009196722 (ELSEVIER)S0143-8166(23)00007-6 DE-627 ger DE-627 rda eng 530 VZ 50.37 bkl Peng, Tao verfasserin (orcid)0000-0002-0120-924X aut Quantitative differential phase contrast phase reconstruction for sparse samples 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Quantitative differential phase contrast (qDPC) microscopy can achieve phase imaging of unlabeled cell samples with high spatial resolution. However, qDPC imaging is easily affected by the noise generated in the experiments. In this manuscript, the L0-norm regularization was introduced into qDPC phase reconstruction for sparse samples (L0-qDPC), including the quantitative phase target and cell samples. After the detailed comparison of phase fidelity, imaging contrast, resolution, and convergence rate, L0-qDPC method can provide a stable qDPC phase imaging without parameter adjustment for sparse samples due to strong constraint and good robustness of L0-norm based on sparse prior, compared with the L2-norm and total variation regularization. Quantitative differential phase contrast imaging Phase reconstruction Regularization Image denoising Ke, Zeyu verfasserin (orcid)0000-0003-4348-6808 aut Zhang, Shuhe verfasserin (orcid)0000-0002-3115-7364 aut He, Jun verfasserin aut Wang, Peng verfasserin aut Wang, Fengsong verfasserin aut Zhong, Zhensheng verfasserin aut Fang, Shu verfasserin aut Shi, Hui verfasserin aut Lu, Rongsheng verfasserin (orcid)0000-0002-9794-9428 aut Zhou, Jinhua verfasserin (orcid)0000-0002-3704-4459 aut Enthalten in Optics and lasers in engineering Amsterdam [u.a.] : Elsevier Science, 1980 163 Online-Ressource (DE-627)320405737 (DE-600)2000651-2 (DE-576)259484369 0143-8166 nnns volume:163 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 50.37 Technische Optik VZ AR 163 |
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10.1016/j.optlaseng.2023.107478 doi (DE-627)ELV009196722 (ELSEVIER)S0143-8166(23)00007-6 DE-627 ger DE-627 rda eng 530 VZ 50.37 bkl Peng, Tao verfasserin (orcid)0000-0002-0120-924X aut Quantitative differential phase contrast phase reconstruction for sparse samples 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Quantitative differential phase contrast (qDPC) microscopy can achieve phase imaging of unlabeled cell samples with high spatial resolution. However, qDPC imaging is easily affected by the noise generated in the experiments. In this manuscript, the L0-norm regularization was introduced into qDPC phase reconstruction for sparse samples (L0-qDPC), including the quantitative phase target and cell samples. After the detailed comparison of phase fidelity, imaging contrast, resolution, and convergence rate, L0-qDPC method can provide a stable qDPC phase imaging without parameter adjustment for sparse samples due to strong constraint and good robustness of L0-norm based on sparse prior, compared with the L2-norm and total variation regularization. Quantitative differential phase contrast imaging Phase reconstruction Regularization Image denoising Ke, Zeyu verfasserin (orcid)0000-0003-4348-6808 aut Zhang, Shuhe verfasserin (orcid)0000-0002-3115-7364 aut He, Jun verfasserin aut Wang, Peng verfasserin aut Wang, Fengsong verfasserin aut Zhong, Zhensheng verfasserin aut Fang, Shu verfasserin aut Shi, Hui verfasserin aut Lu, Rongsheng verfasserin (orcid)0000-0002-9794-9428 aut Zhou, Jinhua verfasserin (orcid)0000-0002-3704-4459 aut Enthalten in Optics and lasers in engineering Amsterdam [u.a.] : Elsevier Science, 1980 163 Online-Ressource (DE-627)320405737 (DE-600)2000651-2 (DE-576)259484369 0143-8166 nnns volume:163 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 50.37 Technische Optik VZ AR 163 |
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10.1016/j.optlaseng.2023.107478 doi (DE-627)ELV009196722 (ELSEVIER)S0143-8166(23)00007-6 DE-627 ger DE-627 rda eng 530 VZ 50.37 bkl Peng, Tao verfasserin (orcid)0000-0002-0120-924X aut Quantitative differential phase contrast phase reconstruction for sparse samples 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Quantitative differential phase contrast (qDPC) microscopy can achieve phase imaging of unlabeled cell samples with high spatial resolution. However, qDPC imaging is easily affected by the noise generated in the experiments. In this manuscript, the L0-norm regularization was introduced into qDPC phase reconstruction for sparse samples (L0-qDPC), including the quantitative phase target and cell samples. After the detailed comparison of phase fidelity, imaging contrast, resolution, and convergence rate, L0-qDPC method can provide a stable qDPC phase imaging without parameter adjustment for sparse samples due to strong constraint and good robustness of L0-norm based on sparse prior, compared with the L2-norm and total variation regularization. Quantitative differential phase contrast imaging Phase reconstruction Regularization Image denoising Ke, Zeyu verfasserin (orcid)0000-0003-4348-6808 aut Zhang, Shuhe verfasserin (orcid)0000-0002-3115-7364 aut He, Jun verfasserin aut Wang, Peng verfasserin aut Wang, Fengsong verfasserin aut Zhong, Zhensheng verfasserin aut Fang, Shu verfasserin aut Shi, Hui verfasserin aut Lu, Rongsheng verfasserin (orcid)0000-0002-9794-9428 aut Zhou, Jinhua verfasserin (orcid)0000-0002-3704-4459 aut Enthalten in Optics and lasers in engineering Amsterdam [u.a.] : Elsevier Science, 1980 163 Online-Ressource (DE-627)320405737 (DE-600)2000651-2 (DE-576)259484369 0143-8166 nnns volume:163 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 50.37 Technische Optik VZ AR 163 |
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10.1016/j.optlaseng.2023.107478 doi (DE-627)ELV009196722 (ELSEVIER)S0143-8166(23)00007-6 DE-627 ger DE-627 rda eng 530 VZ 50.37 bkl Peng, Tao verfasserin (orcid)0000-0002-0120-924X aut Quantitative differential phase contrast phase reconstruction for sparse samples 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Quantitative differential phase contrast (qDPC) microscopy can achieve phase imaging of unlabeled cell samples with high spatial resolution. However, qDPC imaging is easily affected by the noise generated in the experiments. In this manuscript, the L0-norm regularization was introduced into qDPC phase reconstruction for sparse samples (L0-qDPC), including the quantitative phase target and cell samples. After the detailed comparison of phase fidelity, imaging contrast, resolution, and convergence rate, L0-qDPC method can provide a stable qDPC phase imaging without parameter adjustment for sparse samples due to strong constraint and good robustness of L0-norm based on sparse prior, compared with the L2-norm and total variation regularization. Quantitative differential phase contrast imaging Phase reconstruction Regularization Image denoising Ke, Zeyu verfasserin (orcid)0000-0003-4348-6808 aut Zhang, Shuhe verfasserin (orcid)0000-0002-3115-7364 aut He, Jun verfasserin aut Wang, Peng verfasserin aut Wang, Fengsong verfasserin aut Zhong, Zhensheng verfasserin aut Fang, Shu verfasserin aut Shi, Hui verfasserin aut Lu, Rongsheng verfasserin (orcid)0000-0002-9794-9428 aut Zhou, Jinhua verfasserin (orcid)0000-0002-3704-4459 aut Enthalten in Optics and lasers in engineering Amsterdam [u.a.] : Elsevier Science, 1980 163 Online-Ressource (DE-627)320405737 (DE-600)2000651-2 (DE-576)259484369 0143-8166 nnns volume:163 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 50.37 Technische Optik VZ AR 163 |
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10.1016/j.optlaseng.2023.107478 doi (DE-627)ELV009196722 (ELSEVIER)S0143-8166(23)00007-6 DE-627 ger DE-627 rda eng 530 VZ 50.37 bkl Peng, Tao verfasserin (orcid)0000-0002-0120-924X aut Quantitative differential phase contrast phase reconstruction for sparse samples 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Quantitative differential phase contrast (qDPC) microscopy can achieve phase imaging of unlabeled cell samples with high spatial resolution. However, qDPC imaging is easily affected by the noise generated in the experiments. In this manuscript, the L0-norm regularization was introduced into qDPC phase reconstruction for sparse samples (L0-qDPC), including the quantitative phase target and cell samples. After the detailed comparison of phase fidelity, imaging contrast, resolution, and convergence rate, L0-qDPC method can provide a stable qDPC phase imaging without parameter adjustment for sparse samples due to strong constraint and good robustness of L0-norm based on sparse prior, compared with the L2-norm and total variation regularization. Quantitative differential phase contrast imaging Phase reconstruction Regularization Image denoising Ke, Zeyu verfasserin (orcid)0000-0003-4348-6808 aut Zhang, Shuhe verfasserin (orcid)0000-0002-3115-7364 aut He, Jun verfasserin aut Wang, Peng verfasserin aut Wang, Fengsong verfasserin aut Zhong, Zhensheng verfasserin aut Fang, Shu verfasserin aut Shi, Hui verfasserin aut Lu, Rongsheng verfasserin (orcid)0000-0002-9794-9428 aut Zhou, Jinhua verfasserin (orcid)0000-0002-3704-4459 aut Enthalten in Optics and lasers in engineering Amsterdam [u.a.] : Elsevier Science, 1980 163 Online-Ressource (DE-627)320405737 (DE-600)2000651-2 (DE-576)259484369 0143-8166 nnns volume:163 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 50.37 Technische Optik VZ AR 163 |
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530 VZ 50.37 bkl Quantitative differential phase contrast phase reconstruction for sparse samples Quantitative differential phase contrast imaging Phase reconstruction Regularization Image denoising |
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Quantitative differential phase contrast phase reconstruction for sparse samples |
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Quantitative differential phase contrast phase reconstruction for sparse samples |
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Peng, Tao Ke, Zeyu Zhang, Shuhe He, Jun Wang, Peng Wang, Fengsong Zhong, Zhensheng Fang, Shu Shi, Hui Lu, Rongsheng Zhou, Jinhua |
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10.1016/j.optlaseng.2023.107478 |
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quantitative differential phase contrast phase reconstruction for sparse samples |
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Quantitative differential phase contrast phase reconstruction for sparse samples |
| abstract |
Quantitative differential phase contrast (qDPC) microscopy can achieve phase imaging of unlabeled cell samples with high spatial resolution. However, qDPC imaging is easily affected by the noise generated in the experiments. In this manuscript, the L0-norm regularization was introduced into qDPC phase reconstruction for sparse samples (L0-qDPC), including the quantitative phase target and cell samples. After the detailed comparison of phase fidelity, imaging contrast, resolution, and convergence rate, L0-qDPC method can provide a stable qDPC phase imaging without parameter adjustment for sparse samples due to strong constraint and good robustness of L0-norm based on sparse prior, compared with the L2-norm and total variation regularization. |
| abstractGer |
Quantitative differential phase contrast (qDPC) microscopy can achieve phase imaging of unlabeled cell samples with high spatial resolution. However, qDPC imaging is easily affected by the noise generated in the experiments. In this manuscript, the L0-norm regularization was introduced into qDPC phase reconstruction for sparse samples (L0-qDPC), including the quantitative phase target and cell samples. After the detailed comparison of phase fidelity, imaging contrast, resolution, and convergence rate, L0-qDPC method can provide a stable qDPC phase imaging without parameter adjustment for sparse samples due to strong constraint and good robustness of L0-norm based on sparse prior, compared with the L2-norm and total variation regularization. |
| abstract_unstemmed |
Quantitative differential phase contrast (qDPC) microscopy can achieve phase imaging of unlabeled cell samples with high spatial resolution. However, qDPC imaging is easily affected by the noise generated in the experiments. In this manuscript, the L0-norm regularization was introduced into qDPC phase reconstruction for sparse samples (L0-qDPC), including the quantitative phase target and cell samples. After the detailed comparison of phase fidelity, imaging contrast, resolution, and convergence rate, L0-qDPC method can provide a stable qDPC phase imaging without parameter adjustment for sparse samples due to strong constraint and good robustness of L0-norm based on sparse prior, compared with the L2-norm and total variation regularization. |
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Quantitative differential phase contrast phase reconstruction for sparse samples |
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Ke, Zeyu Zhang, Shuhe He, Jun Wang, Peng Wang, Fengsong Zhong, Zhensheng Fang, Shu Shi, Hui Lu, Rongsheng Zhou, Jinhua |
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