Theoretical analysis of performance limitation of computational refocusing in optical coherence tomography
Pith reviewed 2026-05-23 05:15 UTC · model grok-4.3
The pith
Computational refocusing in point-scanning OCT is limited by confocality while spatially-coherent full-field OCT faces no such limit and can correct arbitrary defocus with adequate sampling.
A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.
Core claim
Formulating the lateral imaging process of OCT via pupil-based imaging theory shows that the maximum correctable defocus is primarily limited by confocality in point-scanning OCT, while spatially-coherent full-field OCT has no such constraint and can achieve virtually infinite maximum correctable defocus with a proper and reasonable sampling density.
What carries the argument
Pupil-based imaging theory applied to the lateral imaging process, incorporating explicit constraints on lateral sampling density and confocality.
If this is right
- Point-scanning OCT has a finite maximum correctable defocus set by its confocal gate.
- Spatially-coherent full-field OCT can restore arbitrary defocus provided lateral sampling meets the required density.
- Full-field OCT therefore removes the usual resolution-versus-depth-of-focus trade-off for computational refocusing.
- Spatially-coherent full-field OCT becomes the preferred architecture for optical coherence microscopy applications that require extended depth range.
Where Pith is reading between the lines
- The same sampling-density argument may allow computational refocusing to be applied to other spatially coherent wide-field modalities such as digital holographic microscopy.
- Hardware designs for full-field OCT could prioritize dense lateral sampling over confocal gating to maximize post-acquisition flexibility.
- The absence of a confocality limit suggests that full-field OCT could integrate computational refocusing with numerical aberration correction without additional depth constraints.
Load-bearing premise
The pupil-based imaging theory fully captures the lateral constraints of computational refocusing without noise, residual aberrations, or details of the specific refocusing algorithm.
What would settle it
Side-by-side experimental measurement of the largest defocus amount that can be computationally restored to diffraction-limited resolution in a point-scanning OCT system versus a spatially-coherent full-field OCT system under matched numerical aperture and sampling conditions.
Figures
read the original abstract
High-numerical-aperture optical coherence tomography (OCT) enables sub-cellular imaging but faces a trade-off between lateral resolution and depth of focus. Computational refocusing can correct defocus in Fourier-domain OCT, yet its limitations remain unaddressed theoretically. We formulate the lateral imaging process of OCT by using pupil-based imaging theory and the constraints of the computational refocusing in point-scanning OCT and spatially-coherent full-field OCT (FFOCT) are analyzed. The constrains in lateral sampling density and the confocality are considered, and it is shown that the maximum correctable defocus (MCD) is primarily limited by confocality in point-scanning OCT, while spatially-coherent FFOCT has no such constraint and can achieve virtually infinite MCD with a proper and reasonable sampling density. This makes spatially-coherent FFOCT particularly suitable for optical coherence microscopy.
Editorial analysis
A structured set of objections, weighed in public.
Referee Report
Summary. The manuscript uses pupil-based imaging theory to analyze constraints on computational refocusing in high-NA Fourier-domain OCT. It concludes that maximum correctable defocus (MCD) is limited by confocality and lateral sampling in point-scanning OCT, whereas spatially-coherent full-field OCT (FFOCT) has no such confocality constraint and can achieve virtually infinite MCD given adequate sampling density, making FFOCT preferable for optical coherence microscopy.
Significance. If the pupil-function derivation holds, the result supplies a theoretical rationale for choosing spatially-coherent FFOCT when high lateral resolution must be maintained over extended depths, a practically relevant distinction for optical coherence microscopy. The analysis is grounded in standard imaging theory without ad-hoc parameters.
major comments (1)
- [Abstract] The central claim that FFOCT permits 'virtually infinite' MCD (Abstract) is derived solely from pupil-function constraints on lateral sampling and confocality. Because the formulation omits detection noise, residual aberrations, and numerical conditioning of the refocusing operator, the unbounded-MCD conclusion does not yet address whether realistic noise floors re-impose a finite limit; this omission is load-bearing for the comparative advantage asserted for FFOCT.
Simulated Author's Rebuttal
We thank the referee for their detailed review and valuable comments on our manuscript. Below we provide a point-by-point response to the major comment.
read point-by-point responses
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Referee: [Abstract] The central claim that FFOCT permits 'virtually infinite' MCD (Abstract) is derived solely from pupil-function constraints on lateral sampling and confocality. Because the formulation omits detection noise, residual aberrations, and numerical conditioning of the refocusing operator, the unbounded-MCD conclusion does not yet address whether realistic noise floors re-impose a finite limit; this omission is load-bearing for the comparative advantage asserted for FFOCT.
Authors: The referee correctly identifies that our derivation focuses exclusively on the pupil-function constraints, lateral sampling, and confocality. The 'virtually infinite' MCD for spatially-coherent FFOCT is a statement about the absence of a confocality limit in the imaging model, conditional on sufficient sampling density to avoid aliasing of the pupil function. We do not include detection noise or aberrations because the goal is to isolate the optical constraints of the OCT modalities. These additional factors would affect both point-scanning OCT and FFOCT, but the key distinction remains that point-scanning OCT has an inherent confocality constraint that FFOCT lacks. We will make a partial revision by adding a clarifying statement in the abstract and discussion section to explicitly note the scope of the analysis and that practical noise floors are not considered here. revision: partial
Circularity Check
No circularity; derivation from standard pupil-based imaging theory is independent
full rationale
The paper formulates the lateral imaging process using established pupil-based imaging theory, then analyzes constraints from lateral sampling density and confocality to derive the MCD limits for point-scanning OCT versus FFOCT. No step reduces by construction to a fitted parameter, self-definition, or load-bearing self-citation; the central claim follows directly from the differing confocality properties encoded in the model. The analysis is self-contained against external optical theory benchmarks.
Axiom & Free-Parameter Ledger
axioms (1)
- domain assumption Pupil-based imaging theory accurately models the lateral imaging process in OCT
Forward citations
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Reference graph
Works this paper leans on
-
[1]
Optical coherence microscopy in scattering media,
J. A. Izatt, M. R. Hee, G. M. Owen,et al., “Optical coherence microscopy in scattering media,” Opt. Lett.19, 590–592 (1994)
work page 1994
-
[2]
Full-field optical coherence microscopy,
E. Beaurepaire, A. C. Boccara, M. Lebec,et al., “Full-field optical coherence microscopy,” Opt. Lett.23, 244–246 (1998)
work page 1998
-
[3]
High-resolution optical coherence microscopy for high-speed, in vivo cellular imaging,
A. D. Aguirre, P. Hsiung, T. H. Ko,et al., “High-resolution optical coherence microscopy for high-speed, in vivo cellular imaging,” Opt. Lett.28, 2064–2066 (2003)
work page 2064
-
[4]
C. Apelian, F. Harms, O. Thouvenin, and A. C. Boccara, “Dynamic full field optical coherence tomography: subcellular metabolic contrast revealed in tissues by interferometric signals temporal analysis,” Biomed. Opt. Express 7, 1511–1524 (2016)
work page 2016
-
[5]
Dynamic contrast in scanning microscopic OCT,
M. Münter, M. vom Endt, M. Pieper,et al., “Dynamic contrast in scanning microscopic OCT,” Opt. Lett.45, 4766–4769 (2020)
work page 2020
-
[6]
Imaging intracellular motion with dynamic micro-optical coherence tomography,
H. M. Leung, M. L. Wang, H. Osman,et al., “Imaging intracellular motion with dynamic micro-optical coherence tomography,” Biomed. Opt. Express11, 2768–2778 (2020)
work page 2020
-
[7]
I. A. El-Sadek, A. Miyazawa, L. T.-W. Shen,et al., “Optical coherence tomography-based tissue dynamics imaging for longitudinal and drug response evaluation of tumor spheroids,” Biomed. Opt. Express11, 6231–6248 (2020)
work page 2020
-
[8]
Y. Huang, S. Wang, Q. Guo,et al., “Optical coherence tomography detects necrotic regions and volumetrically quantifies multicellular tumor spheroids,” Cancer Res.77, 6011–6020 (2017)
work page 2017
-
[9]
Three-dimensional dynamics optical coherence tomography for tumor spheroid evaluation,
I. A. El-Sadek, A. Miyazawa, L. T.-W. Shen,et al., “Three-dimensional dynamics optical coherence tomography for tumor spheroid evaluation,” Biomed. Opt. Express12, 6844–6863 (2021)
work page 2021
-
[10]
I.AbdEl-Sadek,R.Morishita,T.Mori,etal.,“Label-freevisualizationandquantificationofthedrug-type-dependent response of tumor spheroids by dynamic optical coherence tomography,” Sci. Rep.14, 3366 (2024)
work page 2024
-
[11]
K. Chen, S. Swanson, and K. Bizheva, “Line-field dynamic optical coherence tomography platform for volumetric assessment of biological tissues,” Biomed. Opt. Express15, 4162–4175 (2024)
work page 2024
-
[12]
Dynamic full-field optical coherence tomography: 3D live-imaging of retinal organoids,
J. Scholler, K. Groux, O. Goureau,et al., “Dynamic full-field optical coherence tomography: 3D live-imaging of retinal organoids,” Light sci. appl.9(2020)
work page 2020
-
[13]
R. Morishita, T. Suzuki, P. Mukherjee,et al., “Label-free intratissue activity imaging of alveolar organoids with dynamic optical coherence tomography,” Biomed. Opt. Express14, 2333–2351 (2023)
work page 2023
-
[14]
Optical coherence tomography and microscopy in gastrointestinal tissues,
J. A. Izatt, M. D. Kulkarni, H.-W. Wang,et al., “Optical coherence tomography and microscopy in gastrointestinal tissues,” IEEE J. Sel. Top. Quantum Electron.2, 1017–1028 (1996)
work page 1996
-
[15]
Y. Chen, P. M. Andrews, A. D. Aguirre,et al., “High-resolution three-dimensional optical coherence tomography imaging of kidney microanatomy ex vivo,” J. Biomed. Opt.12, 034008 (2007)
work page 2007
-
[16]
P. Mukherjee, S. Fukuda, D. Lukmanto,et al., “Label-free metabolic imaging of non-alcoholic-fatty-liver-disease (NAFLD) liver by volumetric dynamic optical coherence tomography,” Biomed. Opt. Express13, 4071–4086 (2022)
work page 2022
-
[17]
P. Mukherjee, S. Fukuda, D. Lukmanto,et al., “Renal tubular function and morphology revealed in kidney without labeling using three-dimensional dynamic optical coherence tomography,” Sci. Rep.13, 15324 (2023)
work page 2023
-
[18]
J. Zhao, A. Van Vleck, and e. a. Winetraub, Yonatan, “Rapid cellular-resolution skin imaging with optical coherence tomography using all-glass multifocal metasurfaces,” ACS Nano17, 3442–3451 (2023)
work page 2023
-
[19]
K. Bizheva, B. Tan, B. MacLelan,et al., “Sub-micrometer axial resolution OCT for in-vivo imaging of the cellular structure of healthy and keratoconic human corneas,” Biomed. Opt. Express8, 800–812 (2017)
work page 2017
-
[20]
K. Bizheva, Z. Hosseinaee, K. Carter,et al., “In vivo contactless, cellular-resolution imaging of the healthy and pathological human limbus with 250-kHz point-scanning SD-OCT,” Transl. Vis. Sci. Technol.13, 29–29 (2024)
work page 2024
-
[21]
Dynamic coherent focus oct with depth-independent transversal resolution,
F. Lexer, C. Hitzenberger, W. Drexler,et al., “Dynamic coherent focus oct with depth-independent transversal resolution,” J. Mod. Opt.46, 541–553 (1999)
work page 1999
-
[22]
Dynamic focus in optical coherence tomography for retinal imaging,
P. Michael, G. Erich, and K. H. Christoph, “Dynamic focus in optical coherence tomography for retinal imaging,” J. Biomed. Opt.11, 054013 (2006)
work page 2006
-
[23]
Thermal-light full-field optical coherence tomography in the 1.2μm wavelength region,
A. Dubois, G. Moneron, and C. Boccara, “Thermal-light full-field optical coherence tomography in the 1.2μm wavelength region,” Opt. Commun.266, 738–743 (2006)
work page 2006
-
[24]
Y. Yasuno, J.-i. Sugisaka, Y. Sando,et al., “Non-iterative numerical method for laterally superresolving fourier domain optical coherence tomography,” Opt. Express14, 1006–1020 (2006)
work page 2006
-
[25]
Subaperture correlation based digital adaptive optics for full field optical coherence tomography,
A. Kumar, W. Drexler, and R. A. Leitgeb, “Subaperture correlation based digital adaptive optics for full field optical coherence tomography,” Opt. Express21, 10850 (2013)
work page 2013
-
[26]
A. Kumar, S. Georgiev, M. Salas, and R. A. Leitgeb, “Digital adaptive optics based on digital lateral shearing of the computed pupil field for point scanning retinal swept source oct,” Biomed. Opt. Express12, 1577–1592 (2021)
work page 2021
-
[27]
Interferometric synthetic aperture microscopy,
P. S. C. T. S. Ralston, D. L. Marks and S. A. Boppart, “Interferometric synthetic aperture microscopy,” Nat. physics 3, 129–134 (2007)
work page 2007
-
[28]
Computational adaptive optics for broadband optical interferometric tomography of biological tissue,
S. G. Adie, B. W. Graf, A. Ahmad,et al., “Computational adaptive optics for broadband optical interferometric tomography of biological tissue,” Proc. Natl. Acad. Sci.109, 7175–7180 (2012)
work page 2012
-
[29]
Deconvolution methods for mitigation of transverse blurring in optical coherence tomography,
T. S. Ralston, D. L. Marks, F. Kamalabadi, and S. A. Boppart, “Deconvolution methods for mitigation of transverse blurring in optical coherence tomography,” IEEE Trans. on Image Process.14, 1254–1264 (2005)
work page 2005
-
[30]
N.Fukutake,“Ageneraltheoryoffar-fieldopticalmicroscopyimageformationandresolutionlimitusingdouble-sided feynman diagrams,” Sci. reports10, 1–12 (2020)
work page 2020
-
[31]
Four-dimensionalimageformationtheoryofopticalcoherencetomography,
N.Fukutake, S.Makita,andY.Yasuno,“Four-dimensionalimageformationtheoryofopticalcoherencetomography,” J. Opt. Soc. Am. A42, 773–779 (2025)
work page 2025
-
[32]
Unified image formation theory for microscopy and optical coherence tomography in 4-D space-time,
N. Fukutake, S. Makita, and Y. Yasuno, “Unified image formation theory for microscopy and optical coherence tomography in 4-D space-time,” Opt. Express33, 28947–28970 (2025)
work page 2025
-
[33]
W. Drexler and J. Fujimoto,Optical Coherence Tomography: Technology and Applications(Springer International Publishing, 2015)
work page 2015
-
[34]
Ultrahigh resolution fourier domain optical coherence tomography,
R. A. Leitgeb, W. Drexler, and e. a. Unterhuber, A., “Ultrahigh resolution fourier domain optical coherence tomography,” Opt. Express12, 2156–2165 (2004)
work page 2004
-
[35]
Gaussian approximations of fluorescence microscope point-spread function models,
B. Zhang, J. Zerubia, and J.-C. Olivo-Marin, “Gaussian approximations of fluorescence microscope point-spread function models,” Appl. optics46, 1819–1829 (2007)
work page 2007
-
[36]
H. Kogelnik and T. Li, “Laser Beams and Resonators,” Appl. Opt.5, 1550–1567 (1966)
work page 1966
-
[37]
L.Zhu, S.Makita, D.Oida,etal., “Computationalrefocusingofjonesmatrixpolarization-sensitiveopticalcoherence tomography and investigation of defocus-induced polarization artifacts,” Biomed. Opt. Express13, 2975–2994 (2022)
work page 2022
-
[38]
D. Oida, K. Tomita, and e. a. Oikawa, Kensuke, “Computational multi-directional optical coherence tomography for visualizing the microstructural directionality of the tissue,” Biomed. Opt. Express12, 3851–3864 (2021)
work page 2021
-
[39]
Bulk-phase-error correction for phase-sensitive signal processing of optical coherence tomography,
K. Oikawa, D. Oida, and e. a. Makita, Shuichi, “Bulk-phase-error correction for phase-sensitive signal processing of optical coherence tomography,” Biomed. Opt. Express11, 5886–5902 (2020)
work page 2020
-
[40]
K. Tomita, S. Makita, N. Fukutake,et al., “Theoretical model for en face optical coherence tomography imaging and its application to volumetric differential contrast imaging,” Biomed. Opt. Express14, 3100–3124 (2023)
work page 2023
-
[41]
T.Nobuhisa,Y.Zhu,ande.a.Makita,Shuichi,“Cellular-resolutionandlong-depth-imagingspatiallycoherentoptical coherence microscope with computational refocusing,” inOptical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XXVIII,vol. 12830 (SPIE, 2025)
work page 2025
-
[42]
In-vivo retinal imaging with off-axis full-field time-domain optical coherence tomography,
H. Sudkamp, P. Koch, H. Spahr,et al., “In-vivo retinal imaging with off-axis full-field time-domain optical coherence tomography,” Opt. Lett.41, 4987–4990 (2016)
work page 2016
-
[43]
Off-axis reference beam for full-field swept-source oct and holoscopy,
D. Hillmann, H. Spahr, and e. a. Sudkamp, Helge, “Off-axis reference beam for full-field swept-source oct and holoscopy,” Opt. Express25, 27770–27784 (2017)
work page 2017
-
[44]
E. Auksorius, D. Borycki, and M. Wojtkowski, “Crosstalk-free volumetric in vivo imaging of a human retina with fourier-domain full-field optical coherence tomography,” Biomed. Opt. Express10, 6390–6407 (2019)
work page 2019
-
[45]
E. Auksorius, D. Borycki, P. Stremplewski,et al., “In Vivoimaging of the human cornea with high-speed and high-resolution Fourier-domain full-field optical coherence tomography,” Biomed. Opt. Express11, 2849–2865 (2020)
work page 2020
-
[46]
Computational aberration correction in spatiotemporal optical coherence (stoc) imaging,
D. Borycki, E. Auksorius, and e. a. Węgrzyn, Piotr, “Computational aberration correction in spatiotemporal optical coherence (stoc) imaging,” Opt. letters45, 1293–1296 (2020)
work page 2020
-
[47]
Y. Yasuno, S. Makita, and e. a. Endo, Takashi, “Simultaneous bm-mode scanning method for real-time full-range fourier domain optical coherence tomography,” Appl. optics45, 1861–1865 (2006)
work page 2006
-
[48]
R. Haindl, W. Trasischker, and e. a. Baumann, B., “Three-beam doppler optical coherence tomography using a facet prism telescope and mems mirror for improved transversal resolution,” J. Mod. Opt.62, 1781–1788 (2015)
work page 2015
-
[49]
S.Tomczewski,P.Węgrzyn,D.Borycki,etal.,“Light-adaptedflickeroptoretinogramscapturedwithaspatio-temporal optical coherence-tomography (stoc-t) system,” Biomed. Opt. Express13, 2186–2201 (2022)
work page 2022
-
[50]
L.Zhu,S.Makita,ande.a.Tamaoki,Junya,“Polarization-artifactreductionandaccuracyimprovementofjones-matrix polarization-sensitive optical coherence tomography by multi-focus-averaging based multiple scattering reduction,” Biomed. Opt. Express15, 256–276 (2024)
work page 2024
-
[51]
Multi-focus averaging for multiple scattering suppression in optical coherence tomography,
L. Zhu, S. Makita, and e. a. Tamaoki, Junya, “Multi-focus averaging for multiple scattering suppression in optical coherence tomography,” Biomed. Opt. Express14, 4828–4844 (2023)
work page 2023
-
[52]
Y. Zhu, L. Zhu, and e. a. Lim, Yiheng, “Multiple scattering suppression for in vivo optical coherence tomography measurement using the b-scan-wise multi-focus averaging method,” Biomed. Opt. Express15, 4044–4064 (2024)
work page 2024
-
[53]
G. T. Smith, N. Dwork, D. O. Connor,et al., “Automated, depth-resolved estimation of the attenuation coefficient from optical coherence tomography data,” IEEE Trans. on Med. Imaging34, 2592–2602 (2015)
work page 2015
-
[54]
J. Kübler, V. S. Zoutenbier, and e. a. Amelink, Arjen, “Investigation of methods to extract confocal function parameters for the depth resolved determination of attenuation coefficients using oct in intralipid samples, titanium oxide phantoms, and in vivo human retinas,” Biomed. Opt. Express12, 6814–6830 (2021)
work page 2021
-
[55]
Image formation and tomogram reconstruction in optical coherence microscopy,
M. Villiger and T. Lasser, “Image formation and tomogram reconstruction in optical coherence microscopy,” JOSA A 27, 2216–2228 (2010)
work page 2010
-
[56]
Modeling of full-field optical coherence tomography in scattering media,
U. Tricoli and R. Carminati, “Modeling of full-field optical coherence tomography in scattering media,” J. Opt. Soc. Am. A36, C122–C129 (2019)
work page 2019
discussion (0)
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