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Frequency-Domain Denoising-Based in Vivo Fluorescence Imaging

T0 review · 4 major / 6 minor · reviewed 2026-08-06 · deepseek-v4-flash

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Pith's one-line read A frequency-domain denoising step lifts in vivo NIR-II fluorescence contrast by more than 2,500-fold and makes FDA-approved ICG a practical deep-tissue imaging agent.

desk verdict The external-modulation FDD results are plausible and worth a real look, but the headline gains are inflated relative to in-text numbers and the 'internal modulation' variant needs controls before it carries the 600 Hz claim. read the letter →

arxiv 2508.02025 v1 pith:IPUCIZJM submitted 2025-08-04 physics.bio-ph physics.app-phphysics.optics

XuHao Yu , RongYuan Zhang , Zhen Tian , Yixuan Chen , JiaChen Zhang , Yue Yuan , Zheng Zhao , Ben Zhong Tang
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Dazhi Hou
This is my paper · ORCID
classification physics.bio-phphysics.app-phphysics.optics
keywords frequency-domaindenoisingNIR-IIfluorescenceimagingindocyaninegreensignal-to-backgroundratiopenetrationdepthreal-timevascularFouriertransforminvivo
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

FDD fluorescence imaging tries to solve a practical bottleneck: near-infrared-II fluorescence is faint in living tissue because background and detector noise drown the signal, and no FDA-approved agent emits strongly there. The paper's proposal is to modulate the excitation laser periodically, record many cycles of frames, and keep only the Fourier component at the modulation frequency for each pixel. This single processing step is claimed to lift signal-to-background ratio by more than 2,500-fold and signal-to-noise ratio by more than 300-fold, which would double penetration depth, cut required dye dose or laser power by 95%, and bring the FDA-approved dye ICG into the NIR-II window for tumor-margin and vascular imaging. It also enables a 600 Hz video of contrast-agent diffusion and artery/vein differentiation. If true, a pure computational method could accelerate clinical NIR-II surgery navigation without developing new contrast agents.

What carries the argument

The central object is the per-pixel Fourier coefficient at the modulation frequency $\omega_0$ (or, in the 'internal modulation' mode, at the fundamental frequency $f_0 = 1/T$ of the acquisition window). For each pixel, the amplitude of this coefficient forms the denoised image, and the phase forms a complementary image that distinguishes structures by the timing of contrast-agent arrival. The operation is optical lock-in detection translated to in vivo imaging: the periodic signal adds coherently across many frames while random broadband noise does not, so a single Fourier bin isolates the signal.

What would settle it

Record a time series from a dye-free or dead mouse while the excitation is modulated and the subject is breathing or being moved; a persistent peak at the modulation frequency in regions with no contrast agent would show that tissue background or motion has a coherent component in that bin, inflating the reported SBR/SNR gains.

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Extended reading notes

Core claim

On the paper's own terms, the discovery is that frequency-domain denoising makes in vivo fluorescence imaging dramatically more sensitive by exploiting the temporal signature of the signal rather than its brightness. Fluorescence is excited by an intensity-modulated source, so each pixel's time trace is periodic, while the in vivo background and detector noise are non-periodic and spread across the spectrum. Taking the Fourier transform and reading only the bin at the modulation frequency (or, for dynamic signals, at the fundamental of the acquisition window) suppresses the broadband noise and recovers the signal, and the phase of that Fourier component carries arrival-time information. The paper reports that this yields SBR/SNR improvements exceeding 2,500-fold and 300-fold, doubles intralipid penetration depth, permits a 95% reduction in contrast-agent dose or excitation intensity, makes ICG usable in the 1,400–1,700 nm window with SNRs above the Rose criterion, and produces real-time 600 Hz videos in which arteries and veins are separated by phase.

Load-bearing premise

The load-bearing premise is that in vivo background and detector noise are effectively random and broadband, so essentially nothing except the modulated fluorescence occupies the extracted Fourier bin.

Editorial extensions

If this is right

  • Because FDD needs no photoswitchable fluorophore, it should work with any contrast agent that emits fluorescence, including agents already approved for humans.
  • The FDD technique extends the time window over which ICG tumor margins remain distinguishable to hours, which should reduce repeat injections during surgical navigation.
  • A 95% reduction in contrast-agent dosage or excitation intensity would lower toxicity and cost, addressing a main barrier to NIR-II agent approval.
  • The 600 Hz frame rate and phase-based artery/vein separation offer a route to motion-blur-free, functional vascular imaging during surgery.
  • FDD provides a greater-than-10-fold contrast increase when total acquisition time is extended threefold, giving more tolerance for low-quantum-yield contrast agents.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • If the broadband-noise assumption holds, the same processing could be transferred to other periodic-excitation imaging modalities with stationary scenes, such as photoacoustic imaging or conventional NIR-I fluorescence, without changing the contrast agent.
  • The phase image is effectively a map of local arrival-time delays, so it could be processed further to estimate blood-flow velocities or perfusion gradients across the field, beyond the paper's artery/vein demonstration.
  • The technique sets a fair benchmark for evaluating new NIR-II agents: if an agent's advantage over ICG disappears after FDD processing, its real contribution may be brightness or photostability rather than noise suppression.
  • A practical caveat follows from the assumption: any motion, heartbeat-synchronous tissue movement, or physiological oscillation that locks to the modulation frequency would enter the extracted bin and inflate apparent contrast, so motion correction or gating would be needed in less-anesthetized or freely moving subjects.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

4 major / 6 minor

Summary. The paper presents frequency-domain denoising (FDD) as a post-processing technique for in vivo NIR-II fluorescence imaging. Excitation light is periodically modulated, a time series of frames is acquired, and each pixel's Fourier coefficient at the modulation frequency is used as the denoised signal, with the phase optionally used for additional contrast. The authors report large SBR/SNR enhancements in intralipid phantoms, 95% reductions in contrast-agent dosage or excitation intensity for mouse vascular imaging, improved tumor-margin and vessel visibility with ICG in the 1,400–1,700 nm band, a 600 Hz 'real-time' video of contrast-agent diffusion with artery/vein differentiation, and motion-blur suppression via an increased frame rate evaluated by SSIM. The central idea is straightforward and the external-modulation phantom experiments are the most controlled part of the study.

Significance. If the claims hold, FDD would be an inexpensive, broadly applicable computational enhancement for NIR-II imaging, potentially making FDA-approved ICG usable in a spectral region where no approved NIR-II agents exist. The external-modulation phantom depth data (Fig. 2) provide a clear, controlled demonstration of the core mechanism, and the proposed extension to ICG-based surgical navigation is clinically motivated. However, the most clinically interesting claims—ICG vessel-over-liver separation, artery/vein phase discrimination, and the 600 Hz temporal-resolution gain—rest on an 'internal modulation' variant that is not validated against the windowing and motion artifacts inherent to Fourier analysis of non-periodic, drift-dominated signals. The abstract's headline enhancement figures (2,500-fold SBR, 300-fold SNR) are also not supported by the numbers reported in the text (734-fold and 98-fold at the 6 mm penetration limit). The technique is potentially significant, but the load-bearing validation is currently incomplete.

major comments (4)
  1. [Abstract; Results, Fig. 2e-f] The abstract claims that FDD improves SBR and SNR by more than 2,500-fold and 300-fold, respectively, but the text reports only 734-fold and 98-fold improvements at the 6 mm penetration limit of the original image (Fig. 2e, 2f, right axes). No other measurement in the manuscript supports the larger figures. The abstract should either cite the specific experimental condition that yields 2,500-fold/300-fold or be corrected to match the reported data.
  2. [Extended Data Fig. 1d; 'Real-time imaging of spatially varying signals'] The SSIM evaluation for motion-blur suppression is self-referential: the reference image used for SSIM calculation is itself an FDD image with the same parameters and a constant spatial position. Comparing both the original and FDD images against an FDD reference measures similarity to the FDD output, not fidelity to a true ground truth. The resulting 21-fold SSIM enhancement is therefore inflated by construction. A motion-free conventional image (or an independent ground truth, e.g., a sharp image of a static phantom) should be used as the reference.
  3. [Results, 'Video contrast and frame rate improvement of temporally varying signals', Fig. 5e, Fig.] For the 'internal modulation' variant (used for ICG hepatic clearance, the 600 Hz video, and the artery/vein phase images), there is no external modulation: the Fourier component at f0 = 1/T of the full acquisition window is treated as the denoised signal. For non-periodic dynamics such as a one-time bolus or monotonic hepatic clearance, this coefficient is a windowed projection of the total trend, not an instantaneous measurement; linear drift, respiratory or peristaltic motion, and baseline shifts all fall into the same f0 bin and are indistinguishable from the intended biology. The manuscript provides no no-injection control, no static-phantom control, and no estimate of motion leakage at f0. This undermines the reported >100-fold SBR/SNR gains for liver-overlapping vessels (Fig. 5f, 5g), the vessel-over-liver separation, and the artery/vein phase split in Fig. 6d-6e, which can arise from window endpoints rather than physiology. The authors should validate the method on known synthetic dynamics and on a static control, and quantify spectral leakage at f0.
  4. [Methods, 'Real-time imaging of temporally varying signals'; Results, 'Video contrast and frame rate improvement of…] The phrase '600 Hz real-time video' conflates output frame rate with temporal resolution. The Methods state that after each new frame an FDD calculation is performed based on all previously collected frames, so the integration window grows over time; frame k is a low-frequency coefficient over k frames, not a 1.67-ms instantaneous sample. The claimed 5-fold temporal-resolution improvement over prior 100 Hz work is therefore unsupported unless the effective temporal bandwidth of the FDD output is characterized. The 'phase' images derived from the same windowed transform inherit the same ambiguity.
minor comments (6)
  1. [Results, Eq. (2)] Equation (2) defines SNR as (Signal - Bckground) / standard deviation of Background; 'Bckground' should be 'Background'.
  2. [Introduction and Discussion] The duration of distinguishable tumor imaging is inconsistently stated: the Introduction says 'seven-fold increase', Results say 'four times those of the original images', and the Discussion says 'three-fold extension of tumor margin duration'. These numbers should be harmonized.
  3. [Fig. 5 caption] In the caption for Fig. 5, 'local magnifications of the live' should presumably be 'liver'.
  4. [Methods] In the Methods, 'the total FDD acquisition times of tumor and vascular imaing were 320 s and 480 s' contains a typo ('imaing' should be 'imaging').
  5. [Fig. 3, Fig. 4 captions] The figure captions use 'Florescence imaging' instead of 'Fluorescence imaging'.
  6. [Abstract] The abstract states 'we achieved a SBR far exceeded the Rose criterion', but the text (Results) reports SNRs of 45 and 65 as exceeding the Rose criterion; SBR and SNR should be stated consistently.

Circularity Check

2 steps flagged · score 4.0 of 10

External-modulation FDD is independently benchmarked against phantom depth, but two quantitative claims are self-referential: the 21-fold SSIM improvement is scored against an FDD reference image, and the internal-modulation mode defines its signal as the Fourier coefficient at the reciprocal of the acquisition window.

  1. other [Extended Data Fig. 1d and 'Video contrast and frame rate improvement of spatially varying signals' section]
    "The reference image utilized for SSIM calculation was an FDD image with same parameters and a constant spatial position. The calculated results demonstrate a 21-fold enhancement in SSIM with the FDD technique, as shown in Extended Data Fig. 1d."

    SSIM measures similarity between two images, and here the reference image is itself produced by the FDD technique. Comparing an FDD-processed image against an FDD reference therefore scores the method for closeness to its own output, not to an independent ground truth. The 21-fold SSIM enhancement is thus largely a self-consistency measure of the FDD pipeline rather than an independent assessment of image fidelity. This does not affect the central phantom-depth SBR/SNR claims, but it is presented as quantitative evidence of image-quality improvement and is circular by construction.

  2. self definitional [Fig. 5e caption and 'Imaging contrast improvement of ICG' section]
    "By utilizing the temporal variations in signal dynamics caused by hepatic ICG clearance, we replaced external laser modulation in the FDD processing, which not only reduced noise but also facilitated the differentiation of vessels passing through the liver, as shown in Fig. 5c. e, Fourier transform of panel d. The peak corresponds to the value of the corresponding point in panel c, and its frequency (dashed line) is the reciprocal of the acquisition time."

    In the internal-modulation mode there is no external periodic reference; the 'signal' is defined as the Fourier coefficient at f0 = 1/T, the reciprocal of the acquisition window. The FDD image in Fig. 5c is constructed from exactly these Fourier coefficients, so the statement that the peak in the Fourier transform 'corresponds to' the value in panel c is tautological. For non-periodic in vivo dynamics such as ICG hepatic clearance, that coefficient is a window projection of a monotonic trend or drift, not an independently defined physiological signal. The reported >100-fold SBR/SNR gains and vessel-over-liver separation therefore reduce, at least partly, to properties of the chosen Fourier basis rather than validated signal extraction.

full rationale

The core externally-modulated FDD technique is a standard lock-in / frequency-domain filtering operation: the laser is modulated at a known frequency, the fluorescence is acquired over N periods, and the amplitude at the modulation frequency is extracted. This central procedure is benchmarked against independent phantom measurements (intralipid penetration depth, Fig. 2), where the original-image visibility limit is 6 mm and FDD doubles that depth; no parameter is fitted to the quantity being predicted. The SBR/SNR definitions (Eqs. 1-2) are standard, and the reported improvements in the external-modulation mode are computed from measured images with independently selected background ROIs. Those claims are not circular. The paper's self-citations (e.g., the AIE agent DIPT-ICF from the same groups, Ref. 21) are not load-bearing for the FDD derivation; they supply an independently described fluorophore. The circularity is confined to two secondary but non-negligible evaluation claims. First, the SSIM improvement in Extended Data Fig. 1 uses an FDD image as the reference, so the comparison measures self-similarity rather than image quality. Second, the internal-modulation variant used for Fig. 5 and Fig. 6 replaces external modulation with the temporal variation of the data itself, and explicitly defines the signal frequency as the reciprocal of the acquisition time. Because the FDD output is the Fourier coefficient at that frequency, the 'peak' evidence and the resulting vessel/liver and artery/vein contrasts are constructed by the choice of basis, not independently validated. These steps support partial circularity in the dynamic-imaging claims, but the central external-modulation results retain independent content, so a moderate score of 4 is appropriate.

Assumptions & free parameters 2 free parameters · 4 assumptions · 0 invented entities

The central claim rests on standard Fourier-domain properties and two implicit biological assumptions: unmodulated broadband noise, and that a single fundamental frequency captures the relevant dynamics. The paper introduces no new physical entities. The main user-chosen settings are acquisition windows and Fourier-bin selection; no parameter is fit to data in the reported enhancement calculations, though the photon calibration (2.24 photons per amplitude unit) is a measurement conversion.

free parameters (2)
  • Internal modulation frequency (f0 = 1/T) = 1/T, where T = 320-480 s for ICG dynamic imaging (Methods)
    In Fig. 5e and Fig. 6, the signal frequency is set to the reciprocal of the total acquisition window. This hand-chosen frequency determines what temporal dynamics survive the FDD projection and is not derived from the dye's clearance or diffusion kinetics.
  • External modulation frequency and period count N = Not reported; examples: exposure 10 s over 40 s total (Fig. 3), 4 s exposure over 320-480 s (Figs. 4-5)
    The claimed 98-734-fold noise suppression depends on N and on the modulation frequency, but these values are not stated, so the trade-off between acquisition time and achieved gain is not quantified.
assumptions (4)
  • standard math Noise is random and broadband, so it distributes across Fourier bins while the modulated fluorescence signal concentrates at the modulation frequency.
    Invoked in Fig. 1d; requires white, stationary noise over the acquisition window to hold.
  • domain assumption In vivo background (autofluorescence, tissue) is not itself modulated at the excitation frequency.
    Assumed throughout the imaging sections; if background is also excited by the modulated laser, FDD will extract it as signal and the true SBR gains are smaller than reported.
  • ad hoc to paper For non-periodic dynamic signals, the contrast-agent time course is adequately represented by its component at f0 = 1/T.
    Introduced in Fig. 5d-5e and Fig. 6 for hepatic clearance and bolus diffusion; no validation shows that the fundamental Fourier component preserves the anatomy of interest.
  • domain assumption The Rose criterion threshold of SNR = 4 applies to the paper's Eq. (2) definition of SNR.
    Stated in the text as 'which is 4 for the SNR used in this study'; the standard Rose criterion uses a detectability index and the mapping is asserted, not derived.

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Cite this review

Pith. "Pith review of Frequency-Domain Denoising-Based in Vivo Fluorescence Imaging." pith.science (2026). https://pith.science/paper/IPUCIZJM

@misc{pith2026250802025,
  author       = {Pith},
  title        = {Pith review of: Frequency-Domain Denoising-Based in Vivo Fluorescence Imaging},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/IPUCIZJM}},
  note         = {Machine review of arXiv:2508.02025}
}
read the original abstract

The second near-infrared window (NIR-II, 900-1,880 nm) has been pivotal in advancing in vivo fluorescence imaging due to its superior penetration depth and contrast. Yet, its clinical utility remains limited by insufficient imaging temporal-spatial resolution and the absence of U.S. Food and Drug Administration (FDA)-approved NIR-II contrast agents. This work presents a frequency-domain denoising (FDD)-based in vivo fluorescence imaging technique, which can improve signal-to-background ratio (SBR) and signal-to-noise ratio (SNR) by more than 2,500-fold and 300-fold, respectively. The great enhancement yields a doubled penetration depth and a 95% reduction in contrast agent dosage or excitation light intensity for mouse vascular imaging. Additionally, we achieved a SBR far exceeded the Rose criterion in the observation of tumor margins and vessels in mice using Indocyanine Green (ICG), demonstrating the feasibility of NIR-II surgical navigation with FDA-approved agents. Furthermore, a 600 Hz real-time video enables visualization of the entire contrast agent diffusion process within the mouse body and differentiation between arteries and veins. This innovative technique, characterized by exceptional sensitivity, efficiency, and robustness, presents a promising solution for clinical applications, particularly in NIR-II surgical navigation.

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