L1 ⚛ L1-160 ⊙ Testnet

CT-FLIT (Fluorescence Lifetime Imaging Tomography)

Multimodal Fusion · Hybrid x-ray CT + diffuse fluorescence tomography

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⬇ L1-160.md

# ⚛ L1 Principle — CT-FLIT (Fluorescence Lifetime Imaging Tomography) **ID:** `L1-160` · **Status:** ⊙ Testnet (genesis catalog) > **🌐 Domain:** Multimodal Fusion — *Hybrid x-ray CT + diffuse fluorescence tomography* > **🎯 Problem class:** nonlinear inverse · **🧮 Solution space:** 3D fluorophore concentration > **📡 Carrier:** photon · **🌫 Noise:** shot poisson > **⚖ Difficulty (δ):** 10 · **⛓ Block:** 41554242 --- ## 🧠 1. Introduction **CT-FLIT (Fluorescence Lifetime Imaging Tomography)** is a **nonlinear inverse problem** whose unknown lives in **3D fluorophore concentration** space, within the **Hybrid x-ray CT + diffuse fluorescence tomography** sub-domain of **Multimodal Fusion**. Measurements consist of photons collected by an optical detector via a **ct fluorescence fusion** sensing mechanism. The forward operator applies, in order: L · ct structure operator; L · diffuse fluorescence tomo operator; L · regularize with ct operator; pixel-level spatial averaging on the detector. Observations are corrupted by Poisson shot noise from quantum-limited detection. Existence of the recovered 3D fluorophore concentration is guaranteed within the declared Omega bounds. Uniqueness is local rather than global (non-convex landscape); convergence depends on initialisation and priors. Stability is moderately conditioned (kappa_eff ~= 30); tissue_scattering_model dominates the stability cliff; CT_prior_mismatch and the remaining mismatch parameters contribute higher-order bias terms. Photon-shot-noise-limited (poisson counting) sets the irreducible data-fidelity floor, while TV / wavelet-sparsity / deep priors stabilise recovery at the ill-conditioned end of Omega. ## ⚙ 2. Forward Model Physical chain: **x** → L · ct structure → L · diffuse fluorescence tomo → L · regularize with ct → Spatial integration → **y** (detector). ``` y = ∫_A dA `L.regularize_with_ct` `L.diffuse_fluorescence_tomo` `L.ct_structure` x, measurements ~ Poisson(αy) ``` **Measurement DAG:** | Primitive | What it does | |---|---| | `L.ct_structure` | L · ct structure operator | | `L.diffuse_fluorescence_tomo` | L · diffuse fluorescence tomo operator | | `L.regularize_with_ct` | L · regularize with ct operator | | `int.spatial` | Pixel-level spatial averaging on the detector | ## 🔬 3. Physics Fingerprint | Property | Value | |---|---| | Domain | Multimodal Fusion | | Sub domain | Hybrid x-ray CT + diffuse fluorescence tomography | | Carrier | photon | | Problem class | nonlinear_inverse | | Solution space | 3D_fluorophore_concentration | | Noise model | shot_poisson | | Integration axis | spatial | | Difficulty delta | 10 | | L dag | 4.5 | ## 📡 4. Measurement Model Existence of the recovered 3D fluorophore concentration is guaranteed within the declared Omega bounds. Uniqueness is local rather than global (non-convex landscape); convergence depends on initialisation and priors. Stability is moderately conditioned (kappa_eff ~= 30); tissue_scattering_model dominates the stability cliff; CT_prior_mismatch and the remaining mismatch parameters contribute higher-order bias terms. Photon-shot-noise-limited (poisson counting) sets the irreducible data-fidelity floor, while TV / wavelet-sparsity / deep priors stabilise recovery at the ill-conditioned end of Omega. | Metric | Value | |---|---| | Metric | PSNR_dB | | Secondary | SSIM | ## 📏 5. Operating Range (Ω) **Center problem class:** `ct_flit` · **Forward operator:** `ct_flit_forward` **Center point:** | Parameter | Unit | Value | |---|---|---| | H | px | 128 | | W | px | 128 | | Z | — | 64 | | Snr db | dB | 20 | | N sources | — | 16 | | N detectors | — | 32 | | Ct prior mismatch | — | 0 | | Registration error | — | 0 | | Fluorophore leakage | — | 0 | | Tissue scattering model | — | 0 | **Allowed bounds:** | Parameter | Unit | Range | |---|---|---| | H | px | 32 | | W | px | 32 | | Z | — | 16 – 256 | | Snr db | dB | 0.0 – 35.0 | | N sources | — | 4 – 64 | | N detectors | — | 4 – 128 | | Ct prior mismatch | — | 0.0 – 0.5 | | Registration error | — | 0.0 – 5.0 | | Fluorophore leakage | — | 0.0 – 0.3 | | Tissue scattering model | — | 0.0 – 0.5 | ## 🎯 6. Tolerance (ε) **Center tolerance:** 16.0 | Metric | Range | |---|---| | Psnr db | 5.0 – 40.0 | ## ⚖ 7. Hardness Function Hardness scales as **`epsilon_fn`** on **PSNR_dB**, with κ = `600` and δ = `10`. ## 💾 8. Reference Dataset - **primary** · weight 1.0 · IPFS _(not pinned yet)_ ## 9. On-chain Registration - **Chain hash:** `0x0cf19ebfee032d471c4b093de091920b81f3e8977d1dbf03a7bf61c32a2629d3` - **Chain tx hash:** `0x81b0ba87b1b71e90896e7418f7e67ee9ab92c8c97a6cb304029d58acfe934d22` - **Chain block:** `41554242` --- ## File Mapping This bundle consists of: `L1-160.md`, `L1-160.json`. | File | Role | How to regenerate | |------|------|-------------------| | `L1-160.md` | Source of truth — edit this | Human or LLM | | `L1-160.json` | Structured metadata for the registry | LLM regenerates from the sections above | **Prompt for your LLM after editing this Markdown:** > Read the attached Markdown. Regenerate the sibling `.json` so every field matches. > Preserve the schema documented in the rows above. > Output each file in its own fenced code block tagged with the filename. > Output only the JSON object. _This Markdown was auto-synthesized from the catalog row for `L1-160`._ _Edit it, regenerate the JSON, and submit at [/submit](/submit) to claim the artifact._

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Read the attached Markdown (L1-160.md).
Regenerate L1-160.json so every field matches the Markdown.
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Output each file in its own fenced code block tagged with the filename.

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L2-160-001 CT-FLIT (Fluorescence Lifetime Imaging Tomography) Mismatch-Only Spec

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📋 JSON metadata

{
  "artifact_id": "L1-160",
  "chain_block": 41554242,
  "chain_hash": "0x0cf19ebfee032d471c4b093de091920b81f3e8977d1dbf03a7bf61c32a2629d3",
  "chain_tx_hash": "0x81b0ba87b1b71e90896e7418f7e67ee9ab92c8c97a6cb304029d58acfe934d22",
  "domain": "Multimodal Fusion",
  "hardness_fn": {
    "delta": 10,
    "kappa": 600,
    "metric": "PSNR_dB",
    "type": "epsilon_fn"
  },
  "initiator_dataset": [
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      "license_hash": null,
      "name": "primary",
      "weight": 1.0
    }
  ],
  "layer": "L1",
  "observable_profile": {
    "metric": "PSNR_dB",
    "regime": "Existence of the recovered 3D fluorophore concentration is guaranteed within the declared Omega bounds. Uniqueness is local rather than global (non-convex landscape); convergence depends on initialisation and priors. Stability is moderately conditioned (kappa_eff ~= 30); tissue_scattering_model dominates the stability cliff; CT_prior_mismatch and the remaining mismatch parameters contribute higher-order bias terms. Photon-shot-noise-limited (poisson counting) sets the irreducible data-fidelity floor, while TV / wavelet-sparsity / deep priors stabilise recovery at the ill-conditioned end of Omega.",
    "secondary": "SSIM"
  },
  "physics_fingerprint": {
    "L_DAG": 4.5,
    "carrier": "photon",
    "difficulty_delta": 10,
    "domain": "Multimodal Fusion",
    "integration_axis": "spatial",
    "noise_model": "shot_poisson",
    "primitives": [
      "L.ct_structure",
      "L.diffuse_fluorescence_tomo",
      "L.regularize_with_ct",
      "int.spatial"
    ],
    "problem_class": "nonlinear_inverse",
    "sensing_mechanism": "ct_fluorescence_fusion",
    "solution_space": "3D_fluorophore_concentration",
    "sub_domain": "Hybrid x-ray CT + diffuse fluorescence tomography",
    "title": "CT-FLIT (Fluorescence Lifetime Imaging Tomography)"
  },
  "size_tiers": {
    "allowed_forward_operators": [
      "ct_flit_forward"
    ],
    "allowed_omega_dimensions": [
      "H",
      "W",
      "Z",
      "N_sources",
      "N_detectors",
      "SNR_dB",
      "tissue_scattering_model",
      "CT_prior_mismatch",
      "fluorophore_leakage",
      "registration_error",
      "tissue_scattering_model",
      "CT_prior_mismatch",
      "fluorophore_leakage",
      "registration_error"
    ],
    "allowed_problem_classes": [
      "ct_flit"
    ],
    "center_spec": {
      "epsilon_fn_center": "16.0",
      "forward_operator": "ct_flit_forward",
      "input_format": "measurement_only",
      "omega": {
        "CT_prior_mismatch": 0.0,
        "H": 128,
        "N_detectors": 32,
        "N_sources": 16,
        "SNR_dB": 20,
        "W": 128,
        "Z": 64,
        "fluorophore_leakage": 0.0,
        "registration_error": 0.0,
        "tissue_scattering_model": 0.0
      },
      "problem_class": "ct_flit"
    },
    "epsilon_bounds": {
      "psnr_db": [
        5.0,
        40.0
      ]
    },
    "omega_bounds": {
      "CT_prior_mismatch": [
        0.0,
        0.5
      ],
      "H": 32,
      "N_detectors": [
        4,
        128
      ],
      "N_sources": [
        4,
        64
      ],
      "SNR_dB": [
        0.0,
        35.0
      ],
      "W": 32,
      "Z": [
        16,
        256
      ],
      "fluorophore_leakage": [
        0.0,
        0.3
      ],
      "registration_error": [
        0.0,
        5.0
      ],
      "tissue_scattering_model": [
        0.0,
        0.5
      ]
    }
  },
  "staked_pwm": 0.0,
  "status": "testnet",
  "sub_domain": "Hybrid x-ray CT + diffuse fluorescence tomography",
  "title": "CT-FLIT (Fluorescence Lifetime Imaging Tomography)"
}

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