L1 ⚛ L1-529 ⊙ Testnet

Glaucoma Optic-Disc Cupping Classification (PWDR)

Medical Imaging · Optic disc + cup segmentation from fundus with cup-to-disc-ratio glaucoma readout

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⬇ L1-529.md

# ⚛ L1 Principle — Glaucoma Optic-Disc Cupping Classification (PWDR) **ID:** `L1-529` · **Status:** ⊙ Testnet (genesis catalog) > **🌐 Domain:** Medical Imaging — *Optic disc + cup segmentation from fundus with cup-to-disc-ratio glaucoma readout* > **🎯 Problem class:** linear inverse with categorical readout · **🧮 Solution space:** 1D glaucoma severity > **📡 Carrier:** photon · **🌫 Noise:** gaussian > **⚖ Difficulty (δ):** 3 · **⛓ Block:** 41553360 --- ## 🧠 1. Introduction **Glaucoma Optic-Disc Cupping Classification (PWDR)** is a **linear inverse with categorical readout** whose unknown lives in **1D glaucoma severity** space, within the **Optic disc + cup segmentation from fundus with cup-to-disc-ratio glaucoma readout** sub-domain of **Medical Imaging**. Measurements consist of photons collected by an optical detector via a **fundus with glaucoma grading** sensing mechanism. The forward operator applies, in order: L · fundus acquisition operator; L · disc cup segmentation operator; L · cdr measurement operator; L · isnt rule check operator; L · rnfl defect detection operator; L · glaucoma severity classifier operator; pixel-level spatial averaging on the detector. Observations are corrupted by additive Gaussian noise. Existence inherited from L1-049. Uniqueness conditional on adequate disc visibility (no media opacity). Stability dominated by physiologic_cupping_variant (large physiologic cups can mimic glaucoma) and tilted_disc_anatomy. Joint Hadamard well-posedness established by Bourne 2016 (ICO Glaucoma Guidelines), Spaeth 2002 (Disc Damage Likelihood Scale), Jonas 1989 (foundational neuroretinal rim morphometry), Li 2018 (deep learning glaucoma detection benchmark). ## ⚙ 2. Forward Model Physical chain: **x** → L · fundus acquisition → L · disc cup segmentation → L · cdr measurement → L · isnt rule check → L · rnfl defect detection → L · glaucoma severity classifier → Spatial integration → **y** (detector). ``` y = ∫_A dA `L.glaucoma_severity_classifier` `L.rnfl_defect_detection` `L.isnt_rule_check` `L.cdr_measurement` `L.disc_cup_segmentation` `L.fundus_acquisition` x + n, n ~ 𝒩(0, σ²) ``` **Measurement DAG:** | Primitive | What it does | |---|---| | `L.fundus_acquisition` | L · fundus acquisition operator | | `L.disc_cup_segmentation` | L · disc cup segmentation operator | | `L.cdr_measurement` | L · cdr measurement operator | | `L.isnt_rule_check` | L · isnt rule check operator | | `L.rnfl_defect_detection` | L · rnfl defect detection operator | | `L.glaucoma_severity_classifier` | L · glaucoma severity classifier operator | | `int.spatial` | Pixel-level spatial averaging on the detector | ## 🔬 3. Physics Fingerprint | Property | Value | |---|---| | Domain | Medical Imaging | | Sub domain | Optic disc + cup segmentation from fundus with cup-to-disc-ratio glaucoma readout | | Carrier | photon | | Problem class | linear_inverse_with_categorical_readout | | Solution space | 1D_glaucoma_severity | | Noise model | gaussian | | Integration axis | spatial | | Difficulty delta | 3 | | L dag | 5.6 | ## 📡 4. Measurement Model Existence inherited from L1-049. Uniqueness conditional on adequate disc visibility (no media opacity). Stability dominated by physiologic_cupping_variant (large physiologic cups can mimic glaucoma) and tilted_disc_anatomy. Joint Hadamard well-posedness established by Bourne 2016 (ICO Glaucoma Guidelines), Spaeth 2002 (Disc Damage Likelihood Scale), Jonas 1989 (foundational neuroretinal rim morphometry), Li 2018 (deep learning glaucoma detection benchmark). | Metric | Value | |---|---| | Metric | categorical_accuracy | | Secondary | sensitivity_for_advanced_glaucoma | ## 📏 5. Operating Range (Ω) **Center problem class:** `glaucoma_disc_pwdr` · **Forward operator:** `glaucoma_disc_pwdr_forward` **Center point:** | Parameter | Unit | Value | |---|---|---| | H | px | 2048 | | W | px | 2048 | | Snr db | dB | 30 | | Image quality | — | 0 | | Rgb calibration | — | 0 | | Pallor mimicker | — | 0 | | Pixel resolution um | µm | 5 | | Tilted disc anatomy | — | 0 | | Field of view degrees | — | 30 | | Physiologic cupping variant | — | 0 | | Peripapillary atrophy overlap | — | 0 | | Manual grader inter rater kappa | — | 0 | **Allowed bounds:** | Parameter | Unit | Range | |---|---|---| | H | px | 512 – 4096 | | W | px | 512 – 4096 | ## 🎯 6. Tolerance (ε) **Center tolerance:** 0.85_accuracy | Metric | Range | |---|---| | Categorical accuracy | 0.5 – 0.99 | ## ⚖ 7. Hardness Function Hardness scales as **`epsilon_fn`** on **categorical_accuracy**, with κ = `80` and δ = `3`. ## 💾 8. Reference Dataset - **primary** · weight 1.0 · IPFS _(not pinned yet)_ ## 9. On-chain Registration - **Chain hash:** `0xe7aef74be727afd2ae3572ec25bb1d6fe089484fae36b603285d906a4e4c1305` - **Chain tx hash:** `0x4ae9e22989c9201a9492a07a2434377889e0a6f3a33067f3cc42df72fb8bc3c3` - **Chain block:** `41553360` --- ## File Mapping This bundle consists of: `L1-529.md`, `L1-529.json`. | File | Role | How to regenerate | |------|------|-------------------| | `L1-529.md` | Source of truth — edit this | Human or LLM | | `L1-529.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 `L1-529`._ _Edit it, regenerate the JSON, and submit at [/submit](/submit) to claim the artifact._

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Read the attached Markdown (L1-529.md).
Regenerate L1-529.json so every field matches the Markdown.
Preserve the schema documented in the File Mapping footer at the bottom of the MD.
Output each file in its own fenced code block tagged with the filename.

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L2-529-001 Glaucoma Optic-Disc Cupping Classification (PWDR) — Spec Skeleton

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📋 JSON metadata

{
  "artifact_id": "L1-529",
  "chain_block": 41553360,
  "chain_hash": "0xe7aef74be727afd2ae3572ec25bb1d6fe089484fae36b603285d906a4e4c1305",
  "chain_tx_hash": "0x4ae9e22989c9201a9492a07a2434377889e0a6f3a33067f3cc42df72fb8bc3c3",
  "domain": "Medical Imaging",
  "hardness_fn": {
    "delta": 3,
    "kappa": 80,
    "metric": "categorical_accuracy",
    "type": "epsilon_fn"
  },
  "initiator_dataset": [
    {
      "ipfs_cid": null,
      "license_hash": null,
      "name": "primary",
      "weight": 1.0
    }
  ],
  "layer": "L1",
  "observable_profile": {
    "metric": "categorical_accuracy",
    "regime": "Existence inherited from L1-049. Uniqueness conditional on adequate disc visibility (no media opacity). Stability dominated by physiologic_cupping_variant (large physiologic cups can mimic glaucoma) and tilted_disc_anatomy. Joint Hadamard well-posedness established by Bourne 2016 (ICO Glaucoma Guidelines), Spaeth 2002 (Disc Damage Likelihood Scale), Jonas 1989 (foundational neuroretinal rim morphometry), Li 2018 (deep learning glaucoma detection benchmark).",
    "secondary": "sensitivity_for_advanced_glaucoma"
  },
  "physics_fingerprint": {
    "L_DAG": 5.6,
    "carrier": "photon",
    "difficulty_delta": 3,
    "domain": "Medical Imaging",
    "integration_axis": "spatial",
    "noise_model": "gaussian",
    "primitives": [
      "L.fundus_acquisition",
      "L.disc_cup_segmentation",
      "L.cdr_measurement",
      "L.isnt_rule_check",
      "L.rnfl_defect_detection",
      "L.glaucoma_severity_classifier",
      "int.spatial"
    ],
    "problem_class": "linear_inverse_with_categorical_readout",
    "sensing_mechanism": "fundus_with_glaucoma_grading",
    "solution_space": "1D_glaucoma_severity",
    "sub_domain": "Optic disc + cup segmentation from fundus with cup-to-disc-ratio glaucoma readout",
    "title": "Glaucoma Optic-Disc Cupping Classification (PWDR)"
  },
  "size_tiers": {
    "allowed_forward_operators": [
      "glaucoma_disc_pwdr_forward",
      "glaucoma_ddls_pwdr_forward",
      "glaucoma_with_visual_field_pwdr_forward"
    ],
    "allowed_omega_dimensions": [
      "H",
      "W",
      "field_of_view_degrees",
      "pixel_resolution_um",
      "RGB_calibration",
      "SNR_dB",
      "image_quality",
      "physiologic_cupping_variant",
      "pallor_mimicker",
      "tilted_disc_anatomy",
      "peripapillary_atrophy_overlap",
      "manual_grader_inter_rater_kappa"
    ],
    "allowed_problem_classes": [
      "glaucoma_disc_pwdr",
      "glaucoma_ddls_pwdr",
      "glaucoma_screening_pwdr"
    ],
    "center_spec": {
      "epsilon_fn_center": "0.85_accuracy",
      "forward_operator": "glaucoma_disc_pwdr_forward",
      "input_format": "disc_centered_fundus_with_glaucoma_label",
      "omega": {
        "H": 2048,
        "RGB_calibration": 0.0,
        "SNR_dB": 30,
        "W": 2048,
        "field_of_view_degrees": 30,
        "image_quality": 0.0,
        "manual_grader_inter_rater_kappa": 0.0,
        "pallor_mimicker": 0.0,
        "peripapillary_atrophy_overlap": 0.0,
        "physiologic_cupping_variant": 0.0,
        "pixel_resolution_um": 5,
        "tilted_disc_anatomy": 0.0
      },
      "problem_class": "glaucoma_disc_pwdr"
    },
    "epsilon_bounds": {
      "categorical_accuracy": [
        0.5,
        0.99
      ]
    },
    "omega_bounds": {
      "H": [
        512,
        4096
      ],
      "W": [
        512,
        4096
      ]
    }
  },
  "staked_pwm": 0.0,
  "status": "testnet",
  "sub_domain": "Optic disc + cup segmentation from fundus with cup-to-disc-ratio glaucoma readout",
  "title": "Glaucoma Optic-Disc Cupping Classification (PWDR)"
}

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