# ⚛  L1 Principle — Clinical B-mode Ultrasound

**ID:** `L1-032` · **Status:** ⊙ Testnet (genesis catalog)

> **🌐 Domain:** Medical Imaging — *Pulse-echo diagnostic ultrasound*
> **🎯 Problem class:** linear inverse · **🧮 Solution space:** 2D acoustic reflectivity
> **📡 Carrier:** acoustic · **🌫 Noise:** gaussian
> **⚖ Difficulty (δ):** 3 · **⛓ Block:** 41553385

---

## 🧠 1. Introduction

**Clinical B-mode Ultrasound** is a **linear inverse problem** whose unknown lives in **2D acoustic reflectivity** space, within the **Pulse-echo diagnostic ultrasound** sub-domain of **Medical Imaging**.

Measurements consist of acoustic pressure waves recorded by transducers via a **pulse echo ultrasound** sensing mechanism.

The forward operator applies, in order: L · emit · acoustic pulse operator; S · scan · beam operator; L · beamform operator; L · envelope detect operator; detector accumulates flux over the exposure window.

Observations are corrupted by additive Gaussian noise. Existence of the recovered 2D acoustic reflectivity is guaranteed within the declared Omega bounds. Uniqueness holds on the measurement-supported subspace; out-of-support modes are controlled by the declared priors. Stability is moderately conditioned (kappa_eff ~= 12); acoustic_attenuation dominates the stability cliff; speed_of_sound_error and the remaining mismatch parameters contribute higher-order bias terms. Additive gaussian thermal/electronic noise sets the irreducible data-fidelity floor, while mild Tikhonov or analytic inversion is sufficient at the nominal Omega point.

## ⚙ 2. Forward Model

Physical chain: **x** → L · emit · acoustic pulse → S · scan · beam → L · beamform → L · envelope detect → Temporal integration → **y** (detector).

```
y = ∫_t dt `L.envelope_detect` `L.beamform` `S.scan.beam` `L.emit.acoustic_pulse` x + n,    n ~ 𝒩(0, σ²)
```

**Measurement DAG:**

| Primitive | What it does |
|---|---|
| `L.emit.acoustic_pulse` | L · emit · acoustic pulse operator |
| `S.scan.beam` | S · scan · beam operator |
| `L.beamform` | L · beamform operator |
| `L.envelope_detect` | L · envelope detect operator |
| `int.temporal` | Detector accumulates flux over the exposure window |

## 🔬 3. Physics Fingerprint

| Property | Value |
|---|---|
| Domain | Medical Imaging |
| Sub domain | Pulse-echo diagnostic ultrasound |
| Carrier | acoustic |
| Problem class | linear_inverse |
| Solution space | 2D_acoustic_reflectivity |
| Noise model | gaussian |
| Integration axis | temporal |
| Difficulty delta | 3 |
| L dag | 3.5 |

## 📡 4. Measurement Model

Existence of the recovered 2D acoustic reflectivity is guaranteed within the declared Omega bounds. Uniqueness holds on the measurement-supported subspace; out-of-support modes are controlled by the declared priors. Stability is moderately conditioned (kappa_eff ~= 12); acoustic_attenuation dominates the stability cliff; speed_of_sound_error and the remaining mismatch parameters contribute higher-order bias terms. Additive gaussian thermal/electronic noise sets the irreducible data-fidelity floor, while mild Tikhonov or analytic inversion is sufficient at the nominal Omega point.

| Metric | Value |
|---|---|
| Metric | PSNR_dB |
| Secondary | SSIM |

## 📏 5. Operating Range (Ω)

**Center problem class:** `clinical_ultrasound` · **Forward operator:** `clinical_ultrasound_forward`

**Center point:**

| Parameter | Unit | Value |
|---|---|---|
| F mhz | MHz | 5 |
| Snr db | dB | 25 |
| N lines | — | 256 |
| Depth cm | — | 15 |
| Shadowing | — | 0 |
| N elements | — | 128 |
| Acoustic attenuation | — | 0.5 |
| Speed of sound error | — | 0 |

**Allowed bounds:**

| Parameter | Unit | Range |
|---|---|---|
| F mhz | MHz | 1 – 30 |
| Snr db | dB | 0.0 – 40.0 |
| N lines | — | 64 – 1024 |
| Depth cm | — | 1 – 30 |
| Shadowing | — | 0.0 – 0.5 |
| N elements | — | 32 – 512 |
| Reverberation | — | 0.0 – 0.3 |
| Probe pressure | — | 0.0 – 0.3 |
| Acoustic attenuation | — | 0.1 – 1.5 |
| Speed of sound error | — | 0.0 – 0.05 |

## 🎯 6. Tolerance (ε)

**Center tolerance:** 28.0

| Metric | Range |
|---|---|
| Psnr db | 5.0 – 45.0 |

## ⚖ 7. Hardness Function

Hardness scales as **`epsilon_fn`** on **PSNR_dB**, with κ = `240` and δ = `3`.

## 💾 8. Reference Dataset

- **primary** · weight 1.0 · IPFS _(not pinned yet)_

## 9. On-chain Registration

- **Chain hash:** `0xd9bf19b3fdc56a80e3b82a2ccb83b4a5b3824ea54bd6ad3322cec67b532a57cb`
- **Chain tx hash:** `0x10936c80aee816a718793d0a1ebd44d1badaa3f7be594cf2774b8d5d81d21a6f`
- **Chain block:** `41553385`

---

## File Mapping

This bundle consists of: `L1-032.md`, `L1-032.json`.

| File | Role | How to regenerate |
|------|------|-------------------|
| `L1-032.md` | Source of truth — edit this | Human or LLM |
| `L1-032.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 `L1-032`._
_Edit it, regenerate the JSON, and submit at [/submit](/submit) to claim the artifact._