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dw.jang 909eac9ca3 docs: V3 CenterAligner 2-Pass 이식 반영
- docs/ALGORITHM_COMPARISON.md
  * "V3: CenterAligner 2-Pass BVCV" 신규 서브섹션
  * Python 원본 매핑 · 검증 방식 · commit ID 명시
  * V1 3-stage / V2 6-stage / V3 2-Pass 세 알고리즘 병행 정리
- VesiScan_Android_Pipeline_Summary.md
  * v7 patch 헤더 2026-07-13 → 2026-07-15
  * Alignment 섹션 V3 항목 신규 (piezophantomtest PR #35 링크,
    Pass 1/2 요약, 검증 결과 요약, UI 후속 작업 표기)

기능 변화 없음. V3 라이브러리 이식 (커밋 9387552 / fcdce12) 을 문서에 반영.
2026-07-15 16:04:42 +09:00

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Method A / B / C Algorithm Comparison & Placement Test

마지막 업데이트: 2026-07-15 — V3 CenterAligner 2-Pass BVCV 이식 추가.

Wall Detection Comparison

Pipeline

Method A:  raw → SG → composite(sg+|d1|+|d2|) → plateau score → plateau spans
           → prominence wall (ANT=nearest, POST=edge_score)
           → cross-validation → BV(frustum+ellipse cap, 1ch=sphere)
           ※ 채널별 min_wall_contrast_ratio × cos(θ) 보정

Method B:  raw → SG → TGC(multichannel log-fit) → initial detect(Otsu×0.9×cos(θ))
           → BR candidate(per-ch, post-only, prominence≥50)
           → consensus(median, outlier_tol=4, min_votes=3)
           → is_reflection_only(shared+cluster, amp_ratio=1.5)
           → resolve(suspicious post: post>ant×1.5)
           → suppress(valley early-stop 50.0) → rerun detect
           → choose(rerun vs initial) → BV(frustum+ellipse cap, 1ch=sphere)

Method C:  raw → MedianFilter(win=7) → SG+wavelet
           → ImpulseReject(2-pass Hampel, lumen clean)
           → OS-CFAR(per-sample) → lumen mask
           → prominence wall + subsample refine
           → StaLta impulse purity check
           → anatomical gate (antDepth≥10mm, chord 5-110mm)
           → BModeScore V41 (wamp=0.45, stalta=0.20, far=0.15, dark=0.10)
           → ChordConsensus (Tukey MAD + Fischler-Bolles pair test)
           → BV dispatch(frustum/chord/sphere, trusted channels only)

Stage-by-Stage

Stage A (Plateau) B (Otsu+TGC+BR) C (V4.1 CFAR)
Pre-filter none none MedianFilter(win=7) + ImpulseReject(Hampel)
Denoising SG(5,2) SG(5,2) → log-TGC SG(5,2) + db4 wavelet 3-level
Threshold sliding plateau score Q=0.5 Otsu×0.9×cos(θ) OS-CFAR (win=15, rank=40%, scale=1.05)
Low-echo mask platScore < thr sg <= otsu (full) sg <= median(CFAR)
Span merge gap≤5, simple gap<3: unconditional, ≥3: wall check mergeGapMax=5, gapPeakMargin=50
Span refine none refineRightEdge none
Wall select ANT=nearest, POST=edge_score, decay=0.15 ANT=nearest, POST=edge_score, decay=0.12 prominence + subsample, MAX_CANDIDATES_POST=64
Valley logic descending-first, rise=5 descending-first, rise=50 rise=50
Extra conditions contrast×cos(θ)≥1.2, prom≥3 peakMin=max(low+30,thr), sg[ant/post]≥thr, postProm≥30 Kremkau ant fallback, antMinIdx=7
Score sg[ant]+sg[post] asymmetric ant_reliability BModeScore V41 (wamp+stalta+far+dark+grad)
FP filter cross-validation score<3000 AnatomicalGate + ChordConsensus
Impulse check none none StaLta (STA/LTA ratio)
Channel filter none none ChordConsensus (MAD outlier + pair test)
Back reflection none consensus multichannel BR none
Fallback none ant=max(0,s-(post-e)) B-mode tier

BV Estimation

A B C
Model shared with B frustum + ellipse cap Multi-dispatch (trusted ch only)
1-channel sphere V=(4/3)πR³ same Verathon chord
Channel filter none none ChordConsensus (drop inconsistent)
Cap height 8-point ellipse LSQ same fixed: bottom=hemisphere, top=cone
LR ratio shared with B 2-lateral ellipse solve + shrinkage 1/avg_ratio, clamp[1.0,1.6]
Confidence none none 0.95(4C+2L) ~ 0.20(1ch)
DPS PiezoHW (1.968) same 1.9309

Angle Correction (PR#20)

Both Method A and B apply per-channel beam angle correction:

  • Method B: otsu_ratio = OTSU_RATIO × cos(θ) per channel
  • Method A: min_wall_contrast_ratio = 1.2 × cos(θ) per channel
  • Larger angles → lower threshold → better detection of weak posterior walls

Back Reflection System (Method B)

Per-channel:
  1. initial detect → (ant, post)
  2. build_candidate: strongest peak AFTER post (prominence≥50)
     - global BR ≈ post (±3) → None (no separate BR)
     - else → strongest significant peak after post

Multichannel:
  3. consensus: median, outlier_tol=4, min_votes=3
  4. is_reflection_only: post > ant × 1.5 (amp_ratio)
     - Condition A: shared_idx based
     - Condition B: post cluster based

Per-channel resolve:
  5. is_suspicious_post: post > ant × 1.5 OR post ≈ shared (±2)
  6. select_idx → resolve → suppress(valley early-stop 50.0)
  7. rerun detect → choose(rerun vs initial, min_gap=8)

Method C V4.1 New Features (2026-05-04)

Pre-processing:
  MedianFilter(win=7) → remove speckle bumps
  ImpulseReject(2-pass Hampel) → clean 1-3 sample impulses in lumen

Detection:
  DetectLumenFirst V41_PARAMS:
    mergeGapMax=5, gapPeakMargin=50
    maxCandidatesPost=64, medianWin=7, antMinIdx=7
    Kremkau half-amplitude ant fallback

Quality:
  StaLta: STA/LTA ratio → wall edge vs reverberation discrimination
  BModeScore V41_WEIGHTS:
    wamp=0.45 (wall-peak amplitude)
    stalta=0.20 (impulse purity)
    far=0.15, dark=0.10, ant=0.05, post=0.05

Channel Filtering:
  ChordConsensus: Tukey MAD outlier + Fischler-Bolles pair test
  → drop geometrically inconsistent channels before BV

Anatomical Gate:
  antDepthMin: 22 → 10mm (Neyman-Pearson loose prior)
  strict threshold removed → delegated to B-mode score

Python vs Kotlin Sync Status (2026-05-04)

Method A/B: 18 functions compared — CRITICAL 0, MINOR 5

All config constants match: LOW_ECHO_AMP=1250, OTSU_RATIO=0.9, MIN_SCORE=3000, EDGE_DIST_DECAY=0.12, VALLEY_STOP_RISE=50, etc.

Method C: Direct copy from CharlesKWONsLaw (45 files, package renamed)


Placement Test Algorithm

Overview (2026-05-26 updated — v6)

Screen entry → "Place VesiScan above the pubic bone, then press Start"
    ↓ Start Alignment 버튼 탭 (waitingForStart=false)
전체 상태 리셋
    ↓
[600ms interval loop]  ← v6: 1000ms → 600ms (BleManager throttle과 동기화)
    ↓
mpa (first time, 500ms delay) → maa → 6ch reb
    ↓ (maa 전 BleManager.canSendMaa() 게이트 통과 필요)
    │   - State gate: !piezoCollector.isComplete 이면 차단 (3s 후 FORCE)
    │   - Time gate: 마지막 송신 < 600ms 이면 차단
    │
Detachment check (6ch received, THR=30) → LED 4 if detached
    ↓
Wall detection (Method A/B/C) → urineLen ≥ 12
    ↓
computePlacementGuide() → 3-stage guide (VERTICAL → LATERAL → GREEN)
    ↓
Debounce (2 consecutive + 1.5s/3s hold) + Phase protection (3 scans)
    ↓
Arrow direction: always updated (directionIcon synced with guideResult)
    ↓
LED: stage change only (4=detach, 5=searching, 6=complete)
    ↓
GREEN: 7s hold + 3 consecutive fail to exit
    ↓
Screen exit → LED OFF

v6 BLE 사이클 실측 (VBTFW0116 + MTU 247 + CONN_PRIORITY HIGH)

한 측정 사이클 (TX maa → RX raa): 평균 ~330ms (이전 1.21.4s 대비 4배 향상). 600ms loop delay 안에 한 사이클이 안정적으로 완료됨.

Guide Modes

Gradient (default): weighted center gradient → LATERAL → GREEN Boundary: up → detect boundary (max drops) → come back → LATERAL SWEEP (CKLaw): navel → slide down → sagittalArgMaxCh → LATERAL → GREEN

3-Stage Guide (V1 — 일반 사용자 진입, computePlacementGuide)

Stage 1 VERTICAL: detect count + gradient + "Slide up/down ↑↓" Stage 2 LATERAL: |len4-len5| ≤ 10 → GREEN, else "Slide left/right ←→" Stage 3 GREEN: CV ≤ threshold AND |LR dev| ≤ 0.20 → "In position!" (7s hold)

6-Stage Guide (V2 — Clinical Alignment 세션, AlignGuide4Stage)

ClinicalHome → Sensor Alignment 진입 시 자동 활성화. Method D chord 기반 CV 로 정밀 vertical 조정 + CH3 flicker 대응 sliding-window majority.

# Phase 조건
1 INITIAL_ACCUM baseline 10 cycle 누적
2 VERTICAL_CLIMB CH3 sliding window majority — 최근 6 프레임 중 hit ≥ 3
3 CH3_STABILIZE 10 cycle 위치 유지, lost 판정도 sliding (window=4, majority=3)
4 CENTER_OPTIMIZE CH0~CH3 chord CV ≤ 0.15 (3연속 hysteresis)
5 LR_BALANCE |u4−u5| ≤ 8 samples, lost 채널 3연속 hysteresis
6 FINAL_CONFIRM buf clear → 5 fresh 프레임 재확인 통과 → GREEN

CH3 flicker 대응 3-Layer (2026-07-06 이후, commit e808b5b / 9261bc7 / 4f8d536):

  • Layer 1 — Sliding-Window Majority: 3 연속 hit 대체. 인체 flick 패턴 (YYNNYY 등) 통과 가능.
  • Layer 2 — Stuck Detection + Relaxed Mode: VERTICAL_CLIMB 20 프레임 (5초) 갇힘 + CH3 hit 저조 + CH0CH2 all detected → CH3 없이 상단 3채널로 CENTER_OPT 진입 허용. AlignmentConstants.VERTICAL_STUCK_THRESHOLD.
  • Layer 3 — UX Soft-Hint: 12 프레임 (~3초) 반복 시 "↑ 위로" → "CH3 신호 확인 중 · 위치 유지" 로 문구 자동 완화.

Python replay 검증 (tools/align_analyze.py, 2026-07-10~13): data123/ 인체 4 세션 (Phantom + Human 0/1/3 CM). NEW vs LEGACY 병행 replay 결과 Human 0CM (CH3 31.8%) 회귀 방지 + Human 1CM (77.3%) 조기 진입 확인, 팬텀 false-positive 없음. 상세 표: tools/README.md.

V3: CenterAligner 2-Pass BVCV (AlignmentAdvisorV3.kt, 2026-07-15)

piezophantomtest ffd436b (PR #35 "feat: alignment bvcv 규칙 추가") 의 vesiscan_test.alignment.CenterAligner 를 Kotlin 으로 이식. 기존 V2 (실시간 sliding 6-stage) 와 병행. Clinical 세션 전용 batch 방식.

Pass 1 — scanSelect(cyclesByCm)

  • 사용자가 치골 위 0/1/2/3/4 cm 각각에서 20 cycle 씩 측정.
  • 각 위치마다:
    • 20 cycle → sliding window 10 → 11 trace
    • mean_scan (전체 20 cycle 평균) → detectMultichannel(applyCross=false) → nch, ch3
    • per-trace → detectMultichannel(applyCross=true) → estimateBladderVolume6ch → volume_ml 리스트 → bv_cv = std/mean
  • Rule A + bvcv tie 로 최적 위치 선택:
    1. ch3 필수 (mean_scan base 검출)
    2. per-trace ch3 검출률 ≥ CH3_HIT_MIN = 0.80 (임계 통과 없으면 ch3=O 전체 fallback)
    3. max nch
    4. 동률 → min bv_cv
  • 선택 위치의 record 를 target 으로 저장 (Pass 2 기준값).

Pass 2 — guide(cycles, cm)

  • 재측정한 한 위치 (20 cycle) 가 target 기준 충족 시 STOP:
    • ch3='O'
    • per-trace ch3 검출률 ≥ 80%
    • rec.nch ≥ target.nch
    • rec.bv_cv ≤ target.bv_cv × (1 + bvCvTol) (기본 bvCvTol = 0.15)
  • 미충족: MOVE_UP (다음 위치로 이동 안내) + 실패 사유 한글 표시.

Python 1:1 매핑:

  • _traces(cycles, win=10) ↔ buildRecord() sliding
  • alignment_selection.select_cm(rule='A', tie='bvcv') ↔ selectCm()
  • CenterAligner._fail_reason() ↔ failReason()
  • BV 리스트 축적: Python if bv is not None: bvs.append(volume_ml) ↔ Kotlin bv?.let { bvs.add(it.volumeMl) } (nan/0 필터 없음 — Python 1:1)

검증 (app/src/test/java/com/medithings/vesiscan/managers/CenterAlignerValidationTest.kt, data123/ 인체 3 세션):

  • Python reference 와 nch / ch3 / ch3_hit 완전 일치
  • bv_cv 오차 <2% (정상 케이스). BV 발산 케이스만 큰 오차 — Rule A 필터링으로 선택 영향 없음
  • 최종 선택 위치 = cm=3 (Python 과 일치)

주의: unit test 는 PiezoHW.activePreset = DevicePreset.V1 명시 설정 필요. 실기기는 BleManager.autoDetectPreset(deviceName) 이 자동 처리.

UI 통합 (Pass 1 위치 안내 · 진행바 · Pass 2 판정 화면) 은 후속 작업. 관련 commit: 9387552 (이식) + fcdce12 (Python 1:1 nan/0 필터 제거).

Measurement Modes (v6 업데이트)

  • Auto Scan: min 600ms gap (state-based throttle: !isComplete + 600ms), 10-sample trimmed mean (max/min removed, 8 avg)
  • Single Scan (Spot): 5회 측정 → trimmed mean (max 8 attempts, min 3)
  • valid ≥ 4 channels only
  • Analysis on coroutine (Dispatchers.Default)
  • Auto fail: 2ch+ missing 5 consecutive → realign dialog
  • Voiding/Catheterization 클릭 시 Auto Scan 자동 stop + 측정 상태 정규화 (displayMaxVolumeMl/window/timer 모두 0)
  • Detachment → LED 4 (once), recovery → LED 0 (once)
  • Foreground Service: BLE connection maintained during screen off
  • BLE 로그: 실시간 파일 기록 (Downloads/VesiScan_BLE_*.log, 화면 잠금에도 보존)
  • CSV: 세션별 파일 (YYYY-MM-DD_HHmmss.csv)

Placement GREEN 기준

CV threshold = DEFAULT_CV_THR + (scanCount / 5) × 0.03
  DEFAULT_CV_THR: V0=0.07, V1/V2=0.10, 기타=0.08
LR deviation ≤ 0.20
GREEN hold: 7초 (greenLockedAtMs 기준)
GREEN exit: 3회 연속 실패 (greenFailCount)

Test Results (2026-05-04, 500ml phantom, Method C V4.1)

총 측정: 223회
평균: 492.4ml (오차 -1.5%)
±15% 이내: 223/223 (100%)
범위: 441~537ml

BLE maa Throttle — State-Based Gate (v6, 2026-05-26)

배경: CH0/CH1만 도착 + BV_FAIL/BV_SKIP 증상

이전 throttle은 시간 단독 now - lastMaaSentMs < 800ms 만 검사. 펌웨어 응답이 1.21.4초 걸리는 환경에서 800ms 시점에 새 maa가 송신되면:

  1. sendChannelsOnly() 통과 → piezoCollector.startMultiChannel(6) → collector reset
  2. 큐에 떠다니던 이전 사이클의 reb / raa 패킷이 새 collector의 시작 부분에 잘못 들어감
  3. 결과: 한 채널만 들고 raa로 종료 → BV_FAIL no valid channels 또는 BV_SKIP center=0 total=5/6

실측 로그 (FW VBTFW0111, 2026-05-22):

TX maa #1     → reb×5 → (raa 큐 밀림) → TX maa #2 → reb×1 + raa → BV_FAIL scan=656

v6 신규 게이트

private fun canSendMaa(caller: String): Boolean {
    val now = System.currentTimeMillis()
    val collectorBusy = piezoCollector.isMultiChannel && !piezoCollector.isComplete
    val sinceLast = now - lastMaaSentMs
    if (collectorBusy) {
        if (sinceLast < 3000) return false                       // (A) state 차단
        // 3s 넘으면 강제 통과 (FORCE) — deadlock 방지
    }
    if (sinceLast < 600) return false                            // (B) time 차단
    return true
}
게이트 차단 풀림
(A) State isMultiChannel && !isComplete raa 도착 OR 3s FORCE
(B) Time sinceLast < 600 600ms 경과

두 게이트 모두 통과해야 maa 송신. State gate가 race 방어, time gate가 burst 방어.

효과 (FW VBTFW0116 + MTU 247 + CONN_PRIORITY HIGH 조합)

  • 한 사이클 응답: 1.2s → 330ms (4배)
  • 6/6 채널 도착률: 부분응답 잦음 → 100% 도착, 유실 0건
  • BV_FAIL/BV_SKIP 빈도: 자주 → 관찰되지 않음

Logcat 키워드

로그 의미
maa BUSY [...] — prev response in progress (Xms) State gate 차단 (정상 방어)
maa FORCE [...] — prev incomplete after Xms 3s 넘게 raa 없음 → 포기하고 진행
maa THROTTLED [...] — Xms since last Time gate 차단 (정상 방어)
(로그 없음) 정상 송신
MTU changed: 247 (status=0) MTU 정상 협상 (CCCD write 직전)
CONN_PRIORITY HIGH requested (ok=true) priority 요청 큐잉 성공 (수락 여부는 sniffer로만 확인 가능)