C.D. Jones, P. Plassmann University of Glamorgan, Medical Computing Research Group Also: Photometrix Imaging Ltd. (Isotec Imaging Ltd)

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1 Acknowledgement: Project supported by DTI Measurement for Innovators programme MavisCal Calibrating a 3D Wound Measuring Device C.D. Jones, P. Plassmann University of Glamorgan, Medical Computing Research Group Also: Photometrix Imaging Ltd. (Isotec Imaging Ltd) R.F. Stevens, M.R. Pointer, M.B. McCarthy National Physical Laboratory, Teddington

Introduction I Introduction (1 of 4) Why Wound Measurement? Chronic wounds are frequent: 8% of bedridden/chairbound patients develop pressure ulcers 3.

2 Introduction I Introduction (1 of 4) Why Wound Measurement? Chronic wounds are frequent: 8% of bedridden/chairbound patients develop pressure ulcers 3.5% of all adults in the USA suffer from venous leg ulcers alone Wounds are costly: 3rd larges cost factor in the UK (after cardiovacular disease & cancer) venous leg ulcer

3 Introduction (2 of 4) Introduction I Why Wound Measurement? Wounds need to be healed: objective information required monitor progress of healing wound assess influence of clinical interventions increasingly important: litigation verify clinical trials diabetic foot ulcer

4 Introduction (3 of 4) Introduction I Existing techniques Area: transparency tracings or photographs 2D only inaccurate (especially on curved wounds) contact with wound pain, infection Smith & Nephew Visitrak

5 Introduction (4 of 4) Introduction I Existing techniques Volume: fill wound with measured amount of saline or alginate paste messy & time-consuming inaccurate contact with wound pain, infection

6 MAVIS-I I MAVIS - I Data sheet (1990) 110 kg, trolley mounted 15,000, only 6 sold non-contact structured light principle

7 MAVIS - II MAVIS-II Data sheet (2007) light, about 1.5 kg, compact non-contact inexpensive to build, few custom parts accuracy & precision better than MAVIS- I full-colour stereo-photogrammetry principle intelligence in software not hardware no moving mechanical parts

8 MAVIS-II Principle Principle Stereo Photogrammetry displacement between corresponding points in stereo images = distance object point 1 displacemen d t object point 2 Left Image left stereo image Left Image Right Image Right Image right stereo image camera / eyes challenge: finding corresponding points

9 Hardware (1 of 2) MAVIS-II Hardware Off-the-shelf components any high-resolution digital camera with standard lens adapter & flash stereo adapter (slightly modified) laptop or PC camera + stereo adapter

10 Hardware (2 of 2) MAVIS-II Hardware In-house Design range finder

11 Software (1 of 2) MAVIS-II Software Modular design 3-D displacement engine user delineation tool

12 Software (2 of 2) MAVIS-II Software Modular design minimum surface reconstruction positive volume negative volume ulcerated limb measurement, visualisation & output module false reconstruction correct reconstruction

13 I Dimensional Measurements special requirements: patterned several area/volume ratios automated measurement Therefore: no existing benchmarks Colour Measurements Possible? Illumination, reflection, stability, camera suitable?

14 Dimensional I STEP 1: identification of area/volume ratios Artifact Area/Volume Distribution Dimensional Area [cm²] Volume [cm³] Control Artifacts Artifacts

15 Dimensional I STEP 2: Design based on Consistency Checker Dimensional

16 Dimensional I STEP 3: Implementation Dimensional

Dimensional I Dimensional STEP 4: Verification scan using non-contact coordinate measurement machine model sampling points (sphere fitting, polynomial

17 Dimensional I Dimensional STEP 4: Verification scan using non-contact coordinate measurement machine model sampling points (sphere fitting, polynomial fittings) Example Volume: manufactured cm³ (2.6%) sphere fitting cm³ polyn. 4th deg cm³ (2.1%) polyn. 9th deg cm³ (0.6%)

18 Dimensional I Dimensional STEP 5: Characterisation of MAVIS Repeatability (precision) under laboratory conditions (baseline) real life scenario Method: each artifact measured 10x std. dev. precision, mean accuracy

19 Dimensional I Dimensional STEP 5: Characterisation Results Std.Dev. [ % of Area ] Precision of Area Measurements 2.00% 1.50% 1.00% 0.50% 0.00% Area [cm²]

20 Dimensional I Dimensional STEP 5: Characterisation Results Std.Dev. [ % of Area ] Precision of Area Measurements 2.00% Precision of Volume Measurements 10.00% 1.50% Std.Dev. [ % of Volume ] 8.00% 1.00% 6.00% 0.50% 4.00% 0.00% 2.00% % Area [cm²] Volume [cm³]

21 Dimensional I Dimensional STEP 5: Characterisation Results Std.Dev. [ % of Area ] Precision of Area Measurements 2.00% Precision of Volume Measurements Precision of Circumference Measurements 10.00% 1.50% Std.Dev. [ % of Volume ] 1.00% 0.50% 0.00% 8.00% Std.Dev. [ % of Circumference ] 6.00% 4.00% 5.00% 4.00% 3.00% 2.00% 2.00% % 1.00% Area [cm²] % Volume [cm³] Circumference [cm]

22 Dimensional I Dimensional Comparison: Wound Area Precision error range (one standard deviation as % of wound area) rulers tracings digital photography MAVIS wound<10 cm² wound cm² wound >40 cm²

23 I Dimensional Comparison: Wound Volume precision error range (one standard deviation in % of the wound volume) 40% min. precision (large, shallow wounds) 30% Dimensional 20% 10% 0% 3D Scanners casts saline rulers MAVIS max. precision (deep, small wounds)

24 Dimensional I Dimensional STEP 6: Results (accuracy) Error [cm²] Area Measurement Error - Pre Artifact Area [cm²]

25 Dimensional I Dimensional STEP 6: Accuracy Results Error [cm²] Area Measurement Error - Pre Artifact Area [cm²] That s more than enough, mission accomplished! Error [cm²] Error [cm³] Error [cm] Volume Measurement Error - Post Area Measurement Error - Post Artifact Area [cm²] Artifact Volume [cm³] Circumference Measurement Error - Post Artifact Circumference [cm]

26 Colour Rationale I 50% percentage hue not infected infected Pilot Study 60 wounds: 30 infected - 27 detected 30 not inf detected 49 out of 60 wounds were classified correctly (81.6%) Colour 10% Dedicate colorimeter used pixel colour

27 Colour I Colour Benchmarks existing Example: GretagMacbeth colour chart

28 Colour I Colour Method Patch with known CIE colorimetry using CIE standard observer and D65 illuminant raw image data gamma correction using white target modelling by 3rd order polynomial check model vs. known patch data

29 Colour I Results How good is this? Aim: less than 10 E Colour

30 Colour I Results Colour E That s more than enough, mission accomplished!

31 I Summary Summary MAVIS II is: unique inexpensive to manufacture, mainly from standard components lightweight and portable a precise & accurate tool for an increasingly important medical task More information, examples, FAQs, etc:

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