Multimodal and time-lapse skin registration.
OBJECTIVE
Computational skin analysis is revolutionizing modern dermatology. Patterns extracted from image sequences enable algorithmic evaluation. Stacking multiple images to analyze pattern variation implicitly assumes that the images are aligned per-pixel. However, breathing and involuntary motion of the patient causes significant misalignment. Alignment algorithms designed for multimodal and time-lapse skin images can solve this problem. Sequences from multi-modal imaging capture unique appearance features in each modality. Time-lapse image sequences capture skin appearance change over time.


METHODS
Multimodal skin images have been acquired under five different modalities: three in reflectance (visible, parallel-polarized, and cross-polarized) and two in fluorescence mode (UVA and blue light excitation). For time-lapse imagery, 39 images of acne lesions over a 3-month period have been collected. The method detects micro-level features like pores, wrinkles, and other skin texture markings in the acquired images. Images are automatically registered to subpixel accuracy.


RESULTS
The proposed registration approach precisely aligns multimodal and time-lapse images. Subsurface recovery from multimodal images has misregistration artefacts that can be eliminated using this approach. Registered time-lapse imaging captures the evolution of appearance of skin regions with time.


CONCLUSIONS
Misalignment in skin imaging has significant impact on any quantitative or qualitative image evaluation. Micro-level features can be used to obtain highly accurate registration. Multimodal images can be organized with maximal overlap for successful registration. The resulting point-to-point alignment improves the quality of skin image analysis.
Department of Electrical and Computer Engineering, Rutgers University, Piscataway, NJ, USA.
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Madan
Department of Electrical and Computer Engineering, Rutgers University, Piscataway, NJ, USA.
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Dana
Consumer and Personal Product Division, Johnson & Johnson, Piscataway, NJ, USA.
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Cula
D000152:Acne Vulgaris / Q000473:pathology*; D046169:Dermoscopy / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D008029:Lighting / Q000379:methods*; D064847:Multimodal Imaging / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique; D059008:Time-Lapse Imaging / Q000379:methods*
appearance tracking; micro-level features; multimodal registration; surface component recovery; time-lapse registration