TY - GEN
T1 - Inter-scanner variation independent descriptors for constrained diffeomorphic demons registration of retina OCT
AU - Reaungamornrat, S.
AU - Carass, A.
AU - He, Y.
AU - Saidha, S.
AU - Calabresi, P. A.
AU - Prince, J. L.
N1 - Funding Information:
This work was supported in part by the National Institutes of Health grant number 5R01EY024655. The authors gratefully acknowledge Dr. Jeffrey H. Siewerdsen (Biomedical Engineering, Johns Hopkins University) for a discussion on the MIND Demons algorithm.
Publisher Copyright:
© COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.
PY - 2018
Y1 - 2018
N2 - Purpose: OCT offers high in-plane micrometer resolution, enabling studies of neurodegenerative and ocular-disease mechanisms via imaging of the retina at low cost. An important component to such studies is inter-scanner deformable image registration. Image quality of OCT, however, is suboptimal with poor signal-to-noise ratio and through-plane resolution. Geometry of OCT is additionally improperly defined. We developed a diffeomorphic deformable registration method incorporating constraints accommodating the improper geometry and a decentralized-modality-insensitiveneighborhood-descriptors (D-MIND) robust against degradation of OCT image quality and inter-scanner variability. Method: The method, called D-MIND Demons, estimates diffeomorphisms using D-MINDs under constraints on the direction of velocity fields in a MIND-Demons framework. Descriptiveness of D-MINDs with/without denoising was ranked against four other shape/texture-based descriptors. Performance of D-MIND Demons and its variants incorporating other descriptors was compared for cross-scanner, intra- and inter-subject deformable registration using clinical retina OCT data. Result: D-MINDs outperformed other descriptors with the difference in mutual descriptiveness between high-contrast and homogenous regions > 0.2. Among Demons variants, D-MIND-Demons was computationally efficient, demonstrating robustness against OCT image degradation (noise, speckle, intensity-non-uniformity, and poor throughplane resolution) and consistent registration accuracy [(4±4 μm) and (4±6 μm) in cross-scanner intra- and inter-subject registration] regardless of denoising. Conclusions: A promising method for cross-scanner, intra- and inter-subject OCT image registration has been developed for ophthalmological and neurological studies of retinal structures. The approach could assist image segmentation, evaluation of longitudinal disease progression, and patient population analysis, which in turn, facilitate diagnosis and patient-specific treatment.
AB - Purpose: OCT offers high in-plane micrometer resolution, enabling studies of neurodegenerative and ocular-disease mechanisms via imaging of the retina at low cost. An important component to such studies is inter-scanner deformable image registration. Image quality of OCT, however, is suboptimal with poor signal-to-noise ratio and through-plane resolution. Geometry of OCT is additionally improperly defined. We developed a diffeomorphic deformable registration method incorporating constraints accommodating the improper geometry and a decentralized-modality-insensitiveneighborhood-descriptors (D-MIND) robust against degradation of OCT image quality and inter-scanner variability. Method: The method, called D-MIND Demons, estimates diffeomorphisms using D-MINDs under constraints on the direction of velocity fields in a MIND-Demons framework. Descriptiveness of D-MINDs with/without denoising was ranked against four other shape/texture-based descriptors. Performance of D-MIND Demons and its variants incorporating other descriptors was compared for cross-scanner, intra- and inter-subject deformable registration using clinical retina OCT data. Result: D-MINDs outperformed other descriptors with the difference in mutual descriptiveness between high-contrast and homogenous regions > 0.2. Among Demons variants, D-MIND-Demons was computationally efficient, demonstrating robustness against OCT image degradation (noise, speckle, intensity-non-uniformity, and poor throughplane resolution) and consistent registration accuracy [(4±4 μm) and (4±6 μm) in cross-scanner intra- and inter-subject registration] regardless of denoising. Conclusions: A promising method for cross-scanner, intra- and inter-subject OCT image registration has been developed for ophthalmological and neurological studies of retinal structures. The approach could assist image segmentation, evaluation of longitudinal disease progression, and patient population analysis, which in turn, facilitate diagnosis and patient-specific treatment.
KW - Demons algorithm
KW - OCT
KW - deformable image registration
KW - descriptors
KW - diffeomorphism
KW - optical coherence tomography
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U2 - 10.1117/12.2293790
DO - 10.1117/12.2293790
M3 - Conference contribution
C2 - 31695241
AN - SCOPUS:85047345414
T3 - Progress in Biomedical Optics and Imaging - Proceedings of SPIE
BT - Medical Imaging 2018
A2 - Angelini, Elsa D.
A2 - Angelini, Elsa D.
A2 - Landman, Bennett A.
PB - SPIE
T2 - Medical Imaging 2018: Image Processing
Y2 - 11 February 2018 through 13 February 2018
ER -