SLIM (slit lamp image mosaicing): handling reflection artifacts

Autor: Kristina Prokopetc, Adrien Bartoli
Přispěvatelé: Institut Pascal (IP), SIGMA Clermont (SIGMA Clermont)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Centre National de la Recherche Scientifique (CNRS)
Rok vydání: 2017
Předmět:
genetic structures
Computer science
[SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging
0206 medical engineering
Biomedical Engineering
Health Informatics
Context (language use)
02 engineering and technology
Slit Lamp Microscopy
Retina
Retinal Diseases
0202 electrical engineering
electronic engineering
information engineering
Specular highlight
Image Processing
Computer-Assisted
Humans
Radiology
Nuclear Medicine and imaging
Segmentation
Computer vision
Ghosting
ComputingMilieux_MISCELLANEOUS
Lighting
Slit lamp
Slit Lamp
Pixel
business.industry
Lens flare
General Medicine
020601 biomedical engineering
Computer Graphics and Computer-Aided Design
eye diseases
Computer Science Applications
Slit-lamp Examination
020201 artificial intelligence & image processing
Surgery
sense organs
Computer Vision and Pattern Recognition
Artificial intelligence
business
Artifacts
Software
Zdroj: International Journal of Computer Assisted Radiology and Surgery
International Journal of Computer Assisted Radiology and Surgery, 2017, 12 (6), pp.911-920. ⟨10.1007/s11548-017-1555-z⟩
International Journal of Computer Assisted Radiology and Surgery, Springer Verlag, 2017, 12 (6), pp.911-920. ⟨10.1007/s11548-017-1555-z⟩
ISSN: 1861-6429
1861-6410
DOI: 10.1007/s11548-017-1555-z⟩
Popis: The slit lamp is an essential instrument for eye care. It is used in navigated laser treatment with retina mosaicing to assist diagnosis. Specifics of the imaging setup introduce bothersome illumination artifacts. They not only degrade the quality of the mosaic but may also affect the diagnosis. Existing solutions in SLIM manage to deal with strong glares which corrupt the retinal content entirely while leaving aside the correction of semitransparent specular highlights and lens flare. This introduces ghosting and information loss. We propose an effective technique to detect and correct light reflections of different degrees in SLIM. We rely on the specular-free image concept to obtain glare-free image and use it coupled with a contextually driven probability map to segment the visible part of the retina in every frame before image mosaicing. We then perform the image blending on a subset of all spatially aligned frames. We detect the lens flare and label each pixel as ‘flare’ or ‘non flare’ using a probability map. We then invoke an adequate blending method. We also introduce a new quantitative measure for global photometric quality. We tested on a set of video sequences obtained from slit lamp examination sessions of 11 different patients presenting healthy and unhealthy retinas. The segmentation of glare and visible retina was evaluated and compared to state-of-the-art methods. The correction of lens flare and semitransparent highlight with content-aware blending was applied and its performance was evaluated qualitatively and quantitatively. The experiments demonstrated that integrating the proposed method to the mosaicing framework significantly improves the global photometric quality of the mosaics and outperforms existing works in SLIM.
Databáze: OpenAIRE
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