Resolution-enhanced digital epiluminescence microscopy using deep computational optics

Dino Kabiljagic; Alexander Wong

doi:10.1117/12.2507484

4 March 2019 Resolution-enhanced digital epiluminescence microscopy using deep computational optics

Dino Kabiljagic, Alexander Wong

Proceedings Volume 10881, Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues XVII; 108811P (2019) https://doi.org/10.1117/12.2507484
Event: SPIE BiOS, 2019, San Francisco, California, United States

Abstract

The standard practice employed by dermatologists for examining skin lesions is dermoscopy, where an epiluminesence microscope (ELM) is used to examine the skin chrominance and micro-structural characteristics for anomalies. Conventional ELM instruments are being replaced by digital ELM instruments that enable der- matologists and other health care practitioners to digitally capture, archive, and analyze skin lesions using computer-aided diagnosis (CAD) software. One of the limiting factors of digital ELM is the fundamental trade- off between spatial resolution and field-of-view (FOV), where a larger FOV (which is needed to allow for larger skin lesions to be examined in their entirety) can be achieved by reducing magnification at the cost of spatial resolution (leading to a loss of fine details that can be indicative of malignancy and disease). Here, we introduce deep computational optics (DCO) for the purpose of resolution-enhanced digital ELM to improve the balance between spatial resolution and FOV. More specifically, the multitude of parameters of a deep computational model for numerically magnifying digital ELM images are learned through a wealth of low-resolution and high- resolution digital ELM image pairs. The proposed DCO approach was experimentally validated, demonstrating improvements in the spatial resolution of the resolution-enhanced digital ELM by two-fold while maintaining FOV.

Citation Download Citation

Dino Kabiljagic and Alexander Wong "Resolution-enhanced digital epiluminescence microscopy using deep computational optics", Proc. SPIE 10881, Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues XVII, 108811P (4 March 2019); https://doi.org/10.1117/12.2507484

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KEYWORDS

Digital imaging

Skin

Optical signal processing

Computational imaging

Spatial resolution

Skin cancer

Image enhancement

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