Fluorescence Image Histology Pattern Transformation using Image Style Transfer

Mohammadhassan Izadyyazdanabadi; Evgenii Belykh; Xiaochun Zhao; Leandro Borba Moreira; Sirin Gandhi; Claudio Cavallo; Jennifer Eschbacher; Peter Nakaji; Mark C. Preul; Yezhou Yang

arXiv · 1905.06442

Fluorescence Image Histology Pattern Transformation using Image Style Transfer

Mohammadhassan Izadyyazdanabadi·Evgenii Belykh·Xiaochun Zhao·Leandro Borba Moreira·Sirin Gandhi·Claudio Cavallo·Jennifer Eschbacher·Peter Nakaji·Mark C. Preul·Yezhou Yang

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Abstract

Confocal laser endomicroscopy (CLE) allow on-the-fly in vivo intraoperative imaging in a discreet field of view, especially for brain tumors, rather than extracting tissue for examination ex vivo with conventional light microscopy. Fluorescein sodium-driven CLE imaging is more interactive, rapid, and portable than conventional hematoxylin and eosin (H&E)-staining. However, it has several limitations: CLE images may be contaminated with artifacts (motion, red blood cells, noise), and neuropathologists are mainly trained on colorful stained histology slides like H&E while the CLE images are gray. To improve the diagnostic quality of CLE, we used a micrograph of an H&E slide from a glioma tumor biopsy and image style transfer, a neural network method for integrating the content and style of two images. This was done through minimizing the deviation of the target image from both the content (CLE) and style (H&E) images. The style transferred images were assessed and compared to conventional H&E histology by neurosurgeons and a neuropathologist who then validated the quality enhancement in 100 pairs of original and transformed images. Average reviewers' score on test images showed 84 out of 100 transformed images had fewer artifacts and more noticeable critical structures compared to their original CLE form. By providing images that are more interpretable than the original CLE images and more rapidly acquired than H&E slides, the style transfer method allows a real-time, cellular-level tissue examination using CLE technology that closely resembles the conventional appearance of H&E staining and may yield better diagnostic recognition than original CLE grayscale images.

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BibTeX RIS

Mohammadhassan Izadyyazdanabadi, Evgenii Belykh, Xiaochun Zhao, Leandro Borba Moreira, Sirin Gandhi, Claudio Cavallo, Jennifer Eschbacher, Peter Nakaji, Mark C. Preul, Yezhou Yang. 2019-05-15. Fluorescence Image Histology Pattern Transformation using Image Style Transfer. https://arxiv.org/abs/1905.06442

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