Abstract
In the current work, a pix2pix conditional generative adversarial network has been evaluated as a potential solution for generating adequately accurate synthesized morphological X-ray images by translating standard photographic images of mice. Such an approach will benefit 2D functional molecular imaging techniques, such as planar radioisotope and/or fluorescence/bioluminescence imaging, by providing high-resolution information for anatomical mapping, but not for diagnosis, using conventional photographic sensors. Planar functional imaging offers an efficient alternative to biodistribution ex vivo studies and/or 3D high-end molecular imaging systems since it can be effectively used to track new tracers and study the accumulation from zero point in time post-injection. The superimposition of functional information with an artificially produced X-ray image may enhance overall image information in such systems without added complexity and cost. The network has been trained in 700 input (photography)/ground truth (X-ray) paired mouse images and evaluated using a test dataset composed of 80 photographic images and 80 ground truth X-ray images. Performance metrics such as peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM) and Fréchet inception distance (FID) were used to quantitatively evaluate the proposed approach in the acquired dataset.
Highlights
Drug discovery aims in identifying novel candidate treatments against diseases
Pix2pix is a common framework based on conditional Generative Adversarial Networks, which predict pixels from pixels in any dataset, in which the aligned image pairs vary in the visual representation, but the renderings for, e.g., edges, stay the same (Figure 1)
The results demonstrate the ability of the trained networks to efficiently map the photographic mouse image to an X-ray scan in terms of animal mapping, but not for diagnosis, as the information of the actual structure of mouse cannot be generated
Summary
A crucial part in the preclinical evaluation of drug discovery is performed on the basis of biodistribution ex vivo studies that aim in monitoring the interaction of radioisotope- or fluorescence-labeled candidate drugs on animal subjects invasively. This invasive method, a gold standard, raises economical and ethical issues due to the large number of required animals [3]. Non-invasive methods, such as molecular imaging, have been proposed, aiming in improving animal handling and catalyzing the necessary time required for biodistribution ex vivo studies
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