Three-dimensional (3D) printing offers the promise of fabricating optical phantoms with arbitrary geometry, but commercially available thermoplastics provide only a small range of physiologically relevant absorption (µa) and reduced scattering (µs`) values. Here we demonstrate customizable acrylonitrile butadiene styrene (ABS) filaments for dual extrusion 3D printing of tissue mimicking optical phantoms. µa and µs` values were adjusted by incorporating nigrosin and titanium dioxide (TiO2) in the filament extrusion process. A wide range of physiologically relevant optical properties was demonstrated with an average repeatability within 11.5% for µa and 7.71% for µs`. Additionally, a mouse-simulating phantom, which mimicked both the geometry and optical properties of a hairless mouse with an implanted xenograft tumor, was printed using dual extrusion methods. 3D printed tumor optical properties matched the live tumor with less than 3% error at a wavelength of 659 nm. 3D printing with user defined optical properties may provide a viable method for durable optically diffusive phantoms for instrument characterization and calibration.

We present a deep learning framework for widefield, content-aware estimation of absorption and scattering coefficients of tissues, called Generative Adversarial Network Prediction of Optical Properties (GANPOP). Spatial frequency domain imaging is used to obtain ground-truth optical properties from in vivo human hands, freshly resected human esophagectomy samples and homogeneous tissue phantoms. Images of objects with either flat-field or structured illumination are paired with registered optical property maps and are used to train conditional generative adversarial networks that estimate optical properties from a single input image. We benchmark this approach by comparing GANPOP to a single-snapshot optical property (SSOP) technique, using a normalized mean absolute error (NMAE) metric. In human gastrointestinal specimens, GANPOP estimates both reduced scattering and absorption coefficients at 660 nm from a single 0.2 mm -1 spatial frequency illumination image with 58% higher accuracy than SSOP. When applied to both in vivo and ex vivo swine tissues, a GANPOP model trained solely on human specimens and phantoms estimates optical properties with approximately 43% improvement over SSOP, indicating adaptability to sample variety. Moreover, we demonstrate that GANPOP estimates optical properties from flat-field illumination images with similar error to SSOP, which requires structuredillumination. Given a training set that appropriately spans the target domain, GANPOP has the potential to enable rapid and accurate wide-field measurements of optical properties, even from conventional imaging systems with flat-field illumination.Index Terms-optical imaging, tissue optical properties, neural networks, machine learning, spatial frequency domain imaging arXiv:1906.05360v2 [eess.IV]

As the incidence of esophageal adenocarcinoma continues to rise, there is a need for improved imaging technologies with contrast to abnormal esophageal tissues. To inform the design of optical technologies that meet this need, we characterize the spatial distribution of the scattering and absorption properties from 471 to 851 nm of eight resected human esophagi tissues using Spatial Frequency Domain Imaging. Histopathology was used to categorize tissue types, including normal, inflammation, fibrotic, ulceration, Barrett's Esophagus and squamous cell carcinoma. Average absorption and reduced scattering coefficients of normal tissues were 0.211 ± 0.051 and 1.20 ± 0.18 mm−1, respectively at 471 nm, and both values decreased monotonically with increasing wavelength. Fibrotic tissue exhibited at least 68% larger scattering signal across all wavelengths, while squamous cell carcinoma exhibited a 36% decrease in scattering at 471 nm. We additionally image the esophagus with high spatial frequencies up to 0.5 mm−1 and show strong reflectance contrast to tissue treated with radiation. Lastly, we observe that esophageal absorption and scattering values change by an average of 9.4% and 2.7% respectively over a 30 minute duration post‐resection. These results may guide system design for the diagnosis, prevention and monitoring of esophageal pathologies.