Dataset Information

Perceptual Translucency in 3D Printing Using Surface Texture.

ABSTRACT: We propose a method of reproducing perceptual translucency in three-dimensional printing. In contrast to most conventional methods, which reproduce the physical properties of translucency, we focus on the perceptual aspects of translucency. Humans are known to rely on simple cues to perceive translucency, and we develop a method of reproducing these cues using the gradation of surface textures. Textures are designed to reproduce the intensity distribution of the shading and thus provide a cue for the perception of translucency. In creating textures, we adopt computer graphics to develop an image-based optimization method. We validate the effectiveness of the method through subjective evaluation experiments using three-dimensionally printed objects. The results of the validation suggest that the proposed method using texture may increase perceptual translucency under specific conditions. As a method for translucent 3D printing, our method has the limitation that it depends on the observation conditions; however, it provides knowledge to the field of perception that the human visual system can be cheated by only surface textures.

SUBMITTER: Nagasawa K

PROVIDER: S-EPMC10219096 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature

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Perceptual Translucency in 3D Printing Using Surface Texture.

Nagasawa Kazuki K Ono Kamui K Arai Wataru W Tsumura Norimichi N

Journal of imaging 20230522 5

We propose a method of reproducing perceptual translucency in three-dimensional printing. In contrast to most conventional methods, which reproduce the physical properties of translucency, we focus on the perceptual aspects of translucency. Humans are known to rely on simple cues to perceive translucency, and we develop a method of reproducing these cues using the gradation of surface textures. Textures are designed to reproduce the intensity distribution of the shading and thus provide a cue fo ...[more]

PMID: 37233324

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Project description:Additive manufacturing promises to revolutionize manufacturing industries. However, 3D printing of novel build materials is currently limited by constraints inherent to printer designs. In this work, a bench-top powder melt extrusion (PME) 3D printer head was designed and fabricated to print parts directly from powder-based materials rather than filament. The final design of the PME printer head evolved from the Rich Rap Universal Pellet Extruder (RRUPE) design and was realized through an iterative approach. The PME printer was made possible by modifications to the funnel shape, pressure applied to the extrudate by the auger, and hot end structure. Through comparison of parts printed with the PME printer with those from a commercially available fused filament fabrication (FFF) 3D printer using common thermoplastics poly(lactide) (PLA), high impact poly (styrene) (HIPS), and acrylonitrile butadiene styrene (ABS) powders (< 1 mm in diameter), evaluation of the printer performance was performed. For each build material, the PME printed objects show comparable viscoelastic properties by dynamic mechanical analysis (DMA) to those of the FFF objects. However, due to a significant difference in printer resolution between PME (X-Y resolution of 0.8 mm and a Z-layer height calibrated to 0.1 mm) and FFF (X-Y resolution of 0.4 mm and a Z-layer height of 0.18 mm), as well as, an inherently more inconsistent feed of build material for PME than FFF, the resulting print quality, determined by a dimensional analysis and surface roughness comparisons, of the PME printed objects was lower than that of the FFF printed parts based on the print layer uniformity and structure. Further, due to the poorer print resolution and inherent inconsistent build material feed of the PME, the bulk tensile strength and Young's moduli of the objects printed by PME were lower and more inconsistent (49.2 ± 10.7 MPa and 1620 ± 375 MPa, respectively) than those of FFF printed objects (57.7 ± 2.31 MPa and 2160 ± 179 MPa, respectively). Nevertheless, PME print methods promise an opportunity to provide a platform on which it is possible to rapidly prototype a myriad of thermoplastic materials for 3D printing.

Project description:ObjectiveThe objective of this study was to evaluate the robustness and reproducibility of computed tomography-based texture analysis (CTTA) metrics extracted from CT images of a customized texture phantom built for assessing the association of texture metrics to three-dimensional (3D) printed progressively increasing textural heterogeneity.Materials and methodsA custom-built 3D-printed texture phantom comprising of six texture patterns was used to evaluate the robustness and reproducibility of a radiomics panel under a variety of routine abdominal imaging protocols. The phantom was scanned on four CT scanners (Philips, Canon, GE, and Siemens) to assess reproducibility. The robustness assessment was conducted by imaging the texture phantom across different CT imaging parameters such as slice thickness, field of view (FOV), tube voltage, and tube current for each scanner. The texture panel comprised of 387 features belonging to 15 subgroups of texture extraction methods (e.g., Gray-level Co-occurrence Matrix: GLCM). Twelve unique image settings were tested on all the four scanners (e.g., FOV125). Interclass correlation two-way mixed with absolute agreement (ICC3) was used to assess the robustness and reproducibility of radiomic features. Linear regression was used to test the association between change in radiomic features and increased texture heterogeneity. Results were summarized in heat maps.ResultsA total of 5612 (23.2%) of 24 090 features showed excellent robustness and reproducibility (ICC ≥ 0.9). Intensity, GLCM 3D, and gray-level run length matrix (GLRLM) 3D features showed best performance. Among imaging variables, changes in slice thickness affected all metrics more intensely compared to other imaging variables in reducing the ICC3. From the analysis of linear trend effect of the CTTA metrics, the top three metrics with high linear correlations across all scanners and scanning settings were from the GLRLM 2D/3D and discrete cosine transform (DCT) texture family.ConclusionThe choice of scanner and imaging protocols affect texture metrics. Furthermore, not all CTTA metrics have a linear association with linearly varying texture patterns.

Dataset Information

Perceptual Translucency in 3D Printing Using Surface Texture.

Publications

Perceptual Translucency in 3D Printing Using Surface Texture.

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