Reverse Engineering and Additive Manufacturing towards the design of 3D advanced scaffolds for hard tissue regeneration

Fucile, Pierpaolo; Papallo, Ida; Improta, Giovanni; Santis, Roberto De; Gloria, Antonio; Onofrio, Ilaria; D’Antò, Vincenzo; Maietta, Saverio; Russo, Teresa

doi:10.1109/metroi4.2019.8792891

Cited by 13 publications

(21 citation statements)

References 28 publications

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“…Computer models have become a usable method for solving biomedical engineering and are applied to the analysis and measurement of data in the biomedical field (e.g., material mechanical behavior measurement [1][2][3][4], medical image segmentation [5,6], and registration [7][8][9]). Deformable image registration aims to align subject images onto a template space by gradually optimizing the spatial transformation fields consisting of voxel-to-voxel correspondences between template and subject images [10].…”

Section: Introductionmentioning

confidence: 99%

Symmetric Deformable Registration via Learning a Pseudomean for MR Brain Images

Sui

Zheng

et al. 2021

Journal of Healthcare Engineering

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Image registration is a fundamental task in medical imaging analysis, which is commonly used during image-guided interventions and data fusion. In this paper, we present a deep learning architecture to symmetrically learn and predict the deformation field between a pair of images in an unsupervised fashion. To achieve this, we design a deep regression network to predict a deformation field that can be used to align the template-subject image pair. Specifically, instead of estimating the single deformation pathway to align the images, herein, we predict two halfway deformations, which can move the original template and subject into a pseudomean space simultaneously. Therefore, we train a symmetric registration network (S-Net) in this paper. By using a symmetric strategy, the registration can be more accurate and robust particularly on the images with large anatomical variations. Moreover, the smoothness of the deformation is also significantly improved. Experimental results have demonstrated that the trained model can directly predict the symmetric deformations on new image pairs from different databases, consistently producing accurate and robust registration results.

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Section: Introductionmentioning

confidence: 99%

Symmetric Deformable Registration via Learning a Pseudomean for MR Brain Images

Sui

Zheng

et al. 2021

Journal of Healthcare Engineering

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“…A scaffold may be considered as an interconnected porous structure, which is able to support cell adhesion, proliferation, and differentiation, also promoting the extracellular matrix analogue deposition necessary for tissue regeneration. [ 4–7 ]…”

Section: Introductionmentioning

confidence: 99%

“…In this scenario, mechanical features are crucial, as hard tissues (i.e., bone) are stronger (higher strength) and stiffer (higher elastic modulus) in comparison to soft tissues. [ 4,7 ]…”

Section: Introductionmentioning

confidence: 99%

“…Synthetic [i.e., poly(ε‐caprolactone)] and natural polymers (i.e., chitosan, collagen, alginate, agarose, hyaluronic acid, and fibrin) have been largely proposed to manufacture scaffolds for hard and soft tissue regeneration. [ 4–7 ]…”

Section: Introductionmentioning

confidence: 99%

“…Composite devices consisting of polymers reinforced with inorganic nanoparticles were developed. [ 4,7–9 ] The inclusion of nanofillers in the polymeric matrix up to a threshold concentration generally provides an enhancement of the mechanical properties. [ 7–9 ]…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Photo‐Curing 3D Printing and Innovative Design of Porous Composite Structures for Biomedical Applications

Santis

Russo

Fucile

et al. 2021

Macromolecular Symposia

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Light‐activated resins and composites are used in conjunction with a light curing unit and allow an on‐demand process of polymerization. These kinds of materials usually represent the most popular choice in the restorative dental practice. Some works have already highlighted contemporary tendencies in the use of nondegradable scaffolds and mesenchymal stem cells in regenerative medicine. Accordingly, the aim of the current research is to develop 3D porous and light‐activated composite structures with optimized functional properties. Preliminary mechanical and biological tests are carried out.

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Integrated Design Strategy for Additively Manufactured Scaffolds in Tissue Engineering

Fucile

Russo

Santis

et al. 2021

Macromolecular Symposia

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Additive manufacturing technologies allow for the direct fabrication of 3D scaffolds with improved properties for tissue regeneration. In this scenario, design strategies and 3D fiber deposition technique are considered to develop advanced scaffolds with different lay‐down patterns, tailored mechanical and biological properties. 3D poly(ε‐caprolactone) scaffolds are manufactured and surface‐modified (i.e., aminolysis). The effect of surface modification on the mechanical and biological performances of the designed 3D scaffolds is assessed.

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Reverse Engineering and Additive Manufacturing towards the design of 3D advanced scaffolds for hard tissue regeneration

Cited by 13 publications

References 28 publications

Symmetric Deformable Registration via Learning a Pseudomean for MR Brain Images

Symmetric Deformable Registration via Learning a Pseudomean for MR Brain Images

Photo‐Curing 3D Printing and Innovative Design of Porous Composite Structures for Biomedical Applications

Integrated Design Strategy for Additively Manufactured Scaffolds in Tissue Engineering

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