Learning Self-Prior for Mesh Inpainting Using Self-Supervised Graph Convolutional Networks.

This study presents a self-prior-based mesh inpainting framework that requires only an incomplete mesh as input, without the need for any training datasets. Additionally, our method maintains the polygonal mesh format throughout the inpainting process without converting the shape format to an intermediate, such as a voxel grid, a point cloud, or an implicit function, which are typically considered easier for deep neural networks to process. To achieve this goal, we introduce two graph convolutional networks (GCNs): single-resolution GCN (SGCN) and multi-resolution GCN (MGCN), both trained in a self-supervised manner.

Cavity and entrance pore development in ant plant hypocotyls.

Some genera of Rubiaceae in South-eastern Asia are known as typical ant plants. They have large domatia, which form in well-developed hypocotyls in which ants nest. Previously, cavity formation processes were described; however, these reports were dependent on tissue sections of different individuals of different ages.

Ultrasound Imaging With a Flexible Probe Based on Element Array Geometry Estimation Using Deep Neural Network.

Conventionally, ultrasound (US) diagnosis is performed using hand-held rigid probes. Such devices are difficult to be used for long-term monitoring because they need to be continuously pressed against the body to remove the air between the probe and body. Flexible probes, which can deform and effectively adhere to the body, are a promising technology for long-term monitoring applications.

The sinogram polygonizer for reconstructing 3D shapes.

This paper proposes a novel approach, the sinogram polygonizer, for directly reconstructing 3D shapes from sinograms (i.e., the primary output from X-ray computed tomography (CT) scanners consisting of projection image sequences of an object shown from different viewing angles).

CT image segmentation using FEM with optimized boundary condition.

The authors propose a CT image segmentation method using structural analysis that is useful for objects with structural dynamic characteristics. Motivation of our research is from the area of genetic activity. In order to reveal the roles of genes, it is necessary to create mutant mice and measure differences among them by scanning their skeletons with an X-ray CT scanner.