News

Research

Our lab studies on computer graphics and computer vision techniques, focusing on image, video, and geometry processing for 2D and 3D real-world data and their purpose-specific visualization. You can find recent work of our lab in the following list.

You can also find the entire list of projects from the [RESEARCH] page.

If you are interested in joining our lab as an under- and post-graduate student (and also postdoc), please also visit the [JOIN US] page.

Sparse-View Cone-Beam CT Reconstruction by Bar-by-Bar Neural FDK Algorithm

applications

NDT

Reference: Siqi Wang, Tatsuya Yatagawa, Yutaka Ohtake, Hiromasa Suzuki, "Sparse-View Cone-Beam CT Reconstruction by Bar-by-Bar Neural FDK Algorithm," Nondestructive Testing and Evaluation (2023).

Bin-scanning: Segmentation of X-ray CT volume of binned parts using Morse skeleton graph of distance transform

graphics

geometry

applications

Reference: Yuta Yamauchi, Tatsuya Yatagawa, Yutaka Ohtake, Hiromasa Suzuki, "Bin-scanning: Segmentation of X-ray CT volume of binned parts using Morse skeleton graph of distance transform," Computational Visual Media (2023).

Learning Self-prior for Mesh Denoising using Dual Graph Convolutional Networks

graphics

geometry

deep learning

Reference: Shota Hattori, Tatsuya Yatagawa, Yutaka Ohtake, Hiromasa Suzuki, "Learning Self-prior for Mesh Denoising using Dual Graph Convolutional Networks," European Conference on Computer Vision 2022.

Degree of local symmetry for geometry-aware selective part visualization on CT volumes

applications

NDT

Reference: Nobumichi Yasunami, Tatsuya Yatagawa, Yutaka Ohtake, Hiromasa Suzuki, "Degree of local symmetry for geometry-aware selective part visualization on CT volumes," Nondestructive Testing and Evaluation (2022).

Image Based Measurement of Individual Fiber Lengths for Randomly Oriented Short Fiber Composites

applications

NDT

Reference: Siqi Wang, Tatsuya Yatagawa, Yutaka Ohtake, Hiromasa Suzuki, "Image Based Measurement of Individual Fiber Lengths for Randomly Oriented Short Fiber Composites," Journal of Nondestructive Evaluation (2022).

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