107 citations · 166 across the 7 of their papers we have counts for
7 papers
Iterative CT Reconstruction via Latent Variable Optimization of Shallow Diffusion Models
Sho Ozaki, Shizuo Kaji, Toshikazu Imae +3
Image-generative artificial intelligence (AI) has garnered significant attention in recent years. In particular, the diffusion model, a core component of generative AI, produces hi…
Training of deep cross-modality conversion models with a small dataset, and their application in megavoltage CT to kilovoltage CT conversion
Sho Ozaki, Shizuo Kaji, Kanabu Nawa +8
In recent years, deep-learning-based image processing has emerged as a valuable tool for medical imaging owing to its high performance. However, the quality of deep-learning-based…
Fast Statistical Iterative Reconstruction for MVCT in TomoTherapy
Sho Ozaki, Akihiro Haga, Edward Chao +8
Statistical iterative reconstruction is expected to improve the image quality of megavoltage computed tomography (MVCT). However, one of the challenges of iterative reconstruction…
Visual enhancement of Cone-beam CT by use of CycleGAN
S. Kida, S. Kaji, K. Nawa +6
Cone-beam computed tomography (CBCT) offers advantages over conventional fan-beam CT in that it requires a shorter time and less exposure to obtain images. CBCT has found a wide va…
Lattice QCD Study for Confinement in Hadrons
H. Suganuma, T. Iritani, F. Okiharu +2
We study three subjects on quark confinement in hadrons in SU(3) lattice QCD. From the accurate lattice calculation for more than 300 different patterns of three-quark (3…
Composite and elementary natures of a1(1260) meson
H. Nagahiro, K. Nawa, S. Ozaki +2
We develop a practical method to analyze the mixing structure of hadrons consisting of two components of quark-composite and hadronic composite. As an example we investigate the pr…