List-Mode PET Image Reconstruction Using Dykstra-Like Splitting

no code implementations • 1 Mar 2024 • Kibo Ote, Fumio Hashimoto, Yuya Onishi, Yasuomi Ouchi

Convergence of the block iterative method in image reconstruction for positron emission tomography (PET) requires careful control of relaxation parameters, which is a challenging task.

Denoising Image Reconstruction

List-Mode PET Image Reconstruction Using Deep Image Prior

no code implementations • 28 Apr 2022 • Kibo Ote, Fumio Hashimoto, Yuya Onishi, Takashi Isobe, Yasuomi Ouchi

However, the application of deep learning techniques to list-mode PET image reconstruction has not been progressed because list data is a sequence of bit codes and unsuitable for processing by convolutional neural networks (CNN).

Image Reconstruction

Anatomical-Guided Attention Enhances Unsupervised PET Image Denoising Performance

no code implementations • 2 Sep 2021 • Yuya Onishi, Fumio Hashimoto, Kibo Ote, Hiroyuki Ohba, Ryosuke Ota, Etsuji Yoshikawa, Yasuomi Ouchi

Although supervised convolutional neural networks (CNNs) often outperform conventional alternatives for denoising positron emission tomography (PET) images, they require many low- and high-quality reference PET image pairs.

Decoder Image Denoising