mlsanityData to 7 Oct 2026

Amyloid-Beta Axial Plane PET Synthesis from Structural MRI: An Image Translation Approach for Screening Alzheimer's Disease

arXiv 2309.00569 ↗First posted 1 Sep 2023eess.IV cs.CV cs.LGcited by 0

Not on the map. Why?

Abstract (arXiv)

In this work, an image translation model is implemented to produce synthetic amyloid-beta PET images from structural MRI that are quantitatively accurate. Image pairs of amyloid-beta PET and structural MRI were used to train the model. We found that the synthetic PET images could be produced with a high degree of similarity to truth in terms of shape, contrast and overall high SSIM and PSNR. This work demonstrates that performing structural to quantitative image translation is feasible to enable the access amyloid-beta information from only MRI.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 7 of its 21 references that are in the map. First posted on arXiv 1 Sep 2023.

Builds on

7 of 21 references.

References · 7

  1. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,160
  2. 2016Image-to-Image Translation with Conditional Adversarial Networkscited by 4,510
  3. 2018Generative Adversarial Network in Medical Imaging: A Reviewcited by 257
  4. 2021Image-to-Image Translation: Methods and Applicationscited by 116
  5. 2020Understanding SSIMcited by 75
  6. 2016A Formal Evaluation of PSNR as Quality Measurement Parameter for Image Segmentation Algorithmscited by 42
  7. 2021MRI to PET Cross-Modality Translation using Globally and Locally Aware GAN (GLA-GAN) for Multi-Modal Diagnosis of Alzheimer's Diseasecited by 16

Built on by

Not cited yet.