Summary of Diffusion Based Multi-domain Neuroimaging Harmonization Method with Preservation Of Anatomical Details, by Haoyu Lan et al.
Diffusion based multi-domain neuroimaging harmonization method with preservation of anatomical details
by Haoyu Lan, Bino A. Varghese, Nasim Sheikh-Bahaei, Farshid Sepehrband, Arthur W Toga, Jeiran Choupan
First submitted to arxiv on: 1 Sep 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI); Image and Video Processing (eess.IV)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed method utilizes a denoising diffusion probabilistic model to harmonize images from multiple domains in neuroimaging studies. This addresses technical variability caused by batch differences across sites, hindering data aggregation and impacting study reliability. The model produces high-fidelity images while preserving anatomical details and differentiating batch differences at each step. Compared to GAN-based methods, which are limited to harmonizing two domains per model, the proposed method demonstrates superior capability in harmonizing multiple domains. The method is tested on public neuroimaging datasets ADNI1 and ABIDE II, yielding consistent anatomy preservation and superior FID scores compared to GAN-based methods. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary A new way of making brain scan images look similar across different machines has been developed. This helps researchers study the brain more accurately by reducing errors caused by differences in how each machine takes pictures. The method uses a special kind of computer model that produces high-quality images while keeping important details like anatomy intact. It’s better than other methods because it can combine images from multiple sources, not just two. Tests showed that this new method works well on real brain scan datasets and provides more accurate results. |
Keywords
» Artificial intelligence » Diffusion » Gan » Probabilistic model
