تقرير
3D Vessel Graph Generation Using Denoising Diffusion
| العنوان: | 3D Vessel Graph Generation Using Denoising Diffusion |
|---|---|
| المؤلفون: | Prabhakar, Chinmay, Shit, Suprosanna, Musio, Fabio, Yang, Kaiyuan, Amiranashvili, Tamaz, Paetzold, Johannes C., Li, Hongwei Bran, Menze, Bjoern |
| سنة النشر: | 2024 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Computer Vision and Pattern Recognition |
| الوصف: | Blood vessel networks, represented as 3D graphs, help predict disease biomarkers, simulate blood flow, and aid in synthetic image generation, relevant in both clinical and pre-clinical settings. However, generating realistic vessel graphs that correspond to an anatomy of interest is challenging. Previous methods aimed at generating vessel trees mostly in an autoregressive style and could not be applied to vessel graphs with cycles such as capillaries or specific anatomical structures such as the Circle of Willis. Addressing this gap, we introduce the first application of \textit{denoising diffusion models} in 3D vessel graph generation. Our contributions include a novel, two-stage generation method that sequentially denoises node coordinates and edges. We experiment with two real-world vessel datasets, consisting of microscopic capillaries and major cerebral vessels, and demonstrate the generalizability of our method for producing diverse, novel, and anatomically plausible vessel graphs. Comment: Accepted to MICCAI 2024 |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2407.05842 |
| رقم الأكسشن: | edsarx.2407.05842 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |