Código QR (código de barras bidimensional)

Unsupervised Metal Artifact Reduction in Dental CBCT Using Fine-Tuned Cycle-Consistent Adversarial Networks

Metal artifacts generated by dental implants significantly degrade cone-beam computed tomography (CBCT) volumes, obscuring critical anatomical structures and compromising diagnostic precision. To address this, an unsupervised deep learning framework has been proposed for Metal Artifact Reduction (MA...

Fuld beskrivelse

Na minha lista:
Principais autores: Thamindu Chamika, Sithum N. A. Dhanapala, Sasindu Nimalaweera, Maheshi B. Dissanayake, Ruwan D. Jayasinghe
Format: Artigo
Sprog:Inglês
Udgivet: MDPI AG 2026-04-01
Serier:Digital
Fag:
cone-beam computed tomography
metal artifact reduction
CycleGAN
unsupervised learning
dental imaging
deep learning
Online adgang:https://www.mdpi.com/2673-6470/6/2/31
Tags: Tilføj Tag
Ingen Tags, Vær først til at tagge denne postø!

Lignende værker