STEDNet: Swin transformer‐based encoder–decoder network for noise reduction in low‐dose CT

Background Low‐dose computed tomography (LDCT) can reduce the dose of X‐ray radiation, making it increasingly significant for routine clinical diagnosis and treatment planning. However, the noise introduced by low‐dose X‐ray exposure degrades the quality of CT images, affecting the accuracy of clini...

Celý popis

Podrobná bibliografia

Vydané v:	Medical physics (Lancaster) Ročník 50; číslo 7; s. 4443 - 4458
Hlavní autori:	Zhu, Linlin, Han, Yu, Xi, Xiaoqi, Fu, Huijuan, Tan, Siyu, Liu, Mengnan, Yang, Shuangzhan, Liu, Chang, Li, Lei, Yan, Bin
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States 01.07.2023
Predmet:	Algorithms deep learning encoder–decoder Image Processing, Computer-Assisted - methods low‐dose CT Radiation Dosage Signal-To-Noise Ratio Swin transformer Tomography, X-Ray Computed - methods low-dose CT Swin transformer deep learning encoder-decoder
ISSN:	0094-2405, 2473-4209, 2473-4209
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!