566 related articles for article (PubMed ID: 31307019)
1. An investigation of quantitative accuracy for deep learning based denoising in oncological PET.
Lu W; Onofrey JA; Lu Y; Shi L; Ma T; Liu Y; Liu C
Phys Med Biol; 2019 Aug; 64(16):165019. PubMed ID: 31307019
[TBL] [Abstract][Full Text] [Related]
2. Deep learning generation of preclinical positron emission tomography (PET) images from low-count PET with task-based performance assessment.
Dutta K; Laforest R; Luo J; Jha AK; Shoghi KI
Med Phys; 2024 Jun; 51(6):4324-4339. PubMed ID: 38710222
[TBL] [Abstract][Full Text] [Related]
3. Noise reduction with cross-tracer and cross-protocol deep transfer learning for low-dose PET.
Liu H; Wu J; Lu W; Onofrey JA; Liu YH; Liu C
Phys Med Biol; 2020 Sep; 65(18):185006. PubMed ID: 32924973
[TBL] [Abstract][Full Text] [Related]
4. Virtual high-count PET image generation using a deep learning method.
Liu J; Ren S; Wang R; Mirian N; Tsai YJ; Kulon M; Pucar D; Chen MK; Liu C
Med Phys; 2022 Sep; 49(9):5830-5840. PubMed ID: 35880541
[TBL] [Abstract][Full Text] [Related]
5. Dose reduction and image enhancement in micro-CT using deep learning.
Muller FM; Maebe J; Vanhove C; Vandenberghe S
Med Phys; 2023 Sep; 50(9):5643-5656. PubMed ID: 36994779
[TBL] [Abstract][Full Text] [Related]
6. PET image denoising using unsupervised deep learning.
Cui J; Gong K; Guo N; Wu C; Meng X; Kim K; Zheng K; Wu Z; Fu L; Xu B; Zhu Z; Tian J; Liu H; Li Q
Eur J Nucl Med Mol Imaging; 2019 Dec; 46(13):2780-2789. PubMed ID: 31468181
[TBL] [Abstract][Full Text] [Related]
7. Utilizing deep learning techniques to improve image quality and noise reduction in preclinical low-dose PET images in the sinogram domain.
Manoj Doss KK; Chen JC
Med Phys; 2024 Jan; 51(1):209-223. PubMed ID: 37966121
[TBL] [Abstract][Full Text] [Related]
8. Higher SNR PET image prediction using a deep learning model and MRI image.
Liu CC; Qi J
Phys Med Biol; 2019 May; 64(11):115004. PubMed ID: 30844784
[TBL] [Abstract][Full Text] [Related]
9. Deep learning with noise-to-noise training for denoising in SPECT myocardial perfusion imaging.
Liu J; Yang Y; Wernick MN; Pretorius PH; King MA
Med Phys; 2021 Jan; 48(1):156-168. PubMed ID: 33145782
[TBL] [Abstract][Full Text] [Related]
10. Supervised learning with cyclegan for low-dose FDG PET image denoising.
Zhou L; Schaefferkoetter JD; Tham IWK; Huang G; Yan J
Med Image Anal; 2020 Oct; 65():101770. PubMed ID: 32674043
[TBL] [Abstract][Full Text] [Related]
11. Spatial adaptive and transformer fusion network (STFNet) for low-count PET blind denoising with MRI.
Zhang L; Xiao Z; Zhou C; Yuan J; He Q; Yang Y; Liu X; Liang D; Zheng H; Fan W; Zhang X; Hu Z
Med Phys; 2022 Jan; 49(1):343-356. PubMed ID: 34796526
[TBL] [Abstract][Full Text] [Related]
12. Image Denoising of Low-Dose PET Mouse Scans with Deep Learning: Validation Study for Preclinical Imaging Applicability.
Muller FM; Vervenne B; Maebe J; Blankemeyer E; Sellmyer MA; Zhou R; Karp JS; Vanhove C; Vandenberghe S
Mol Imaging Biol; 2024 Feb; 26(1):101-113. PubMed ID: 37875748
[TBL] [Abstract][Full Text] [Related]
13. Feasibility evaluation of PET scan-time reduction for diagnosing amyloid-β levels in Alzheimer's disease patients using a deep-learning-based denoising algorithm.
Peng Z; Ni M; Shan H; Lu Y; Li Y; Zhang Y; Pei X; Chen Z; Xie Q; Wang S; Xu XG
Comput Biol Med; 2021 Nov; 138():104919. PubMed ID: 34655898
[TBL] [Abstract][Full Text] [Related]
14. Head and neck synthetic CT generated from ultra-low-dose cone-beam CT following Image Gently Protocol using deep neural network.
Yuan N; Rao S; Chen Q; Sensoy L; Qi J; Rong Y
Med Phys; 2022 May; 49(5):3263-3277. PubMed ID: 35229904
[TBL] [Abstract][Full Text] [Related]
15. Deep-learning-based direct inversion for material decomposition.
Gong H; Tao S; Rajendran K; Zhou W; McCollough CH; Leng S
Med Phys; 2020 Dec; 47(12):6294-6309. PubMed ID: 33020942
[TBL] [Abstract][Full Text] [Related]
16. Deep learning-based whole-body PSMA PET/CT attenuation correction utilizing Pix-2-Pix GAN.
Ma KC; Mena E; Lindenberg L; Lay NS; Eclarinal P; Citrin DE; Pinto PA; Wood BJ; Dahut WL; Gulley JL; Madan RA; Choyke PL; Turkbey IB; Harmon SA
Oncotarget; 2024 May; 15():288-300. PubMed ID: 38712741
[TBL] [Abstract][Full Text] [Related]
17. Spatially guided nonlocal mean approach for denoising of PET images.
Arabi H; Zaidi H
Med Phys; 2020 Apr; 47(4):1656-1669. PubMed ID: 31955433
[TBL] [Abstract][Full Text] [Related]
18. A method to assess image quality for Low-dose PET: analysis of SNR, CNR, bias and image noise.
Yan J; Schaefferkoette J; Conti M; Townsend D
Cancer Imaging; 2016 Aug; 16(1):26. PubMed ID: 27565136
[TBL] [Abstract][Full Text] [Related]
19. A back-projection-and-filtering-like (BPF-like) reconstruction method with the deep learning filtration from listmode data in TOF-PET.
Lv L; Zeng GL; Zan Y; Hong X; Guo M; Chen G; Tao W; Ding W; Huang Q
Med Phys; 2022 Apr; 49(4):2531-2544. PubMed ID: 35122265
[TBL] [Abstract][Full Text] [Related]
20. High-quality PET image synthesis from ultra-low-dose PET/MRI using bi-task deep learning.
Sun H; Jiang Y; Yuan J; Wang H; Liang D; Fan W; Hu Z; Zhang N
Quant Imaging Med Surg; 2022 Dec; 12(12):5326-5342. PubMed ID: 36465830
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
