183 related articles for article (PubMed ID: 34092815)
1. Lung segmentation and automatic detection of COVID-19 using radiomic features from chest CT images.
Zhao C; Xu Y; He Z; Tang J; Zhang Y; Han J; Shi Y; Zhou W
Pattern Recognit; 2021 Nov; 119():108071. PubMed ID: 34092815
[TBL] [Abstract][Full Text] [Related]
2. Abnormal lung quantification in chest CT images of COVID-19 patients with deep learning and its application to severity prediction.
Shan F; Gao Y; Wang J; Shi W; Shi N; Han M; Xue Z; Shen D; Shi Y
Med Phys; 2021 Apr; 48(4):1633-1645. PubMed ID: 33225476
[TBL] [Abstract][Full Text] [Related]
3. Automated deep learning-based segmentation of COVID-19 lesions from chest computed tomography images.
Salehi M; Ardekani MA; Taramsari AB; Ghaffari H; Haghparast M
Pol J Radiol; 2022; 87():e478-e486. PubMed ID: 36091652
[TBL] [Abstract][Full Text] [Related]
4. Application of nnU-Net for Automatic Segmentation of Lung Lesions on CT Images and Its Implication for Radiomic Models.
Ferrante M; Rinaldi L; Botta F; Hu X; Dolp A; Minotti M; De Piano F; Funicelli G; Volpe S; Bellerba F; De Marco P; Raimondi S; Rizzo S; Shi K; Cremonesi M; Jereczek-Fossa BA; Spaggiari L; De Marinis F; Orecchia R; Origgi D
J Clin Med; 2022 Dec; 11(24):. PubMed ID: 36555950
[TBL] [Abstract][Full Text] [Related]
5. COLI-Net: Deep learning-assisted fully automated COVID-19 lung and infection pneumonia lesion detection and segmentation from chest computed tomography images.
Shiri I; Arabi H; Salimi Y; Sanaat A; Akhavanallaf A; Hajianfar G; Askari D; Moradi S; Mansouri Z; Pakbin M; Sandoughdaran S; Abdollahi H; Radmard AR; Rezaei-Kalantari K; Ghelich Oghli M; Zaidi H
Int J Imaging Syst Technol; 2022 Jan; 32(1):12-25. PubMed ID: 34898850
[TBL] [Abstract][Full Text] [Related]
6. Automatic prostate segmentation using deep learning on clinically diverse 3D transrectal ultrasound images.
Orlando N; Gillies DJ; Gyacskov I; Romagnoli C; D'Souza D; Fenster A
Med Phys; 2020 Jun; 47(6):2413-2426. PubMed ID: 32166768
[TBL] [Abstract][Full Text] [Related]
7. An integrated segmentation and shape-based classification scheme for distinguishing adenocarcinomas from granulomas on lung CT.
Alilou M; Beig N; Orooji M; Rajiah P; Velcheti V; Rakshit S; Reddy N; Yang M; Jacono F; Gilkeson RC; Linden P; Madabhushi A
Med Phys; 2017 Jul; 44(7):3556-3569. PubMed ID: 28295386
[TBL] [Abstract][Full Text] [Related]
8. Learning-based automatic segmentation of arteriovenous malformations on contrast CT images in brain stereotactic radiosurgery.
Wang T; Lei Y; Tian S; Jiang X; Zhou J; Liu T; Dresser S; Curran WJ; Shu HK; Yang X
Med Phys; 2019 Jul; 46(7):3133-3141. PubMed ID: 31050804
[TBL] [Abstract][Full Text] [Related]
9. Deep learning-based automatic segmentation of meningioma from multiparametric MRI for preoperative meningioma differentiation using radiomic features: a multicentre study.
Chen H; Li S; Zhang Y; Liu L; Lv X; Yi Y; Ruan G; Ke C; Feng Y
Eur Radiol; 2022 Oct; 32(10):7248-7259. PubMed ID: 35420299
[TBL] [Abstract][Full Text] [Related]
10. From community-acquired pneumonia to COVID-19: a deep learning-based method for quantitative analysis of COVID-19 on thick-section CT scans.
Li Z; Zhong Z; Li Y; Zhang T; Gao L; Jin D; Sun Y; Ye X; Yu L; Hu Z; Xiao J; Huang L; Tang Y
Eur Radiol; 2020 Dec; 30(12):6828-6837. PubMed ID: 32683550
[TBL] [Abstract][Full Text] [Related]
11. CAD systems for COVID-19 diagnosis and disease stage classification by segmentation of infected regions from CT images.
Alshayeji MH; ChandraBhasi Sindhu S; Abed S
BMC Bioinformatics; 2022 Jul; 23(1):264. PubMed ID: 35794537
[TBL] [Abstract][Full Text] [Related]
12. MultiR-Net: A Novel Joint Learning Network for COVID-19 segmentation and classification.
Li CF; Xu YD; Ding XH; Zhao JJ; Du RQ; Wu LZ; Sun WP
Comput Biol Med; 2022 May; 144():105340. PubMed ID: 35305504
[TBL] [Abstract][Full Text] [Related]
13. Segmentation and suppression of pulmonary vessels in low-dose chest CT scans.
Gu X; Wang J; Zhao J; Li Q
Med Phys; 2019 Aug; 46(8):3603-3614. PubMed ID: 31240721
[TBL] [Abstract][Full Text] [Related]
14. Deep learning-based bronchial tree-guided semi-automatic segmentation of pulmonary segments in computed tomography images.
Chen Z; Wo BWB; Chan OL; Huang YH; Teng X; Zhang J; Dong Y; Xiao L; Ren G; Cai J
Quant Imaging Med Surg; 2024 Feb; 14(2):1636-1651. PubMed ID: 38415134
[TBL] [Abstract][Full Text] [Related]
15. Two-stage hybrid network for segmentation of COVID-19 pneumonia lesions in CT images: a multicenter study.
Shang Y; Wei Z; Hui H; Li X; Li L; Yu Y; Lu L; Li L; Li H; Yang Q; Wang M; Zhan M; Wang W; Zhang G; Wu X; Wang L; Liu J; Tian J; Zha Y
Med Biol Eng Comput; 2022 Sep; 60(9):2721-2736. PubMed ID: 35856130
[TBL] [Abstract][Full Text] [Related]
16. Automatic multiorgan segmentation in thorax CT images using U-net-GAN.
Dong X; Lei Y; Wang T; Thomas M; Tang L; Curran WJ; Liu T; Yang X
Med Phys; 2019 May; 46(5):2157-2168. PubMed ID: 30810231
[TBL] [Abstract][Full Text] [Related]
17. MSD-Net: Multi-Scale Discriminative Network for COVID-19 Lung Infection Segmentation on CT.
Zheng B; Liu Y; Zhu Y; Yu F; Jiang T; Yang D; Xu T
IEEE Access; 2020; 8():185786-185795. PubMed ID: 34812359
[TBL] [Abstract][Full Text] [Related]
18. Reproducibility and non-redundancy of radiomic features extracted from arterial phase CT scans in hepatocellular carcinoma patients: impact of tumor segmentation variability.
Qiu Q; Duan J; Duan Z; Meng X; Ma C; Zhu J; Lu J; Liu T; Yin Y
Quant Imaging Med Surg; 2019 Mar; 9(3):453-464. PubMed ID: 31032192
[TBL] [Abstract][Full Text] [Related]
19. A semiautomatic segmentation method for prostate in CT images using local texture classification and statistical shape modeling.
Shahedi M; Halicek M; Guo R; Zhang G; Schuster DM; Fei B
Med Phys; 2018 Jun; 45(6):2527-2541. PubMed ID: 29611216
[TBL] [Abstract][Full Text] [Related]
20. Self-supervised region-aware segmentation of COVID-19 CT images using 3D GAN and contrastive learning.
Shabani S; Homayounfar M; Vardhanabhuti V; Nikouei Mahani MA; Koohi-Moghadam M
Comput Biol Med; 2022 Oct; 149():106033. PubMed ID: 36041270
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]