77 related articles for article (PubMed ID: 36086503)
1. Automated Quantification of Inflamed Lung Regions in Chest CT by UNet++ and SegCaps: A Comparative Analysis in COVID-19 Cases.
Bhatia P; Sinha A; Joshi SP; Sarkar R; Ghosh R; Jana S
Annu Int Conf IEEE Eng Med Biol Soc; 2022 Jul; 2022():3785-3788. PubMed ID: 36086503
[TBL] [Abstract][Full Text] [Related]
2. A dual-stage deep convolutional neural network for automatic diagnosis of COVID-19 and pneumonia from chest CT images.
Sadik F; Dastider AG; Subah MR; Mahmud T; Fattah SA
Comput Biol Med; 2022 Oct; 149():105806. PubMed ID: 35994932
[TBL] [Abstract][Full Text] [Related]
3. Anam-Net: Anamorphic Depth Embedding-Based Lightweight CNN for Segmentation of Anomalies in COVID-19 Chest CT Images.
Paluru N; Dayal A; Jenssen HB; Sakinis T; Cenkeramaddi LR; Prakash J; Yalavarthy PK
IEEE Trans Neural Netw Learn Syst; 2021 Mar; 32(3):932-946. PubMed ID: 33544680
[TBL] [Abstract][Full Text] [Related]
4. Association of AI quantified COVID-19 chest CT and patient outcome.
Fang X; Kruger U; Homayounieh F; Chao H; Zhang J; Digumarthy SR; Arru CD; Kalra MK; Yan P
Int J Comput Assist Radiol Surg; 2021 Mar; 16(3):435-445. PubMed ID: 33484428
[TBL] [Abstract][Full Text] [Related]
5. Chest X-ray image phase features for improved diagnosis of COVID-19 using convolutional neural network.
Qi X; Brown LG; Foran DJ; Nosher J; Hacihaliloglu I
Int J Comput Assist Radiol Surg; 2021 Feb; 16(2):197-206. PubMed ID: 33420641
[TBL] [Abstract][Full Text] [Related]
6. 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]
7. PDAtt-Unet: Pyramid Dual-Decoder Attention Unet for Covid-19 infection segmentation from CT-scans.
Bougourzi F; Distante C; Dornaika F; Taleb-Ahmed A
Med Image Anal; 2023 May; 86():102797. PubMed ID: 36966605
[TBL] [Abstract][Full Text] [Related]
8. Segmentation of lung lobes and lesions in chest CT for the classification of COVID-19 severity.
Khomduean P; Phuaudomcharoen P; Boonchu T; Taetragool U; Chamchoy K; Wimolsiri N; Jarrusrojwuttikul T; Chuajak A; Techavipoo U; Tweeatsani N
Sci Rep; 2023 Nov; 13(1):20899. PubMed ID: 38017029
[TBL] [Abstract][Full Text] [Related]
9. A Weakly-Supervised Framework for COVID-19 Classification and Lesion Localization From Chest CT.
Wang X; Deng X; Fu Q; Zhou Q; Feng J; Ma H; Liu W; Zheng C
IEEE Trans Med Imaging; 2020 Aug; 39(8):2615-2625. PubMed ID: 33156775
[TBL] [Abstract][Full Text] [Related]
10. An automated diagnosis and classification of COVID-19 from chest CT images using a transfer learning-based convolutional neural network.
Baghdadi NA; Malki A; Abdelaliem SF; Magdy Balaha H; Badawy M; Elhosseini M
Comput Biol Med; 2022 May; 144():105383. PubMed ID: 35290811
[TBL] [Abstract][Full Text] [Related]
11. Adaptive UNet-based Lung Segmentation and Ensemble Learning with CNN-based Deep Features for Automated COVID-19 Diagnosis.
Das A
Multimed Tools Appl; 2022; 81(4):5407-5441. PubMed ID: 34955679
[TBL] [Abstract][Full Text] [Related]
12. Dense-Unet: a light model for lung fields segmentation in Chest X-Ray images.
Yahyatabar M; Jouvet P; Cheriet F
Annu Int Conf IEEE Eng Med Biol Soc; 2020 Jul; 2020():1242-1245. PubMed ID: 33018212
[TBL] [Abstract][Full Text] [Related]
13. Segmenting lung lesions of COVID-19 from CT images via pyramid pooling improved Unet.
Ma Y; Feng P; He P; Ren Y; Guo X; Yu X; Wei B
Biomed Phys Eng Express; 2021 May; 7(4):. PubMed ID: 33979791
[TBL] [Abstract][Full Text] [Related]
14. MSDS-UNet: A multi-scale deeply supervised 3D U-Net for automatic segmentation of lung tumor in CT.
Yang J; Wu B; Li L; Cao P; Zaiane O
Comput Med Imaging Graph; 2021 Sep; 92():101957. PubMed ID: 34325225
[TBL] [Abstract][Full Text] [Related]
15. Comparison of chest CT severity scoring systems for COVID-19.
Elmokadem AH; Mounir AM; Ramadan ZA; Elsedeiq M; Saleh GA
Eur Radiol; 2022 May; 32(5):3501-3512. PubMed ID: 35031841
[TBL] [Abstract][Full Text] [Related]
16. 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]
17. Classification of COVID-19 patients from chest CT images using multi-objective differential evolution-based convolutional neural networks.
Singh D; Kumar V; Vaishali ; Kaur M
Eur J Clin Microbiol Infect Dis; 2020 Jul; 39(7):1379-1389. PubMed ID: 32337662
[TBL] [Abstract][Full Text] [Related]
18. Lung Lesion Localization of COVID-19 From Chest CT Image: A Novel Weakly Supervised Learning Method.
Yang Z; Zhao L; Wu S; Chen CY
IEEE J Biomed Health Inform; 2021 Jun; 25(6):1864-1872. PubMed ID: 33739926
[TBL] [Abstract][Full Text] [Related]
19. Diagnosis of COVID-19 using CT scan images and deep learning techniques.
Shah V; Keniya R; Shridharani A; Punjabi M; Shah J; Mehendale N
Emerg Radiol; 2021 Jun; 28(3):497-505. PubMed ID: 33523309
[TBL] [Abstract][Full Text] [Related]
20. Segmentation of lung parenchyma in CT images using CNN trained with the clustering algorithm generated dataset.
Xu M; Qi S; Yue Y; Teng Y; Xu L; Yao Y; Qian W
Biomed Eng Online; 2019 Jan; 18(1):2. PubMed ID: 30602393
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
