266 related articles for article (PubMed ID: 34325225)
21. 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]
22. C3D-UNET: A Comprehensive 3D Unet for Covid-19 Segmentation with Intact Encoding and Local Attention.
Bao Y; Zeng H; Zhou C; Liu C; Zhang L; Qian D; Wang J; Lu H
Annu Int Conf IEEE Eng Med Biol Soc; 2021 Nov; 2021():2592-2596. PubMed ID: 34891784
[TBL] [Abstract][Full Text] [Related]
23. Three-dimensional lung tumor segmentation from x-ray computed tomography using sparse field active models.
Awad J; Owrangi A; Villemaire L; O'Riordan E; Parraga G; Fenster A
Med Phys; 2012 Feb; 39(2):851-65. PubMed ID: 22320795
[TBL] [Abstract][Full Text] [Related]
24. JCS: An Explainable COVID-19 Diagnosis System by Joint Classification and Segmentation.
Wu YH; Gao SH; Mei J; Xu J; Fan DP; Zhang RG; Cheng MM
IEEE Trans Image Process; 2021; 30():3113-3126. PubMed ID: 33600316
[TBL] [Abstract][Full Text] [Related]
25. 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]
26. Multi-scale attention and deep supervision-based 3D UNet for automatic liver segmentation from CT.
Wang J; Zhang X; Guo L; Shi C; Tamura S
Math Biosci Eng; 2023 Jan; 20(1):1297-1316. PubMed ID: 36650812
[TBL] [Abstract][Full Text] [Related]
27. 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]
28. A study of generalization and compatibility performance of 3D U-Net segmentation on multiple heterogeneous liver CT datasets.
He B; Yin D; Chen X; Luo H; Xiao D; He M; Wang G; Fang C; Liu L; Jia F
BMC Med Imaging; 2021 Nov; 21(1):178. PubMed ID: 34819022
[TBL] [Abstract][Full Text] [Related]
29. Recurrent feature fusion learning for multi-modality pet-ct tumor segmentation.
Bi L; Fulham M; Li N; Liu Q; Song S; Dagan Feng D; Kim J
Comput Methods Programs Biomed; 2021 May; 203():106043. PubMed ID: 33744750
[TBL] [Abstract][Full Text] [Related]
30. Tumorous kidney segmentation in abdominal CT images using active contour and 3D-UNet.
Pandey M; Gupta A
Ir J Med Sci; 2023 Jun; 192(3):1401-1409. PubMed ID: 35930139
[TBL] [Abstract][Full Text] [Related]
31. Attention-VGG16-UNet: a novel deep learning approach for automatic segmentation of the median nerve in ultrasound images.
Huang A; Jiang L; Zhang J; Wang Q
Quant Imaging Med Surg; 2022 Jun; 12(6):3138-3150. PubMed ID: 35655843
[TBL] [Abstract][Full Text] [Related]
32. Volumetric segmentation of ground glass nodule based on 3D attentional cascaded residual U-Net and conditional random field.
Chen H; Liu J; Lu L; Wang T; Xu X; Chu A; Peng W; Gong J; Tang W; Gu Y
Med Phys; 2022 Feb; 49(2):1097-1107. PubMed ID: 34951492
[TBL] [Abstract][Full Text] [Related]
33. A Noise-Robust Framework for Automatic Segmentation of COVID-19 Pneumonia Lesions From CT Images.
Wang G; Liu X; Li C; Xu Z; Ruan J; Zhu H; Meng T; Li K; Huang N; Zhang S
IEEE Trans Med Imaging; 2020 Aug; 39(8):2653-2663. PubMed ID: 32730215
[TBL] [Abstract][Full Text] [Related]
34. Weakly-Supervised Segmentation-Based Quantitative Characterization of Pulmonary Cavity Lesions in CT Scans.
Xing W; Yang Y; Zhou Y; Jiang T; Li Y; Song Y; Hou D; Ta D
IEEE J Transl Eng Health Med; 2024; 12():457-467. PubMed ID: 38899144
[TBL] [Abstract][Full Text] [Related]
35. Hypergraph learning for identification of COVID-19 with CT imaging.
Di D; Shi F; Yan F; Xia L; Mo Z; Ding Z; Shan F; Song B; Li S; Wei Y; Shao Y; Han M; Gao Y; Sui H; Gao Y; Shen D
Med Image Anal; 2021 Feb; 68():101910. PubMed ID: 33285483
[TBL] [Abstract][Full Text] [Related]
36. CoLe-CNN+: Context learning - Convolutional neural network for COVID-19-Ground-Glass-Opacities detection and segmentation.
Pezzano G; Díaz O; Ripoll VR; Radeva P
Comput Biol Med; 2021 Sep; 136():104689. PubMed ID: 34364263
[TBL] [Abstract][Full Text] [Related]
37. Multiscale Local Enhancement Deep Convolutional Networks for the Automated 3D Segmentation of Gross Tumor Volumes in Nasopharyngeal Carcinoma: A Multi-Institutional Dataset Study.
Yang G; Dai Z; Zhang Y; Zhu L; Tan J; Chen Z; Zhang B; Cai C; He Q; Li F; Wang X; Yang W
Front Oncol; 2022; 12():827991. PubMed ID: 35387126
[TBL] [Abstract][Full Text] [Related]
38. A cascaded dual-pathway residual network for lung nodule segmentation in CT images.
Liu H; Cao H; Song E; Ma G; Xu X; Jin R; Jin Y; Hung CC
Phys Med; 2019 Jul; 63():112-121. PubMed ID: 31221402
[TBL] [Abstract][Full Text] [Related]
39. SSA-Net: Spatial self-attention network for COVID-19 pneumonia infection segmentation with semi-supervised few-shot learning.
Wang X; Yuan Y; Guo D; Huang X; Cui Y; Xia M; Wang Z; Bai C; Chen S
Med Image Anal; 2022 Jul; 79():102459. PubMed ID: 35544999
[TBL] [Abstract][Full Text] [Related]
40. COVID-19 lung CT image segmentation using deep learning methods: U-Net versus SegNet.
Saood A; Hatem I
BMC Med Imaging; 2021 Feb; 21(1):19. PubMed ID: 33557772
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
