135 related articles for article (PubMed ID: 36220014)
1. Cross modality fusion for modality-specific lung tumor segmentation in PET-CT images.
Zhang X; Zhang B; Deng S; Meng Q; Chen X; Xiang D
Phys Med Biol; 2022 Nov; 67(22):. PubMed ID: 36220014
[TBL] [Abstract][Full Text] [Related]
2. Modality-Specific Segmentation Network for Lung Tumor Segmentation in PET-CT Images.
Xiang D; Zhang B; Lu Y; Deng S
IEEE J Biomed Health Inform; 2023 Mar; 27(3):1237-1248. PubMed ID: 35759605
[TBL] [Abstract][Full Text] [Related]
3. 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]
4. Automated lung tumor delineation on positron emission tomography/computed tomography via a hybrid regional network.
Lei Y; Wang T; Jeong JJ; Janopaul-Naylor J; Kesarwala AH; Roper J; Tian S; Bradley JD; Liu T; Higgins K; Yang X
Med Phys; 2023 Jan; 50(1):274-283. PubMed ID: 36203393
[TBL] [Abstract][Full Text] [Related]
5. MFCNet: A multi-modal fusion and calibration networks for 3D pancreas tumor segmentation on PET-CT images.
Wang F; Cheng C; Cao W; Wu Z; Wang H; Wei W; Yan Z; Liu Z
Comput Biol Med; 2023 Mar; 155():106657. PubMed ID: 36791551
[TBL] [Abstract][Full Text] [Related]
6. A transformer-guided cross-modality adaptive feature fusion framework for esophageal gross tumor volume segmentation.
Yue Y; Li N; Zhang G; Xing W; Zhu Z; Liu X; Song S; Ta D
Comput Methods Programs Biomed; 2024 Jun; 251():108216. PubMed ID: 38761412
[TBL] [Abstract][Full Text] [Related]
7. Whole-body tumor segmentation from PET/CT images using a two-stage cascaded neural network with camouflaged object detection mechanisms.
He J; Zhang Y; Chung M; Wang M; Wang K; Ma Y; Ding X; Li Q; Pu Y
Med Phys; 2023 Oct; 50(10):6151-6162. PubMed ID: 37134002
[TBL] [Abstract][Full Text] [Related]
8. Cross-modality (CT-MRI) prior augmented deep learning for robust lung tumor segmentation from small MR datasets.
Jiang J; Hu YC; Tyagi N; Zhang P; Rimner A; Deasy JO; Veeraraghavan H
Med Phys; 2019 Oct; 46(10):4392-4404. PubMed ID: 31274206
[TBL] [Abstract][Full Text] [Related]
9. Diffuse large B-cell lymphoma segmentation in PET-CT images via hybrid learning for feature fusion.
Yuan C; Zhang M; Huang X; Xie W; Lin X; Zhao W; Li B; Qian D
Med Phys; 2021 Jul; 48(7):3665-3678. PubMed ID: 33735451
[TBL] [Abstract][Full Text] [Related]
10. AATSN: Anatomy Aware Tumor Segmentation Network for PET-CT volumes and images using a lightweight fusion-attention mechanism.
Ahmad I; Xia Y; Cui H; Islam ZU
Comput Biol Med; 2023 May; 157():106748. PubMed ID: 36958235
[TBL] [Abstract][Full Text] [Related]
11. MSRA-Net: Tumor segmentation network based on Multi-scale Residual Attention.
Wu Y; Jiang H; Pang W
Comput Biol Med; 2023 May; 158():106818. PubMed ID: 36966557
[TBL] [Abstract][Full Text] [Related]
12. Simultaneous cosegmentation of tumors in PET-CT images using deep fully convolutional networks.
Zhong Z; Kim Y; Plichta K; Allen BG; Zhou L; Buatti J; Wu X
Med Phys; 2019 Feb; 46(2):619-633. PubMed ID: 30537103
[TBL] [Abstract][Full Text] [Related]
13. DGCBG-Net: A dual-branch network with global cross-modal interaction and boundary guidance for tumor segmentation in PET/CT images.
Zou Z; Zou B; Kui X; Chen Z; Li Y
Comput Methods Programs Biomed; 2024 Jun; 250():108125. PubMed ID: 38631130
[TBL] [Abstract][Full Text] [Related]
14. Tumor co-segmentation in PET/CT using multi-modality fully convolutional neural network.
Zhao X; Li L; Lu W; Tan S
Phys Med Biol; 2018 Dec; 64(1):015011. PubMed ID: 30523964
[TBL] [Abstract][Full Text] [Related]
15. Random Walk and Graph Cut for Co-Segmentation of Lung Tumor on PET-CT Images.
Ju W; Xiang D; Zhang B; Wang L; Kopriva I; Chen X
IEEE Trans Image Process; 2015 Dec; 24(12):5854-67. PubMed ID: 26462198
[TBL] [Abstract][Full Text] [Related]
16. Multimodal Spatial Attention Module for Targeting Multimodal PET-CT Lung Tumor Segmentation.
Fu X; Bi L; Kumar A; Fulham M; Kim J
IEEE J Biomed Health Inform; 2021 Sep; 25(9):3507-3516. PubMed ID: 33591922
[TBL] [Abstract][Full Text] [Related]
17. TG-Net: Combining transformer and GAN for nasopharyngeal carcinoma tumor segmentation based on total-body uEXPLORER PET/CT scanner.
Huang Z; Tang S; Chen Z; Wang G; Shen H; Zhou Y; Wang H; Fan W; Liang D; Hu Y; Hu Z
Comput Biol Med; 2022 Sep; 148():105869. PubMed ID: 35905660
[TBL] [Abstract][Full Text] [Related]
18. Deep Learning for Variational Multimodality Tumor Segmentation in PET/CT.
Li L; Zhao X; Lu W; Tan S
Neurocomputing (Amst); 2020 Jun; 392():277-295. PubMed ID: 32773965
[TBL] [Abstract][Full Text] [Related]
19. Automated Lung Cancer Segmentation Using a PET and CT Dual-Modality Deep Learning Neural Network.
Wang S; Mahon R; Weiss E; Jan N; Taylor RJ; McDonagh PR; Quinn B; Yuan L
Int J Radiat Oncol Biol Phys; 2023 Feb; 115(2):529-539. PubMed ID: 35934160
[TBL] [Abstract][Full Text] [Related]
20. Automatic lung tumor segmentation on PET/CT images using fuzzy Markov random field model.
Guo Y; Feng Y; Sun J; Zhang N; Lin W; Sa Y; Wang P
Comput Math Methods Med; 2014; 2014():401201. PubMed ID: 24987451
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]