379 related articles for article (PubMed ID: 36306574)
1. Multi-scale feature similarity-based weakly supervised lymphoma segmentation in PET/CT images.
Huang Z; Guo Y; Zhang N; Huang X; Decazes P; Becker S; Ruan S
Comput Biol Med; 2022 Dec; 151(Pt A):106230. PubMed ID: 36306574
[TBL] [Abstract][Full Text] [Related]
2. 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]
3. 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]
4. Automated segmentation of lesions and organs at risk on [
Yazdani E; Karamzadeh-Ziarati N; Cheshmi SS; Sadeghi M; Geramifar P; Vosoughi H; Jahromi MK; Kheradpisheh SR
Cancer Imaging; 2024 Feb; 24(1):30. PubMed ID: 38424612
[TBL] [Abstract][Full Text] [Related]
5. HFRU-Net: High-Level Feature Fusion and Recalibration UNet for Automatic Liver and Tumor Segmentation in CT Images.
Kushnure DT; Talbar SN
Comput Methods Programs Biomed; 2022 Jan; 213():106501. PubMed ID: 34752959
[TBL] [Abstract][Full Text] [Related]
6. An iterative multi-path fully convolutional neural network for automatic cardiac segmentation in cine MR images.
Ma Z; Wu X; Wang X; Song Q; Yin Y; Cao K; Wang Y; Zhou J
Med Phys; 2019 Dec; 46(12):5652-5665. PubMed ID: 31605627
[TBL] [Abstract][Full Text] [Related]
7. Learning fuzzy clustering for SPECT/CT segmentation via convolutional neural networks.
Chen J; Li Y; Luna LP; Chung HW; Rowe SP; Du Y; Solnes LB; Frey EC
Med Phys; 2021 Jul; 48(7):3860-3877. PubMed ID: 33905560
[TBL] [Abstract][Full Text] [Related]
8. 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]
9. [Lung parenchyma segmentation based on double scale parallel attention network].
Feng K; Ren L; Wu Y; Li Y; Wang H; Wang G
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2022 Aug; 39(4):721-729. PubMed ID: 36008336
[TBL] [Abstract][Full Text] [Related]
10. DiSegNet: A deep dilated convolutional encoder-decoder architecture for lymph node segmentation on PET/CT images.
Xu G; Cao H; Udupa JK; Tong Y; Torigian DA
Comput Med Imaging Graph; 2021 Mar; 88():101851. PubMed ID: 33465588
[TBL] [Abstract][Full Text] [Related]
11. Fully automatic segmentation of diffuse large B cell lymphoma lesions on 3D FDG-PET/CT for total metabolic tumour volume prediction using a convolutional neural network.
Blanc-Durand P; Jégou S; Kanoun S; Berriolo-Riedinger A; Bodet-Milin C; Kraeber-Bodéré F; Carlier T; Le Gouill S; Casasnovas RO; Meignan M; Itti E
Eur J Nucl Med Mol Imaging; 2021 May; 48(5):1362-1370. PubMed ID: 33097974
[TBL] [Abstract][Full Text] [Related]
12. A multiple-channel and atrous convolution network for ultrasound image segmentation.
Zhang L; Zhang J; Li Z; Song Y
Med Phys; 2020 Dec; 47(12):6270-6285. PubMed ID: 33007105
[TBL] [Abstract][Full Text] [Related]
13. MSFCN-multiple supervised fully convolutional networks for the osteosarcoma segmentation of CT images.
Huang L; Xia W; Zhang B; Qiu B; Gao X
Comput Methods Programs Biomed; 2017 May; 143():67-74. PubMed ID: 28391820
[TBL] [Abstract][Full Text] [Related]
14. ARPM-net: A novel CNN-based adversarial method with Markov random field enhancement for prostate and organs at risk segmentation in pelvic CT images.
Zhang Z; Zhao T; Gay H; Zhang W; Sun B
Med Phys; 2021 Jan; 48(1):227-237. PubMed ID: 33151620
[TBL] [Abstract][Full Text] [Related]
15. 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]
16. Fully automatic multi-organ segmentation for head and neck cancer radiotherapy using shape representation model constrained fully convolutional neural networks.
Tong N; Gou S; Yang S; Ruan D; Sheng K
Med Phys; 2018 Oct; 45(10):4558-4567. PubMed ID: 30136285
[TBL] [Abstract][Full Text] [Related]
17. Fast interactive medical image segmentation with weakly supervised deep learning method.
Girum KB; Créhange G; Hussain R; Lalande A
Int J Comput Assist Radiol Surg; 2020 Sep; 15(9):1437-1444. PubMed ID: 32653985
[TBL] [Abstract][Full Text] [Related]
18. A modality-collaborative convolution and transformer hybrid network for unpaired multi-modal medical image segmentation with limited annotations.
Liu H; Zhuang Y; Song E; Xu X; Ma G; Cetinkaya C; Hung CC
Med Phys; 2023 Sep; 50(9):5460-5478. PubMed ID: 36864700
[TBL] [Abstract][Full Text] [Related]
19. Metabolic Anomaly Appearance Aware U-Net for Automatic Lymphoma Segmentation in Whole-Body PET/CT Scans.
Shi T; Jiang H; Wang M; Diao Z; Zhang G; Yao YD
IEEE J Biomed Health Inform; 2023 May; 27(5):2465-2476. PubMed ID: 37027631
[TBL] [Abstract][Full Text] [Related]
20. Automatic segmentation and grading of ankylosing spondylitis on MR images via lightweight hybrid multi-scale convolutional neural network with reinforcement learning.
Gou S; Lu Y; Tong N; Huang L; Liu N; Han Q
Phys Med Biol; 2021 Oct; 66(20):. PubMed ID: 34517352
[No Abstract] [Full Text] [Related]
[Next] [New Search]
