141 related articles for article (PubMed ID: 30918620)
1. Dynamic Regulation of Level Set Parameters Using 3D Convolutional Neural Network for Liver Tumor Segmentation.
Deng Z; Guo Q; Zhu Z
J Healthc Eng; 2019; 2019():4321645. PubMed ID: 30918620
[TBL] [Abstract][Full Text] [Related]
2. Adaptive Estimation of Active Contour Parameters Using Convolutional Neural Networks and Texture Analysis.
Hoogi A; Subramaniam A; Veerapaneni R; Rubin DL
IEEE Trans Med Imaging; 2017 Mar; 36(3):781-791. PubMed ID: 28113927
[TBL] [Abstract][Full Text] [Related]
3. Liver tumor segmentation based on 3D convolutional neural network with dual scale.
Meng L; Tian Y; Bu S
J Appl Clin Med Phys; 2020 Jan; 21(1):144-157. PubMed ID: 31793212
[TBL] [Abstract][Full Text] [Related]
4. SADSNet: A robust 3D synchronous segmentation network for liver and liver tumors based on spatial attention mechanism and deep supervision.
Yang S; Liang Y; Wu S; Sun P; Chen Z
J Xray Sci Technol; 2024; 32(3):707-723. PubMed ID: 38552134
[TBL] [Abstract][Full Text] [Related]
5. Automatic liver segmentation by integrating fully convolutional networks into active contour models.
Guo X; Schwartz LH; Zhao B
Med Phys; 2019 Oct; 46(10):4455-4469. PubMed ID: 31356688
[TBL] [Abstract][Full Text] [Related]
6. Automatic 3D liver segmentation based on deep learning and globally optimized surface evolution.
Hu P; Wu F; Peng J; Liang P; Kong D
Phys Med Biol; 2016 Dec; 61(24):8676-8698. PubMed ID: 27880735
[TBL] [Abstract][Full Text] [Related]
7. Automatic abdominal multi-organ segmentation using deep convolutional neural network and time-implicit level sets.
Hu P; Wu F; Peng J; Bao Y; Chen F; Kong D
Int J Comput Assist Radiol Surg; 2017 Mar; 12(3):399-411. PubMed ID: 27885540
[TBL] [Abstract][Full Text] [Related]
8. 3D Liver Tumor Segmentation in CT Images Using Improved Fuzzy
Wu W; Wu S; Zhou Z; Zhang R; Zhang Y
Biomed Res Int; 2017; 2017():5207685. PubMed ID: 29090220
[TBL] [Abstract][Full Text] [Related]
9. Shape-intensity prior level set combining probabilistic atlas and probability map constrains for automatic liver segmentation from abdominal CT images.
Wang J; Cheng Y; Guo C; Wang Y; Tamura S
Int J Comput Assist Radiol Surg; 2016 May; 11(5):817-26. PubMed ID: 26646416
[TBL] [Abstract][Full Text] [Related]
10. Blood vessel-based liver segmentation using the portal phase of an abdominal CT dataset.
Maklad AS; Matsuhiro M; Suzuki H; Kawata Y; Niki N; Satake M; Moriyama N; Utsunomiya T; Shimada M
Med Phys; 2013 Nov; 40(11):113501. PubMed ID: 24320472
[TBL] [Abstract][Full Text] [Related]
11. Automatic 3D liver location and segmentation via convolutional neural network and graph cut.
Lu F; Wu F; Hu P; Peng Z; Kong D
Int J Comput Assist Radiol Surg; 2017 Feb; 12(2):171-182. PubMed ID: 27604760
[TBL] [Abstract][Full Text] [Related]
12. 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]
13. Abdominal multi-organ auto-segmentation using 3D-patch-based deep convolutional neural network.
Kim H; Jung J; Kim J; Cho B; Kwak J; Jang JY; Lee SW; Lee JG; Yoon SM
Sci Rep; 2020 Apr; 10(1):6204. PubMed ID: 32277135
[TBL] [Abstract][Full Text] [Related]
14. Automatic 3D CT liver segmentation based on fast global minimization of probabilistic active contour.
Jin R; Wang M; Xu L; Lu J; Song E; Ma G
Med Phys; 2023 Apr; 50(4):2100-2120. PubMed ID: 36413182
[TBL] [Abstract][Full Text] [Related]
15. A Liver Segmentation Method Based on the Fusion of VNet and WGAN.
Ma J; Deng Y; Ma Z; Mao K; Chen Y
Comput Math Methods Med; 2021; 2021():5536903. PubMed ID: 34659447
[TBL] [Abstract][Full Text] [Related]
16. Spatial feature fusion convolutional network for liver and liver tumor segmentation from CT images.
Liu T; Liu J; Ma Y; He J; Han J; Ding X; Chen CT
Med Phys; 2021 Jan; 48(1):264-272. PubMed ID: 33159809
[TBL] [Abstract][Full Text] [Related]
17. Cascaded deep convolutional encoder-decoder neural networks for efficient liver tumor segmentation.
Budak Ü; Guo Y; Tanyildizi E; Şengür A
Med Hypotheses; 2020 Jan; 134():109431. PubMed ID: 31669758
[TBL] [Abstract][Full Text] [Related]
18. Multi-scale contextual semantic enhancement network for 3D medical image segmentation.
Xia T; Huang G; Pun CM; Zhang W; Li J; Ling WK; Lin C; Yang Q
Phys Med Biol; 2022 Nov; 67(22):. PubMed ID: 36317277
[No Abstract] [Full Text] [Related]
19. Toward reliable automatic liver and tumor segmentation using convolutional neural network based on 2.5D models.
Wardhana G; Naghibi H; Sirmacek B; Abayazid M
Int J Comput Assist Radiol Surg; 2021 Jan; 16(1):41-51. PubMed ID: 33219906
[TBL] [Abstract][Full Text] [Related]
20. Automatic liver tumor segmentation in CT with fully convolutional neural networks and object-based postprocessing.
Chlebus G; Schenk A; Moltz JH; van Ginneken B; Hahn HK; Meine H
Sci Rep; 2018 Oct; 8(1):15497. PubMed ID: 30341319
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
