363 related articles for article (PubMed ID: 37003043)
1. Dual center validation of deep learning for automated multi-label segmentation of thoracic anatomy in bedside chest radiographs.
Busch F; Xu L; Sushko D; Weidlich M; Truhn D; Müller-Franzes G; Heimer MM; Niehues SM; Makowski MR; Hinsche M; Vahldiek JL; Aerts HJ; Adams LC; Bressem KK
Comput Methods Programs Biomed; 2023 Jun; 234():107505. PubMed ID: 37003043
[TBL] [Abstract][Full Text] [Related]
2. Hybrid U-Net-based deep learning model for volume segmentation of lung nodules in CT images.
Wang Y; Zhou C; Chan HP; Hadjiiski LM; Chughtai A; Kazerooni EA
Med Phys; 2022 Nov; 49(11):7287-7302. PubMed ID: 35717560
[TBL] [Abstract][Full Text] [Related]
3. Abdomen CT multi-organ segmentation using token-based MLP-Mixer.
Pan S; Chang CW; Wang T; Wynne J; Hu M; Lei Y; Liu T; Patel P; Roper J; Yang X
Med Phys; 2023 May; 50(5):3027-3038. PubMed ID: 36463516
[TBL] [Abstract][Full Text] [Related]
4. 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]
5. Fully Automated Lung Lobe Segmentation in Volumetric Chest CT with 3D U-Net: Validation with Intra- and Extra-Datasets.
Park J; Yun J; Kim N; Park B; Cho Y; Park HJ; Song M; Lee M; Seo JB
J Digit Imaging; 2020 Feb; 33(1):221-230. PubMed ID: 31152273
[TBL] [Abstract][Full Text] [Related]
6. CheXLocNet: Automatic localization of pneumothorax in chest radiographs using deep convolutional neural networks.
Wang H; Gu H; Qin P; Wang J
PLoS One; 2020; 15(11):e0242013. PubMed ID: 33166371
[TBL] [Abstract][Full Text] [Related]
7. U-net architecture with embedded Inception-ResNet-v2 image encoding modules for automatic segmentation of organs-at-risk in head and neck cancer radiation therapy based on computed tomography scans.
Siciarz P; McCurdy B
Phys Med Biol; 2022 Jun; 67(11):. PubMed ID: 35134792
[No Abstract] [Full Text] [Related]
8. MDU-Net: A Convolutional Network for Clavicle and Rib Segmentation from a Chest Radiograph.
Wang W; Feng H; Bu Q; Cui L; Xie Y; Zhang A; Feng J; Zhu Z; Chen Z
J Healthc Eng; 2020; 2020():2785464. PubMed ID: 32724504
[TBL] [Abstract][Full Text] [Related]
9. Layered deep learning for automatic mandibular segmentation in cone-beam computed tomography.
Verhelst PJ; Smolders A; Beznik T; Meewis J; Vandemeulebroucke A; Shaheen E; Van Gerven A; Willems H; Politis C; Jacobs R
J Dent; 2021 Nov; 114():103786. PubMed ID: 34425172
[TBL] [Abstract][Full Text] [Related]
10. Mutual enhancing learning-based automatic segmentation of CT cardiac substructure.
Momin S; Lei Y; McCall NS; Zhang J; Roper J; Harms J; Tian S; Lloyd MS; Liu T; Bradley JD; Higgins K; Yang X
Phys Med Biol; 2022 May; 67(10):. PubMed ID: 35447610
[No Abstract] [Full Text] [Related]
11. Separation of bones from soft tissue in chest radiographs: Anatomy-specific orientation-frequency-specific deep neural network convolution.
Zarshenas A; Liu J; Forti P; Suzuki K
Med Phys; 2019 May; 46(5):2232-2242. PubMed ID: 30848498
[TBL] [Abstract][Full Text] [Related]
12. Machine Segmentation of Pelvic Anatomy in MRI-Assisted Radiosurgery (MARS) for Prostate Cancer Brachytherapy.
Sanders JW; Lewis GD; Thames HD; Kudchadker RJ; Venkatesan AM; Bruno TL; Ma J; Pagel MD; Frank SJ
Int J Radiat Oncol Biol Phys; 2020 Dec; 108(5):1292-1303. PubMed ID: 32634543
[TBL] [Abstract][Full Text] [Related]
13. Automated segmentation of head CT scans for computer-assisted craniomaxillofacial surgery applying a hierarchical patch-based stack of convolutional neural networks.
Steybe D; Poxleitner P; Metzger MC; Brandenburg LS; Schmelzeisen R; Bamberg F; Tran PH; Kellner E; Reisert M; Russe MF
Int J Comput Assist Radiol Surg; 2022 Nov; 17(11):2093-2101. PubMed ID: 35665881
[TBL] [Abstract][Full Text] [Related]
14. AnatomyNet: Deep learning for fast and fully automated whole-volume segmentation of head and neck anatomy.
Zhu W; Huang Y; Zeng L; Chen X; Liu Y; Qian Z; Du N; Fan W; Xie X
Med Phys; 2019 Feb; 46(2):576-589. PubMed ID: 30480818
[TBL] [Abstract][Full Text] [Related]
15. Evaluation of the feasibility of explainable computer-aided detection of cardiomegaly on chest radiographs using deep learning.
Lee MS; Kim YS; Kim M; Usman M; Byon SS; Kim SH; Lee BI; Lee BD
Sci Rep; 2021 Aug; 11(1):16885. PubMed ID: 34413405
[TBL] [Abstract][Full Text] [Related]
16. RPLS-Net: pulmonary lobe segmentation based on 3D fully convolutional networks and multi-task learning.
Liu J; Wang C; Guo J; Shao J; Xu X; Liu X; Li H; Li W; Yi Z
Int J Comput Assist Radiol Surg; 2021 Jun; 16(6):895-904. PubMed ID: 33846890
[TBL] [Abstract][Full Text] [Related]
17. Deeply supervised 3D fully convolutional networks with group dilated convolution for automatic MRI prostate segmentation.
Wang B; Lei Y; Tian S; Wang T; Liu Y; Patel P; Jani AB; Mao H; Curran WJ; Liu T; Yang X
Med Phys; 2019 Apr; 46(4):1707-1718. PubMed ID: 30702759
[TBL] [Abstract][Full Text] [Related]
18. A deep learning based dual encoder-decoder framework for anatomical structure segmentation in chest X-ray images.
Ullah I; Ali F; Shah B; El-Sappagh S; Abuhmed T; Park SH
Sci Rep; 2023 Jan; 13(1):791. PubMed ID: 36646735
[TBL] [Abstract][Full Text] [Related]
19. A novel adaptive cubic quasi-Newton optimizer for deep learning based medical image analysis tasks, validated on detection of COVID-19 and segmentation for COVID-19 lung infection, liver tumor, and optic disc/cup.
Liu Y; Zhang M; Zhong Z; Zeng X
Med Phys; 2023 Mar; 50(3):1528-1538. PubMed ID: 36057788
[TBL] [Abstract][Full Text] [Related]
20. Comparison of the automatic segmentation of multiple organs at risk in CT images of lung cancer between deep convolutional neural network-based and atlas-based techniques.
Zhu J; Zhang J; Qiu B; Liu Y; Liu X; Chen L
Acta Oncol; 2019 Feb; 58(2):257-264. PubMed ID: 30398090
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]