120 related articles for article (PubMed ID: 35354108)
21. Fully Automatic Brain Tumor Segmentation using End-To-End Incremental Deep Neural Networks in MRI images.
Naceur MB; Saouli R; Akil M; Kachouri R
Comput Methods Programs Biomed; 2018 Nov; 166():39-49. PubMed ID: 30415717
[TBL] [Abstract][Full Text] [Related]
22. 3D multi-scale FCN with random modality voxel dropout learning for Intervertebral Disc Localization and Segmentation from Multi-modality MR Images.
Li X; Dou Q; Chen H; Fu CW; Qi X; Belavý DL; Armbrecht G; Felsenberg D; Zheng G; Heng PA
Med Image Anal; 2018 Apr; 45():41-54. PubMed ID: 29414435
[TBL] [Abstract][Full Text] [Related]
23. VoxResNet: Deep voxelwise residual networks for brain segmentation from 3D MR images.
Chen H; Dou Q; Yu L; Qin J; Heng PA
Neuroimage; 2018 Apr; 170():446-455. PubMed ID: 28445774
[TBL] [Abstract][Full Text] [Related]
24. Learning-based 3T brain MRI segmentation with guidance from 7T MRI labeling.
Deng M; Yu R; Wang L; Shi F; Yap PT; Shen D;
Med Phys; 2016 Dec; 43(12):6588-6597. PubMed ID: 28054724
[TBL] [Abstract][Full Text] [Related]
25. CTumorGAN: a unified framework for automatic computed tomography tumor segmentation.
Pang S; Du A; Orgun MA; Yu Z; Wang Y; Wang Y; Liu G
Eur J Nucl Med Mol Imaging; 2020 Sep; 47(10):2248-2268. PubMed ID: 32222809
[TBL] [Abstract][Full Text] [Related]
26. Multi-Scale deep learning framework for cochlea localization, segmentation and analysis on clinical ultra-high-resolution CT images.
Heutink F; Koch V; Verbist B; van der Woude WJ; Mylanus E; Huinck W; Sechopoulos I; Caballo M
Comput Methods Programs Biomed; 2020 Jul; 191():105387. PubMed ID: 32109685
[TBL] [Abstract][Full Text] [Related]
27. 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]
28. MetricUNet: Synergistic image- and voxel-level learning for precise prostate segmentation via online sampling.
He K; Lian C; Adeli E; Huo J; Gao Y; Zhang B; Zhang J; Shen D
Med Image Anal; 2021 Jul; 71():102039. PubMed ID: 33831595
[TBL] [Abstract][Full Text] [Related]
29. Deep causal learning for pancreatic cancer segmentation in CT sequences.
Li C; Mao Y; Liang S; Li J; Wang Y; Guo Y
Neural Netw; 2024 Jul; 175():106294. PubMed ID: 38657562
[TBL] [Abstract][Full Text] [Related]
30. Male pelvic CT multi-organ segmentation using synthetic MRI-aided dual pyramid networks.
Lei Y; Wang T; Tian S; Fu Y; Patel P; Jani AB; Curran WJ; Liu T; Yang X
Phys Med Biol; 2021 Apr; 66(8):. PubMed ID: 33780918
[TBL] [Abstract][Full Text] [Related]
31. LINKS: learning-based multi-source IntegratioN frameworK for Segmentation of infant brain images.
Wang L; Gao Y; Shi F; Li G; Gilmore JH; Lin W; Shen D
Neuroimage; 2015 Mar; 108():160-72. PubMed ID: 25541188
[TBL] [Abstract][Full Text] [Related]
32. A dual-transformation with contrastive learning framework for lymph node metastasis prediction in pancreatic cancer.
Chen X; Wang W; Jiang Y; Qian X
Med Image Anal; 2023 Apr; 85():102753. PubMed ID: 36682152
[TBL] [Abstract][Full Text] [Related]
33. Boundary-Weighted Domain Adaptive Neural Network for Prostate MR Image Segmentation.
Zhu Q; Du B; Yan P
IEEE Trans Med Imaging; 2020 Mar; 39(3):753-763. PubMed ID: 31425022
[TBL] [Abstract][Full Text] [Related]
34. Image generation by GAN and style transfer for agar plate image segmentation.
Andreini P; Bonechi S; Bianchini M; Mecocci A; Scarselli F
Comput Methods Programs Biomed; 2020 Feb; 184():105268. PubMed ID: 31891902
[TBL] [Abstract][Full Text] [Related]
35. Automated psoriasis lesion segmentation from unconstrained environment using residual U-Net with transfer learning.
Raj R; Londhe ND; Sonawane R
Comput Methods Programs Biomed; 2021 Jul; 206():106123. PubMed ID: 33975181
[TBL] [Abstract][Full Text] [Related]
36. Segmentation of organs-at-risks in head and neck CT images using convolutional neural networks.
Ibragimov B; Xing L
Med Phys; 2017 Feb; 44(2):547-557. PubMed ID: 28205307
[TBL] [Abstract][Full Text] [Related]
37. Automatic segmentation of organs at risk and tumors in CT images of lung cancer from partially labelled datasets with a semi-supervised conditional nnU-Net.
Zhang G; Yang Z; Huo B; Chai S; Jiang S
Comput Methods Programs Biomed; 2021 Nov; 211():106419. PubMed ID: 34563895
[TBL] [Abstract][Full Text] [Related]
38. Deep learning for fully automated tumor segmentation and extraction of magnetic resonance radiomics features in cervical cancer.
Lin YC; Lin CH; Lu HY; Chiang HJ; Wang HK; Huang YT; Ng SH; Hong JH; Yen TC; Lai CH; Lin G
Eur Radiol; 2020 Mar; 30(3):1297-1305. PubMed ID: 31712961
[TBL] [Abstract][Full Text] [Related]
39. Meta grayscale adaptive network for 3D integrated renal structures segmentation.
He Y; Yang G; Yang J; Ge R; Kong Y; Zhu X; Zhang S; Shao P; Shu H; Dillenseger JL; Coatrieux JL; Li S
Med Image Anal; 2021 Jul; 71():102055. PubMed ID: 33866259
[TBL] [Abstract][Full Text] [Related]
40. Non-equivalent images and pixels: Confidence-aware resampling with meta-learning mixup for polyp segmentation.
Guo X; Chen Z; Liu J; Yuan Y
Med Image Anal; 2022 May; 78():102394. PubMed ID: 35219939
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]