186 related articles for article (PubMed ID: 30040632)
1. Multiple Resolution Residually Connected Feature Streams for Automatic Lung Tumor Segmentation From CT Images.
Jiang J; Hu YC; Liu CJ; Halpenny D; Hellmann MD; Deasy JO; Mageras G; Veeraraghavan H
IEEE Trans Med Imaging; 2019 Jan; 38(1):134-144. PubMed ID: 30040632
[TBL] [Abstract][Full Text] [Related]
2. Automatic lung tumor segmentation from CT images using improved 3D densely connected UNet.
Zhang G; Yang Z; Jiang S
Med Biol Eng Comput; 2022 Nov; 60(11):3311-3323. PubMed ID: 36169904
[TBL] [Abstract][Full Text] [Related]
3. Nested block self-attention multiple resolution residual network for multiorgan segmentation from CT.
Jiang J; Elguindi S; Berry SL; Onochie I; Cervino L; Deasy JO; Veeraraghavan H
Med Phys; 2022 Aug; 49(8):5244-5257. PubMed ID: 35598077
[TBL] [Abstract][Full Text] [Related]
4. Deep learning-based dominant index lesion segmentation for MR-guided radiation therapy of prostate cancer.
Simeth J; Jiang J; Nosov A; Wibmer A; Zelefsky M; Tyagi N; Veeraraghavan H
Med Phys; 2023 Aug; 50(8):4854-4870. PubMed ID: 36856092
[TBL] [Abstract][Full Text] [Related]
5. Two-stage deep learning model for fully automated pancreas segmentation on computed tomography: Comparison with intra-reader and inter-reader reliability at full and reduced radiation dose on an external dataset.
Panda A; Korfiatis P; Suman G; Garg SK; Polley EC; Singh DP; Chari ST; Goenka AH
Med Phys; 2021 May; 48(5):2468-2481. PubMed ID: 33595105
[TBL] [Abstract][Full Text] [Related]
6. A Segmentation Framework of Pulmonary Nodules in Lung CT Images.
Mukhopadhyay S
J Digit Imaging; 2016 Feb; 29(1):86-103. PubMed ID: 26055544
[TBL] [Abstract][Full Text] [Related]
7. Deep Deconvolutional Residual Network Based Automatic Lung Nodule Segmentation.
Singadkar G; Mahajan A; Thakur M; Talbar S
J Digit Imaging; 2020 Jun; 33(3):678-684. PubMed ID: 32026218
[TBL] [Abstract][Full Text] [Related]
8. Three-stage segmentation of lung region from CT images using deep neural networks.
Osadebey M; Andersen HK; Waaler D; Fossaa K; Martinsen ACT; Pedersen M
BMC Med Imaging; 2021 Jul; 21(1):112. PubMed ID: 34266391
[TBL] [Abstract][Full Text] [Related]
9. 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]
10. Automatic segmentation of lung tumors on CT images based on a 2D & 3D hybrid convolutional neural network.
Gan W; Wang H; Gu H; Duan Y; Shao Y; Chen H; Feng A; Huang Y; Fu X; Ying Y; Quan H; Xu Z
Br J Radiol; 2021 Oct; 94(1126):20210038. PubMed ID: 34347535
[TBL] [Abstract][Full Text] [Related]
11. Lung Segmentation on HRCT and Volumetric CT for Diffuse Interstitial Lung Disease Using Deep Convolutional Neural Networks.
Park B; Park H; Lee SM; Seo JB; Kim N
J Digit Imaging; 2019 Dec; 32(6):1019-1026. PubMed ID: 31396776
[TBL] [Abstract][Full Text] [Related]
12. Automatic detection of lung nodules in CT datasets based on stable 3D mass-spring models.
Cascio D; Magro R; Fauci F; Iacomi M; Raso G
Comput Biol Med; 2012 Nov; 42(11):1098-109. PubMed ID: 23020972
[TBL] [Abstract][Full Text] [Related]
13. Multi-scale segmentation squeeze-and-excitation UNet with conditional random field for segmenting lung tumor from CT images.
Zhang B; Qi S; Wu Y; Pan X; Yao Y; Qian W; Guan Y
Comput Methods Programs Biomed; 2022 Jul; 222():106946. PubMed ID: 35716533
[TBL] [Abstract][Full Text] [Related]
14. DICOM re-encoding of volumetrically annotated Lung Imaging Database Consortium (LIDC) nodules.
Fedorov A; Hancock M; Clunie D; Brochhausen M; Bona J; Kirby J; Freymann J; Pieper S; J W L Aerts H; Kikinis R; Prior F
Med Phys; 2020 Nov; 47(11):5953-5965. PubMed ID: 32772385
[TBL] [Abstract][Full Text] [Related]
15. Segmentation and tracking of lung nodules via graph-cuts incorporating shape prior and motion from 4D CT.
Cha J; Farhangi MM; Dunlap N; Amini AA
Med Phys; 2018 Jan; 45(1):297-306. PubMed ID: 29164630
[TBL] [Abstract][Full Text] [Related]
16. An effective deep network for automatic segmentation of complex lung tumors in CT images.
Wang B; Chen K; Tian X; Yang Y; Zhang X
Med Phys; 2021 Sep; 48(9):5004-5016. PubMed ID: 34224147
[TBL] [Abstract][Full Text] [Related]
17. Automatic recognition of 3D GGO CT imaging signs through the fusion of hybrid resampling and layer-wise fine-tuning CNNs.
Han G; Liu X; Zheng G; Wang M; Huang S
Med Biol Eng Comput; 2018 Dec; 56(12):2201-2212. PubMed ID: 29873026
[TBL] [Abstract][Full Text] [Related]
18. Segmentation of pulmonary nodules in computed tomography using a regression neural network approach and its application to the Lung Image Database Consortium and Image Database Resource Initiative dataset.
Messay T; Hardie RC; Tuinstra TR
Med Image Anal; 2015 May; 22(1):48-62. PubMed ID: 25791434
[TBL] [Abstract][Full Text] [Related]
19. A novel computer-aided lung nodule detection system for CT images.
Tan M; Deklerck R; Jansen B; Bister M; Cornelis J
Med Phys; 2011 Oct; 38(10):5630-45. PubMed ID: 21992380
[TBL] [Abstract][Full Text] [Related]
20. Postoperative glioma segmentation in CT image using deep feature fusion model guided by multi-sequence MRIs.
Tang F; Liang S; Zhong T; Huang X; Deng X; Zhang Y; Zhou L
Eur Radiol; 2020 Feb; 30(2):823-832. PubMed ID: 31650265
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
