140 related articles for article (PubMed ID: 32066744)
1. An objective comparison of detection and segmentation algorithms for artefacts in clinical endoscopy.
Ali S; Zhou F; Braden B; Bailey A; Yang S; Cheng G; Zhang P; Li X; Kayser M; Soberanis-Mukul RD; Albarqouni S; Wang X; Wang C; Watanabe S; Oksuz I; Ning Q; Yang S; Khan MA; Gao XW; Realdon S; Loshchenov M; Schnabel JA; East JE; Wagnieres G; Loschenov VB; Grisan E; Daul C; Blondel W; Rittscher J
Sci Rep; 2020 Feb; 10(1):2748. PubMed ID: 32066744
[TBL] [Abstract][Full Text] [Related]
2. Deep learning for detection and segmentation of artefact and disease instances in gastrointestinal endoscopy.
Ali S; Dmitrieva M; Ghatwary N; Bano S; Polat G; Temizel A; Krenzer A; Hekalo A; Guo YB; Matuszewski B; Gridach M; Voiculescu I; Yoganand V; Chavan A; Raj A; Nguyen NT; Tran DQ; Huynh LD; Boutry N; Rezvy S; Chen H; Choi YH; Subramanian A; Balasubramanian V; Gao XW; Hu H; Liao Y; Stoyanov D; Daul C; Realdon S; Cannizzaro R; Lamarque D; Tran-Nguyen T; Bailey A; Braden B; East JE; Rittscher J
Med Image Anal; 2021 May; 70():102002. PubMed ID: 33657508
[TBL] [Abstract][Full Text] [Related]
3. Endoscopy Artefact Detection by Deep Transfer Learning of Baseline Models.
Yin TK; Huang KL; Chiu SR; Yang YQ; Chang BR
J Digit Imaging; 2022 Oct; 35(5):1101-1110. PubMed ID: 35478060
[TBL] [Abstract][Full Text] [Related]
4. A deep learning framework for quality assessment and restoration in video endoscopy.
Ali S; Zhou F; Bailey A; Braden B; East JE; Lu X; Rittscher J
Med Image Anal; 2021 Feb; 68():101900. PubMed ID: 33246229
[TBL] [Abstract][Full Text] [Related]
5. A deep learning dataset for sample preparation artefacts detection in multispectral high-content microscopy.
Sharma V; Yakimovich A
Sci Data; 2024 Feb; 11(1):232. PubMed ID: 38395957
[TBL] [Abstract][Full Text] [Related]
6. Automatic CNN-based detection of cardiac MR motion artefacts using k-space data augmentation and curriculum learning.
Oksuz I; Ruijsink B; Puyol-Antón E; Clough JR; Cruz G; Bustin A; Prieto C; Botnar R; Rueckert D; Schnabel JA; King AP
Med Image Anal; 2019 Jul; 55():136-147. PubMed ID: 31055126
[TBL] [Abstract][Full Text] [Related]
7. Superpixel-based deep convolutional neural networks and active contour model for automatic prostate segmentation on 3D MRI scans.
da Silva GLF; Diniz PS; Ferreira JL; França JVF; Silva AC; de Paiva AC; de Cavalcanti EAA
Med Biol Eng Comput; 2020 Sep; 58(9):1947-1964. PubMed ID: 32566988
[TBL] [Abstract][Full Text] [Related]
8. Evaluation of prostate segmentation algorithms for MRI: the PROMISE12 challenge.
Litjens G; Toth R; van de Ven W; Hoeks C; Kerkstra S; van Ginneken B; Vincent G; Guillard G; Birbeck N; Zhang J; Strand R; Malmberg F; Ou Y; Davatzikos C; Kirschner M; Jung F; Yuan J; Qiu W; Gao Q; Edwards PE; Maan B; van der Heijden F; Ghose S; Mitra J; Dowling J; Barratt D; Huisman H; Madabhushi A
Med Image Anal; 2014 Feb; 18(2):359-73. PubMed ID: 24418598
[TBL] [Abstract][Full Text] [Related]
9. Brain MRI artefact detection and correction using convolutional neural networks.
Oksuz I
Comput Methods Programs Biomed; 2021 Feb; 199():105909. PubMed ID: 33373815
[TBL] [Abstract][Full Text] [Related]
10. CHAOS Challenge - combined (CT-MR) healthy abdominal organ segmentation.
Kavur AE; Gezer NS; Barış M; Aslan S; Conze PH; Groza V; Pham DD; Chatterjee S; Ernst P; Özkan S; Baydar B; Lachinov D; Han S; Pauli J; Isensee F; Perkonigg M; Sathish R; Rajan R; Sheet D; Dovletov G; Speck O; Nürnberger A; Maier-Hein KH; Bozdağı Akar G; Ünal G; Dicle O; Selver MA
Med Image Anal; 2021 Apr; 69():101950. PubMed ID: 33421920
[TBL] [Abstract][Full Text] [Related]
11. Fully automatic segmentation of glottis and vocal folds in endoscopic laryngeal high-speed videos using a deep Convolutional LSTM Network.
Fehling MK; Grosch F; Schuster ME; Schick B; Lohscheller J
PLoS One; 2020; 15(2):e0227791. PubMed ID: 32040514
[TBL] [Abstract][Full Text] [Related]
12. A multi-task and multi-channel convolutional neural network for semi-supervised neonatal artefact detection.
Hermans T; Smets L; Lemmens K; Dereymaeker A; Jansen K; Naulaers G; Zappasodi F; Van Huffel S; Comani S; De Vos M
J Neural Eng; 2023 Mar; 20(2):. PubMed ID: 36791462
[No Abstract] [Full Text] [Related]
13. Multi-object segmentation framework using deformable models for medical imaging analysis.
Namías R; D'Amato JP; Del Fresno M; Vénere M; Pirró N; Bellemare ME
Med Biol Eng Comput; 2016 Aug; 54(8):1181-92. PubMed ID: 26392182
[TBL] [Abstract][Full Text] [Related]
14. Differential privacy preserved federated transfer learning for multi-institutional
Shiri I; Salimi Y; Maghsudi M; Jenabi E; Harsini S; Razeghi B; Mostafaei S; Hajianfar G; Sanaat A; Jafari E; Samimi R; Khateri M; Sheikhzadeh P; Geramifar P; Dadgar H; Bitrafan Rajabi A; Assadi M; Bénard F; Vafaei Sadr A; Voloshynovskiy S; Mainta I; Uribe C; Rahmim A; Zaidi H
Eur J Nucl Med Mol Imaging; 2023 Dec; 51(1):40-53. PubMed ID: 37682303
[TBL] [Abstract][Full Text] [Related]
15. Mitigation of motion-induced artifacts in cone beam computed tomography using deep convolutional neural networks.
Amirian M; Montoya-Zegarra JA; Herzig I; Eggenberger Hotz P; Lichtensteiger L; Morf M; Züst A; Paysan P; Peterlik I; Scheib S; Füchslin RM; Stadelmann T; Schilling FP
Med Phys; 2023 Oct; 50(10):6228-6242. PubMed ID: 36995003
[TBL] [Abstract][Full Text] [Related]
16. Deep learning-based metal artefact reduction in PET/CT imaging.
Arabi H; Zaidi H
Eur Radiol; 2021 Aug; 31(8):6384-6396. PubMed ID: 33569626
[TBL] [Abstract][Full Text] [Related]
17. Digital hair segmentation using hybrid convolutional and recurrent neural networks architecture.
Attia M; Hossny M; Zhou H; Nahavandi S; Asadi H; Yazdabadi A
Comput Methods Programs Biomed; 2019 Aug; 177():17-30. PubMed ID: 31319945
[TBL] [Abstract][Full Text] [Related]
18. Reference layer artefact subtraction (RLAS): a novel method of minimizing EEG artefacts during simultaneous fMRI.
Chowdhury ME; Mullinger KJ; Glover P; Bowtell R
Neuroimage; 2014 Jan; 84():307-19. PubMed ID: 23994127
[TBL] [Abstract][Full Text] [Related]
19. A k-Space Model of Movement Artefacts: Application to Segmentation Augmentation and Artefact Removal.
Shaw R; Sudre CH; Varsavsky T; Ourselin S; Cardoso MJ
IEEE Trans Med Imaging; 2020 Sep; 39(9):2881-2892. PubMed ID: 32149627
[TBL] [Abstract][Full Text] [Related]
20. EndoSLAM dataset and an unsupervised monocular visual odometry and depth estimation approach for endoscopic videos.
Ozyoruk KB; Gokceler GI; Bobrow TL; Coskun G; Incetan K; Almalioglu Y; Mahmood F; Curto E; Perdigoto L; Oliveira M; Sahin H; Araujo H; Alexandrino H; Durr NJ; Gilbert HB; Turan M
Med Image Anal; 2021 Jul; 71():102058. PubMed ID: 33930829
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
