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Items: 1 to 50 of 265

1.

Machine learning in cardiovascular magnetic resonance: basic concepts and applications.

Leiner T, Rueckert D, Suinesiaputra A, Baeßler B, Nezafat R, Išgum I, Young AA.

J Cardiovasc Magn Reson. 2019 Oct 7;21(1):61. doi: 10.1186/s12968-019-0575-y. Review.

2.

Brain Connectivity Measures Improve Modeling of Functional Outcome After Acute Ischemic Stroke.

Ktena SI, Schirmer MD, Etherton MR, Giese AK, Tuozzo C, Mills BB, Rueckert D, Wu O, Rost NS.

Stroke. 2019 Oct;50(10):2761-2767. doi: 10.1161/STROKEAHA.119.025738. Epub 2019 Sep 12.

PMID:
31510905
3.

Self-supervised learning for medical image analysis using image context restoration.

Chen L, Bentley P, Mori K, Misawa K, Fujiwara M, Rueckert D.

Med Image Anal. 2019 Jul 26;58:101539. doi: 10.1016/j.media.2019.101539. [Epub ahead of print]

PMID:
31374449
4.

Sex and regional differences in myocardial plasticity in aortic stenosis are revealed by 3D model machine learning.

Bhuva AN, Treibel TA, De Marvao A, Biffi C, Dawes TJW, Doumou G, Bai W, Patel K, Boubertakh R, Rueckert D, O'Regan DP, Hughes AD, Moon JC, Manisty CH.

Eur Heart J Cardiovasc Imaging. 2019 Jul 5. pii: jez166. doi: 10.1093/ehjci/jez166. [Epub ahead of print]

PMID:
31280289
5.

Computational anatomy for multi-organ analysis in medical imaging: A review.

Cerrolaza JJ, Picazo ML, Humbert L, Sato Y, Rueckert D, Ballester MÁG, Linguraru MG.

Med Image Anal. 2019 Aug;56:44-67. doi: 10.1016/j.media.2019.04.002. Epub 2019 May 15.

PMID:
31181343
6.

Cardiac Rhythm Device Identification Using Neural Networks.

Howard JP, Fisher L, Shun-Shin MJ, Keene D, Arnold AD, Ahmad Y, Cook CM, Moon JC, Manisty CH, Whinnett ZI, Cole GD, Rueckert D, Francis DP.

JACC Clin Electrophysiol. 2019 May;5(5):576-586. doi: 10.1016/j.jacep.2019.02.003. Epub 2019 Mar 27.

7.

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. doi: 10.1016/j.media.2019.04.009. Epub 2019 Apr 22.

8.

Weakly Supervised Estimation of Shadow Confidence Maps in Fetal Ultrasound Imaging.

Meng Q, Sinclair M, Zimmer V, Hou B, Rajchl M, Toussaint N, Oktay O, Schlemper J, Gomez A, Housden J, Matthew J, Rueckert D, Schnabel JA, Kainz B.

IEEE Trans Med Imaging. 2019 Apr 25. doi: 10.1109/TMI.2019.2913311. [Epub ahead of print]

9.

Impact of a clinical decision support tool on prediction of progression in early-stage dementia: a prospective validation study.

Bruun M, Frederiksen KS, Rhodius-Meester HFM, Baroni M, Gjerum L, Koikkalainen J, Urhemaa T, Tolonen A, van Gils M, Rueckert D, Dyremose N, Andersen BB, Lemstra AW, Hallikainen M, Kurl S, Herukka SK, Remes AM, Waldemar G, Soininen H, Mecocci P, van der Flier WM, Lötjönen J, Hasselbalch SG.

Alzheimers Res Ther. 2019 Mar 20;11(1):25. doi: 10.1186/s13195-019-0482-3.

10.

Automated quality control in image segmentation: application to the UK Biobank cardiovascular magnetic resonance imaging study.

Robinson R, Valindria VV, Bai W, Oktay O, Kainz B, Suzuki H, Sanghvi MM, Aung N, Paiva JM, Zemrak F, Fung K, Lukaschuk E, Lee AM, Carapella V, Kim YJ, Piechnik SK, Neubauer S, Petersen SE, Page C, Matthews PM, Rueckert D, Glocker B.

J Cardiovasc Magn Reson. 2019 Mar 14;21(1):18. doi: 10.1186/s12968-019-0523-x.

11.

Machine learning in whole-body MRI: experiences and challenges from an applied study using multicentre data.

Lavdas I, Glocker B, Rueckert D, Taylor SA, Aboagye EO, Rockall AG.

Clin Radiol. 2019 May;74(5):346-356. doi: 10.1016/j.crad.2019.01.012. Epub 2019 Feb 23. Review.

PMID:
30803815
12.

Attention gated networks: Learning to leverage salient regions in medical images.

Schlemper J, Oktay O, Schaap M, Heinrich M, Kainz B, Glocker B, Rueckert D.

Med Image Anal. 2019 Apr;53:197-207. doi: 10.1016/j.media.2019.01.012. Epub 2019 Feb 5.

13.

Deep learning cardiac motion analysis for human survival prediction.

Bello GA, Dawes TJW, Duan J, Biffi C, de Marvao A, Howard LSGE, Gibbs JSR, Wilkins MR, Cook SA, Rueckert D, O'Regan DP.

Nat Mach Intell. 2019 Feb 11;1:95-104. doi: 10.1038/s42256-019-0019-2.

14.

Evaluating reinforcement learning agents for anatomical landmark detection.

Alansary A, Oktay O, Li Y, Folgoc LL, Hou B, Vaillant G, Kamnitsas K, Vlontzos A, Glocker B, Kainz B, Rueckert D.

Med Image Anal. 2019 Apr;53:156-164. doi: 10.1016/j.media.2019.02.007. Epub 2019 Feb 14.

PMID:
30784956
15.

Ventricular remodeling in preterm infants: computational cardiac magnetic resonance atlasing shows significant early remodeling of the left ventricle.

Cox DJ, Bai W, Price AN, Edwards AD, Rueckert D, Groves AM.

Pediatr Res. 2019 May;85(6):807-815. doi: 10.1038/s41390-018-0171-0. Epub 2018 Nov 19.

PMID:
30758323
16.

Independent Left Ventricular Morphometric Atlases Show Consistent Relationships with Cardiovascular Risk Factors: A UK Biobank Study.

Gilbert K, Bai W, Mauger C, Medrano-Gracia P, Suinesiaputra A, Lee AM, Sanghvi MM, Aung N, Piechnik SK, Neubauer S, Petersen SE, Rueckert D, Young AA.

Sci Rep. 2019 Feb 4;9(1):1130. doi: 10.1038/s41598-018-37916-6.

17.

Automatic 3D Bi-Ventricular Segmentation of Cardiac Images by a Shape-Refined Multi- Task Deep Learning Approach.

Duan J, Bello G, Schlemper J, Bai W, Dawes TJW, Biffi C, de Marvao A, Doumoud G, O'Regan DP, Rueckert D.

IEEE Trans Med Imaging. 2019 Sep;38(9):2151-2164. doi: 10.1109/TMI.2019.2894322. Epub 2019 Jan 23.

18.

Fibrosis Microstructure Modulates Reentry in Non-ischemic Dilated Cardiomyopathy: Insights From Imaged Guided 2D Computational Modeling.

Balaban G, Halliday BP, Mendonca Costa C, Bai W, Porter B, Rinaldi CA, Plank G, Rueckert D, Prasad SK, Bishop MJ.

Front Physiol. 2018 Dec 19;9:1832. doi: 10.3389/fphys.2018.01832. eCollection 2018.

19.

Impact of a Clinical Decision Support Tool on Dementia Diagnostics in Memory Clinics: The PredictND Validation Study.

Bruun M, Frederiksen KS, Rhodius-Meester HFM, Baroni M, Gjerum L, Koikkalainen J, Urhemaa T, Tolonen A, van Gils M, Tong T, Guerrero R, Rueckert D, Dyremose N, Andersen BB, Simonsen AH, Lemstra A, Hallikainen M, Kurl S, Herukka SK, Remes AM, Waldemar G, Soininen H, Mecocci P, van der Flier WM, Lötjönen J, Hasselbalch SG.

Curr Alzheimer Res. 2019;16(2):91-101. doi: 10.2174/1567205016666190103152425.

PMID:
30605060
20.

Metabolic pathways associated with right ventricular adaptation to pulmonary hypertension: 3D analysis of cardiac magnetic resonance imaging.

Attard MI, Dawes TJW, de Marvao A, Biffi C, Shi W, Wharton J, Rhodes CJ, Ghataorhe P, Gibbs JSR, Howard LSGE, Rueckert D, Wilkins MR, O'Regan DP.

Eur Heart J Cardiovasc Imaging. 2019 Jun 1;20(6):668-676. doi: 10.1093/ehjci/jey175.

21.

Fetal Skull Reconstruction via Deep Convolutional Autoencoders.

Cerrolaza JJ, Li Y, Biffi C, Gomez A, Matthew J, Sinclair M, Gupta C, Knight CL, Rueckert D.

Conf Proc IEEE Eng Med Biol Soc. 2018 Jul;2018:887-890. doi: 10.1109/EMBC.2018.8512282.

PMID:
30440533
22.

Human-level Performance On Automatic Head Biometrics In Fetal Ultrasound Using Fully Convolutional Neural Networks.

Sinclair M, Baumgartner CF, Matthew J, Bai W, Martinez JC, Li Y, Smith S, Knight CL, Kainz B, Hajnal J, King AP, Rueckert D.

Conf Proc IEEE Eng Med Biol Soc. 2018 Jul;2018:714-717. doi: 10.1109/EMBC.2018.8512278.

PMID:
30440496
23.

Identifying the optimal regional predictor of right ventricular global function: a high-resolution three-dimensional cardiac magnetic resonance study.

Dawes TJW, de Marvao A, Shi W, Rueckert D, Cook SA, O'Regan DP.

Anaesthesia. 2019 Mar;74(3):312-320. doi: 10.1111/anae.14494. Epub 2018 Nov 14.

24.

Learning-Based Quality Control for Cardiac MR Images.

Tarroni G, Oktay O, Bai W, Schuh A, Suzuki H, Passerat-Palmbach J, de Marvao A, O'Regan DP, Cook S, Glocker B, Matthews PM, Rueckert D.

IEEE Trans Med Imaging. 2019 May;38(5):1127-1138. doi: 10.1109/TMI.2018.2878509. Epub 2018 Nov 1.

25.

Evaluating combinations of diagnostic tests to discriminate different dementia types.

Bruun M, Rhodius-Meester HFM, Koikkalainen J, Baroni M, Gjerum L, Lemstra AW, Barkhof F, Remes AM, Urhemaa T, Tolonen A, Rueckert D, van Gils M, Frederiksen KS, Waldemar G, Scheltens P, Mecocci P, Soininen H, Lötjönen J, Hasselbalch SG, van der Flier WM.

Alzheimers Dement (Amst). 2018 Aug 17;10:509-518. doi: 10.1016/j.dadm.2018.07.003. eCollection 2018.

26.

Automated cardiovascular magnetic resonance image analysis with fully convolutional networks.

Bai W, Sinclair M, Tarroni G, Oktay O, Rajchl M, Vaillant G, Lee AM, Aung N, Lukaschuk E, Sanghvi MM, Zemrak F, Fung K, Paiva JM, Carapella V, Kim YJ, Suzuki H, Kainz B, Matthews PM, Petersen SE, Piechnik SK, Neubauer S, Glocker B, Rueckert D.

J Cardiovasc Magn Reson. 2018 Sep 14;20(1):65. doi: 10.1186/s12968-018-0471-x.

27.

Convolutional Recurrent Neural Networks for Dynamic MR Image Reconstruction.

Qin C, Schlemper J, Caballero J, Price AN, Hajnal JV, Rueckert D.

IEEE Trans Med Imaging. 2019 Jan;38(1):280-290. doi: 10.1109/TMI.2018.2863670. Epub 2018 Aug 6.

28.

Structural brain imaging in Alzheimer's disease and mild cognitive impairment: biomarker analysis and shared morphometry database.

Ledig C, Schuh A, Guerrero R, Heckemann RA, Rueckert D.

Sci Rep. 2018 Jul 26;8(1):11258. doi: 10.1038/s41598-018-29295-9.

29.

3-D Reconstruction in Canonical Co-Ordinate Space From Arbitrarily Oriented 2-D Images.

Hou B, Khanal B, Alansary A, McDonagh S, Davidson A, Rutherford M, Hajnal JV, Rueckert D, Glocker B, Kainz B.

IEEE Trans Med Imaging. 2018 Aug;37(8):1737-1750. doi: 10.1109/TMI.2018.2798801. Epub 2018 Feb 19.

30.

DRINet for Medical Image Segmentation.

Chen L, Bentley P, Mori K, Misawa K, Fujiwara M, Rueckert D.

IEEE Trans Med Imaging. 2018 Nov;37(11):2453-2462. doi: 10.1109/TMI.2018.2835303. Epub 2018 May 10.

31.

Data-Driven Differential Diagnosis of Dementia Using Multiclass Disease State Index Classifier.

Tolonen A, Rhodius-Meester HFM, Bruun M, Koikkalainen J, Barkhof F, Lemstra AW, Koene T, Scheltens P, Teunissen CE, Tong T, Guerrero R, Schuh A, Ledig C, Baroni M, Rueckert D, Soininen H, Remes AM, Waldemar G, Hasselbalch SG, Mecocci P, van der Flier WM, Lötjönen J.

Front Aging Neurosci. 2018 Apr 25;10:111. doi: 10.3389/fnagi.2018.00111. eCollection 2018.

32.

Disease prediction using graph convolutional networks: Application to Autism Spectrum Disorder and Alzheimer's disease.

Parisot S, Ktena SI, Ferrante E, Lee M, Guerrero R, Glocker B, Rueckert D.

Med Image Anal. 2018 Aug;48:117-130. doi: 10.1016/j.media.2018.06.001. Epub 2018 Jun 2.

33.

Construction of a neonatal cortical surface atlas using Multimodal Surface Matching in the Developing Human Connectome Project.

Bozek J, Makropoulos A, Schuh A, Fitzgibbon S, Wright R, Glasser MF, Coalson TS, O'Muircheartaigh J, Hutter J, Price AN, Cordero-Grande L, Teixeira RPAG, Hughes E, Tusor N, Baruteau KP, Rutherford MA, Edwards AD, Hajnal JV, Smith SM, Rueckert D, Jenkinson M, Robinson EC.

Neuroimage. 2018 Oct 1;179:11-29. doi: 10.1016/j.neuroimage.2018.06.018. Epub 2018 Jun 14.

34.

Brain lesion segmentation through image synthesis and outlier detection.

Bowles C, Qin C, Guerrero R, Gunn R, Hammers A, Dickie DA, Valdés Hernández M, Wardlaw J, Rueckert D.

Neuroimage Clin. 2017 Sep 8;16:643-658. doi: 10.1016/j.nicl.2017.09.003. eCollection 2017.

35.

Automated processing pipeline for neonatal diffusion MRI in the developing Human Connectome Project.

Bastiani M, Andersson JLR, Cordero-Grande L, Murgasova M, Hutter J, Price AN, Makropoulos A, Fitzgibbon SP, Hughes E, Rueckert D, Victor S, Rutherford M, Edwards AD, Smith SM, Tournier JD, Hajnal JV, Jbabdi S, Sotiropoulos SN.

Neuroimage. 2019 Jan 15;185:750-763. doi: 10.1016/j.neuroimage.2018.05.064. Epub 2018 May 28. Review.

36.

Rapid Automated Quantification of Cerebral Leukoaraiosis on CT Images: A Multicenter Validation Study.

Chen L, Carlton Jones AL, Mair G, Patel R, Gontsarova A, Ganesalingam J, Math N, Dawson A, Aweid B, Cohen D, Mehta A, Wardlaw J, Rueckert D, Bentley P; IST-3 Collaborative Group.

Radiology. 2018 Aug;288(2):573-581. doi: 10.1148/radiol.2018171567. Epub 2018 May 15.

37.

Automatic MRI Quantifying Methods in Behavioral-Variant Frontotemporal Dementia Diagnosis.

Cajanus A, Hall A, Koikkalainen J, Solje E, Tolonen A, Urhemaa T, Liu Y, Haanpää RM, Hartikainen P, Helisalmi S, Korhonen V, Rueckert D, Hasselbalch S, Waldemar G, Mecocci P, Vanninen R, van Gils M, Soininen H, Lötjönen J, Remes AM.

Dement Geriatr Cogn Dis Extra. 2018 Feb 23;8(1):51-59. doi: 10.1159/000486849. eCollection 2018 Jan-Apr.

38.

White matter hyperintensity and stroke lesion segmentation and differentiation using convolutional neural networks.

Guerrero R, Qin C, Oktay O, Bowles C, Chen L, Joules R, Wolz R, Valdés-Hernández MC, Dickie DA, Wardlaw J, Rueckert D.

Neuroimage Clin. 2017 Dec 20;17:918-934. doi: 10.1016/j.nicl.2017.12.022. eCollection 2018.

39.

Dynamic patterns of cortical expansion during folding of the preterm human brain.

Garcia KE, Robinson EC, Alexopoulos D, Dierker DL, Glasser MF, Coalson TS, Ortinau CM, Rueckert D, Taber LA, Van Essen DC, Rogers CE, Smyser CD, Bayly PV.

Proc Natl Acad Sci U S A. 2018 Mar 20;115(12):3156-3161. doi: 10.1073/pnas.1715451115. Epub 2018 Mar 5.

40.

The developing human connectome project: A minimal processing pipeline for neonatal cortical surface reconstruction.

Makropoulos A, Robinson EC, Schuh A, Wright R, Fitzgibbon S, Bozek J, Counsell SJ, Steinweg J, Vecchiato K, Passerat-Palmbach J, Lenz G, Mortari F, Tenev T, Duff EP, Bastiani M, Cordero-Grande L, Hughes E, Tusor N, Tournier JD, Hutter J, Price AN, Teixeira RPAG, Murgasova M, Victor S, Kelly C, Rutherford MA, Smith SM, Edwards AD, Hajnal JV, Jenkinson M, Rueckert D.

Neuroimage. 2018 Jun;173:88-112. doi: 10.1016/j.neuroimage.2018.01.054. Epub 2018 Jan 31.

41.

Metric learning with spectral graph convolutions on brain connectivity networks.

Ktena SI, Parisot S, Ferrante E, Rajchl M, Lee M, Glocker B, Rueckert D.

Neuroimage. 2018 Apr 1;169:431-442. doi: 10.1016/j.neuroimage.2017.12.052. Epub 2017 Dec 24.

42.

A spatio-temporal reference model of the aging brain.

Huizinga W, Poot DHJ, Vernooij MW, Roshchupkin GV, Bron EE, Ikram MA, Rueckert D, Niessen WJ, Klein S; Alzheimer's Disease Neuroimaging Initiative.

Neuroimage. 2018 Apr 1;169:11-22. doi: 10.1016/j.neuroimage.2017.10.040. Epub 2017 Dec 5.

PMID:
29203452
43.

Regional brain morphometry in patients with traumatic brain injury based on acute- and chronic-phase magnetic resonance imaging.

Ledig C, Kamnitsas K, Koikkalainen J, Posti JP, Takala RSK, Katila A, Frantzén J, Ala-Seppälä H, Kyllönen A, Maanpää HR, Tallus J, Lötjönen J, Glocker B, Tenovuo O, Rueckert D.

PLoS One. 2017 Nov 28;12(11):e0188152. doi: 10.1371/journal.pone.0188152. eCollection 2017.

44.

Impaired development of the cerebral cortex in infants with congenital heart disease is correlated to reduced cerebral oxygen delivery.

Kelly CJ, Makropoulos A, Cordero-Grande L, Hutter J, Price A, Hughes E, Murgasova M, Teixeira RPAG, Steinweg JK, Kulkarni S, Rahman L, Zhang H, Alexander DC, Pushparajah K, Rueckert D, Hajnal JV, Simpson J, Edwards AD, Rutherford MA, Counsell SJ.

Sci Rep. 2017 Nov 8;7(1):15088. doi: 10.1038/s41598-017-14939-z.

45.

Myocardial strain computed at multiple spatial scales from tagged magnetic resonance imaging: Estimating cardiac biomarkers for CRT patients.

Sinclair M, Peressutti D, Puyol-Antón E, Bai W, Rivolo S, Webb J, Claridge S, Jackson T, Nordsletten D, Hadjicharalambous M, Kerfoot E, Rinaldi CA, Rueckert D, King AP.

Med Image Anal. 2018 Jan;43:169-185. doi: 10.1016/j.media.2017.10.004. Epub 2017 Oct 31.

46.

Multimodal surface matching with higher-order smoothness constraints.

Robinson EC, Garcia K, Glasser MF, Chen Z, Coalson TS, Makropoulos A, Bozek J, Wright R, Schuh A, Webster M, Hutter J, Price A, Cordero Grande L, Hughes E, Tusor N, Bayly PV, Van Essen DC, Smith SM, Edwards AD, Hajnal J, Jenkinson M, Glocker B, Rueckert D.

Neuroimage. 2018 Feb 15;167:453-465. doi: 10.1016/j.neuroimage.2017.10.037. Epub 2017 Oct 31.

47.

A Deep Cascade of Convolutional Neural Networks for Dynamic MR Image Reconstruction.

Schlemper J, Caballero J, Hajnal JV, Price AN, Rueckert D.

IEEE Trans Med Imaging. 2018 Feb;37(2):491-503. doi: 10.1109/TMI.2017.2760978. Epub 2017 Oct 13.

48.

Three-dimensional cardiovascular imaging-genetics: a mass univariate framework.

Biffi C, de Marvao A, Attard MI, Dawes TJW, Whiffin N, Bai W, Shi W, Francis C, Meyer H, Buchan R, Cook SA, Rueckert D, O'Regan DP.

Bioinformatics. 2018 Jan 1;34(1):97-103. doi: 10.1093/bioinformatics/btx552.

49.

Anatomically Constrained Neural Networks (ACNNs): Application to Cardiac Image Enhancement and Segmentation.

Oktay O, Ferrante E, Kamnitsas K, Heinrich M, Bai W, Caballero J, Cook SA, de Marvao A, Dawes T, O'Regan DP, Kainz B, Glocker B, Rueckert D.

IEEE Trans Med Imaging. 2018 Feb;37(2):384-395. doi: 10.1109/TMI.2017.2743464. Epub 2017 Sep 26.

50.

A flexible graphical model for multi-modal parcellation of the cortex.

Parisot S, Glocker B, Ktena SI, Arslan S, Schirmer MD, Rueckert D.

Neuroimage. 2017 Nov 15;162:226-248. doi: 10.1016/j.neuroimage.2017.09.005. Epub 2017 Sep 6.

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