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Items: 1 to 50 of 235

1.

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.

2.

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 Jun 2;48:117-130. doi: 10.1016/j.media.2018.06.001. [Epub ahead of print]

PMID:
29890408
3.

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 Jun 13;179:11-29. doi: 10.1016/j.neuroimage.2018.06.018. [Epub ahead of print]

PMID:
29890325
4.

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.

5.

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. 2018 May 28. pii: S1053-8119(18)30488-9. doi: 10.1016/j.neuroimage.2018.05.064. [Epub ahead of print] Review.

6.

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 May 15:171567. doi: 10.1148/radiol.2018171567. [Epub ahead of print]

PMID:
29762091
7.

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.

8.

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.

9.

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.

PMID:
29507201
10.

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.

PMID:
29409960
11.

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.

PMID:
29278772
12.

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
13.

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.

14.

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.

15.

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.

16.

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.

PMID:
29100940
17.

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.

18.

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.

19.

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.

PMID:
28961105
20.

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.

PMID:
28889005
21.

PVR: Patch-to-Volume Reconstruction for Large Area Motion Correction of Fetal MRI.

Alansary A, Rajchl M, McDonagh SG, Murgasova M, Damodaram M, Lloyd DFA, Davidson A, Rutherford M, Hajnal JV, Rueckert D, Kainz B.

IEEE Trans Med Imaging. 2017 Oct;36(10):2031-2044. doi: 10.1109/TMI.2017.2737081. Epub 2017 Sep 1.

PMID:
28880160
22.

Multi-Atlas Segmentation Using Partially Annotated Data: Methods and Annotation Strategies.

Koch LM, Rajchl M, Bai W, Baumgartner CF, Tong T, Passerat-Palmbach J, Aljabar P, Rueckert D, Koch LM, Rajchl M, Wenjia Bai, Baumgartner CF, Tong Tong, Passerat-Palmbach J, Aljabar P, Rueckert D, Bai W, Passerat-Palmbach J, Rajchl M, Tong T, Baumgartner CF, Koch LM, Rueckert D, Aljabar P.

IEEE Trans Pattern Anal Mach Intell. 2018 Jul;40(7):1683-1696. doi: 10.1109/TPAMI.2017.2711020. Epub 2017 Aug 22.

23.

Learning and combining image neighborhoods using random forests for neonatal brain disease classification.

Zimmer VA, Glocker B, Hahner N, Eixarch E, Sanroma G, Gratacós E, Rueckert D, González Ballester MÁ, Piella G.

Med Image Anal. 2017 Dec;42:189-199. doi: 10.1016/j.media.2017.08.004. Epub 2017 Aug 9.

PMID:
28818743
24.

Fully automatic, multiorgan segmentation in normal whole body magnetic resonance imaging (MRI), using classification forests (CFs), convolutional neural networks (CNNs), and a multi-atlas (MA) approach.

Lavdas I, Glocker B, Kamnitsas K, Rueckert D, Mair H, Sandhu A, Taylor SA, Aboagye EO, Rockall AG.

Med Phys. 2017 Oct;44(10):5210-5220. doi: 10.1002/mp.12492. Epub 2017 Aug 31.

PMID:
28756622
25.

SonoNet: Real-Time Detection and Localisation of Fetal Standard Scan Planes in Freehand Ultrasound.

Baumgartner CF, Kamnitsas K, Matthew J, Fletcher TP, Smith S, Koch LM, Kainz B, Rueckert D.

IEEE Trans Med Imaging. 2017 Nov;36(11):2204-2215. doi: 10.1109/TMI.2017.2712367. Epub 2017 Jul 11.

26.

Automated Detection of Motion Artefacts in MR Imaging Using Decision Forests.

Lorch B, Vaillant G, Baumgartner C, Bai W, Rueckert D, Maier A.

J Med Eng. 2017;2017:4501647. doi: 10.1155/2017/4501647. Epub 2017 Jun 11.

27.

A review on automatic fetal and neonatal brain MRI segmentation.

Makropoulos A, Counsell SJ, Rueckert D.

Neuroimage. 2018 Apr 15;170:231-248. doi: 10.1016/j.neuroimage.2017.06.074. Epub 2017 Jun 28. Review.

PMID:
28666878
28.

Fully automatic acute ischemic lesion segmentation in DWI using convolutional neural networks.

Chen L, Bentley P, Rueckert D.

Neuroimage Clin. 2017 Jun 13;15:633-643. doi: 10.1016/j.nicl.2017.06.016. eCollection 2017.

29.

Five-class differential diagnostics of neurodegenerative diseases using random undersampling boosting.

Tong T, Ledig C, Guerrero R, Schuh A, Koikkalainen J, Tolonen A, Rhodius H, Barkhof F, Tijms B, Lemstra AW, Soininen H, Remes AM, Waldemar G, Hasselbalch S, Mecocci P, Baroni M, Lötjönen J, Flier WV, Rueckert D.

Neuroimage Clin. 2017 Jun 12;15:613-624. doi: 10.1016/j.nicl.2017.06.012. eCollection 2017.

30.

Reverse Classification Accuracy: Predicting Segmentation Performance in the Absence of Ground Truth.

Valindria VV, Lavdas I, Bai W, Kamnitsas K, Aboagye EO, Rockall AG, Rueckert D, Glocker B.

IEEE Trans Med Imaging. 2017 Aug;36(8):1597-1606. doi: 10.1109/TMI.2017.2665165. Epub 2017 Apr 17.

31.

Human brain mapping: A systematic comparison of parcellation methods for the human cerebral cortex.

Arslan S, Ktena SI, Makropoulos A, Robinson EC, Rueckert D, Parisot S.

Neuroimage. 2018 Apr 15;170:5-30. doi: 10.1016/j.neuroimage.2017.04.014. Epub 2017 Apr 13. Review.

PMID:
28412442
32.

Multi-atlas pancreas segmentation: Atlas selection based on vessel structure.

Karasawa K, Oda M, Kitasaka T, Misawa K, Fujiwara M, Chu C, Zheng G, Rueckert D, Mori K.

Med Image Anal. 2017 Jul;39:18-28. doi: 10.1016/j.media.2017.03.006. Epub 2017 Mar 31.

33.

Reproducible Large-Scale Neuroimaging Studies with the OpenMOLE Workflow Management System.

Passerat-Palmbach J, Reuillon R, Leclaire M, Makropoulos A, Robinson EC, Parisot S, Rueckert D.

Front Neuroinform. 2017 Mar 22;11:21. doi: 10.3389/fninf.2017.00021. eCollection 2017.

34.

Multi-channel MRI segmentation of eye structures and tumors using patient-specific features.

Ciller C, De Zanet S, Kamnitsas K, Maeder P, Glocker B, Munier FL, Rueckert D, Thiran JP, Bach Cuadra M, Sznitman R.

PLoS One. 2017 Mar 28;12(3):e0173900. doi: 10.1371/journal.pone.0173900. eCollection 2017.

35.

Distortion Correction in Fetal EPI Using Non-Rigid Registration With a Laplacian Constraint.

Kuklisova-Murgasova M, Lockwood Estrin G, Nunes RG, Malik SJ, Rutherford MA, Rueckert D, Hajnal JV.

IEEE Trans Med Imaging. 2018 Jan;37(1):12-19. doi: 10.1109/TMI.2017.2667227. Epub 2017 Feb 9.

PMID:
28207387
36.

Statistical shape modeling of the left ventricle: myocardial infarct classification challenge.

Suinesiaputra A, Ablin P, Alba X, Alessandrini M, Allen J, Bai W, Cimen S, Claes P, Cowan BR, D'hooge J, Duchateau N, Ehrhardt J, Frangi AF, Gooya A, Grau V, Lekadir K, Lu A, Mukhopadhyay A, Oksuz I, Parajali N, Pennec X, Pereanez M, Pinto C, Piras P, Rohe MM, Rueckert D, Saring D, Sermesant M, Siddiqi K, Tabassian M, Teresi L, Tsaftaris SA, Wilms M, Young AA, Zhang X, Medrano-Gracia P.

IEEE J Biomed Health Inform. 2017 Jan 17. doi: 10.1109/JBHI.2017.2652449. [Epub ahead of print]

PMID:
28103561
37.

Machine Learning of Three-dimensional Right Ventricular Motion Enables Outcome Prediction in Pulmonary Hypertension: A Cardiac MR Imaging Study.

Dawes TJW, de Marvao A, Shi W, Fletcher T, Watson GMJ, Wharton J, Rhodes CJ, Howard LSGE, Gibbs JSR, Rueckert D, Cook SA, Wilkins MR, O'Regan DP.

Radiology. 2017 May;283(2):381-390. doi: 10.1148/radiol.2016161315. Epub 2017 Jan 16.

38.

Stratified Decision Forests for Accurate Anatomical Landmark Localization in Cardiac Images.

Oktay O, Bai W, Guerrero R, Rajchl M, de Marvao A, O'Regan DP, Cook SA, Heinrich MP, Glocker B, Rueckert D.

IEEE Trans Med Imaging. 2017 Jan;36(1):332-342. doi: 10.1109/TMI.2016.2597270.

39.

Regional Differences in End-Diastolic Volumes between 3D Echo and CMR in HLHS Patients.

Gomez A, Oktay O, Rueckert D, Penney GP, Schnabel JA, Simpson JM, Pushparajah K.

Front Pediatr. 2016 Dec 12;4:133. doi: 10.3389/fped.2016.00133. eCollection 2016.

40.

Titin-truncating variants affect heart function in disease cohorts and the general population.

Schafer S, de Marvao A, Adami E, Fiedler LR, Ng B, Khin E, Rackham OJ, van Heesch S, Pua CJ, Kui M, Walsh R, Tayal U, Prasad SK, Dawes TJ, Ko NS, Sim D, Chan LL, Chin CW, Mazzarotto F, Barton PJ, Kreuchwig F, de Kleijn DP, Totman T, Biffi C, Tee N, Rueckert D, Schneider V, Faber A, Regitz-Zagrosek V, Seidman JG, Seidman CE, Linke WA, Kovalik JP, O'Regan D, Ware JS, Hubner N, Cook SA.

Nat Genet. 2017 Jan;49(1):46-53. doi: 10.1038/ng.3719. Epub 2016 Nov 21.

41.

Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation.

Kamnitsas K, Ledig C, Newcombe VFJ, Simpson JP, Kane AD, Menon DK, Rueckert D, Glocker B.

Med Image Anal. 2017 Feb;36:61-78. doi: 10.1016/j.media.2016.10.004. Epub 2016 Oct 29.

42.

DeepCut: Object Segmentation From Bounding Box Annotations Using Convolutional Neural Networks.

Rajchl M, Lee MC, Oktay O, Kamnitsas K, Passerat-Palmbach J, Bai W, Damodaram M, Rutherford MA, Hajnal JV, Kainz B, Rueckert D.

IEEE Trans Med Imaging. 2017 Feb;36(2):674-683. doi: 10.1109/TMI.2016.2621185. Epub 2016 Nov 9.

43.

A framework for combining a motion atlas with non-motion information to learn clinically useful biomarkers: Application to cardiac resynchronisation therapy response prediction.

Peressutti D, Sinclair M, Bai W, Jackson T, Ruijsink J, Nordsletten D, Asner L, Hadjicharalambous M, Rinaldi CA, Rueckert D, King AP.

Med Image Anal. 2017 Jan;35:669-684. doi: 10.1016/j.media.2016.10.002. Epub 2016 Oct 11.

44.

ISLES 2015 - A public evaluation benchmark for ischemic stroke lesion segmentation from multispectral MRI.

Maier O, Menze BH, von der Gablentz J, Ḧani L, Heinrich MP, Liebrand M, Winzeck S, Basit A, Bentley P, Chen L, Christiaens D, Dutil F, Egger K, Feng C, Glocker B, Götz M, Haeck T, Halme HL, Havaei M, Iftekharuddin KM, Jodoin PM, Kamnitsas K, Kellner E, Korvenoja A, Larochelle H, Ledig C, Lee JH, Maes F, Mahmood Q, Maier-Hein KH, McKinley R, Muschelli J, Pal C, Pei L, Rangarajan JR, Reza SMS, Robben D, Rueckert D, Salli E, Suetens P, Wang CW, Wilms M, Kirschke JS, Kr Amer UM, Münte TF, Schramm P, Wiest R, Handels H, Reyes M.

Med Image Anal. 2017 Jan;35:250-269. doi: 10.1016/j.media.2016.07.009. Epub 2016 Jul 21.

45.

Instantiated mixed effects modeling of Alzheimer's disease markers.

Guerrero R, Schmidt-Richberg A, Ledig C, Tong T, Wolz R, Rueckert D; Alzheimer's Disease Neuroimaging Initiative (ADNI).

Neuroimage. 2016 Nov 15;142:113-125. doi: 10.1016/j.neuroimage.2016.06.049. Epub 2016 Jul 2.

46.

Learning clinically useful information from images: Past, present and future.

Rueckert D, Glocker B, Kainz B.

Med Image Anal. 2016 Oct;33:13-18. doi: 10.1016/j.media.2016.06.009. Epub 2016 Jun 15.

47.

Autoadaptive motion modelling for MR-based respiratory motion estimation.

Baumgartner CF, Kolbitsch C, McClelland JR, Rueckert D, King AP.

Med Image Anal. 2017 Jan;35:83-100. doi: 10.1016/j.media.2016.06.005. Epub 2016 Jun 9.

48.

Evaluation of Six Registration Methods for the Human Abdomen on Clinically Acquired CT.

Xu Z, Lee CP, Heinrich MP, Modat M, Rueckert D, Ourselin S, Abramson RG, Landman BA.

IEEE Trans Biomed Eng. 2016 Aug;63(8):1563-72. doi: 10.1109/TBME.2016.2574816. Epub 2016 Jun 1.

49.

Relationship between body composition and left ventricular geometry using three dimensional cardiovascular magnetic resonance.

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

J Cardiovasc Magn Reson. 2016 May 31;18(1):32. doi: 10.1186/s12968-016-0251-4.

50.

Group-wise parcellation of the cortex through multi-scale spectral clustering.

Parisot S, Arslan S, Passerat-Palmbach J, Wells WM 3rd, Rueckert D.

Neuroimage. 2016 Aug 1;136:68-83. doi: 10.1016/j.neuroimage.2016.05.035. Epub 2016 May 15.

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