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Items: 1 to 20 of 81

1.

ISLES 2016 and 2017-Benchmarking Ischemic Stroke Lesion Outcome Prediction Based on Multispectral MRI.

Winzeck S, Hakim A, McKinley R, Pinto JAADSR, Alves V, Silva C, Pisov M, Krivov E, Belyaev M, Monteiro M, Oliveira A, Choi Y, Paik MC, Kwon Y, Lee H, Kim BJ, Won JH, Islam M, Ren H, Robben D, Suetens P, Gong E, Niu Y, Xu J, Pauly JM, Lucas C, Heinrich MP, Rivera LC, Castillo LS, Daza LA, Beers AL, Arbelaezs P, Maier O, Chang K, Brown JM, Kalpathy-Cramer J, Zaharchuk G, Wiest R, Reyes M.

Front Neurol. 2018 Sep 13;9:679. doi: 10.3389/fneur.2018.00679. eCollection 2018.

2.

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.

3.

Ischemic stroke lesion segmentation using stacked sparse autoencoder.

Praveen GB, Agrawal A, Sundaram P, Sardesai S.

Comput Biol Med. 2018 Aug 1;99:38-52. doi: 10.1016/j.compbiomed.2018.05.027. Epub 2018 Jun 2.

PMID:
29883752
4.

MABAL: a Novel Deep-Learning Architecture for Machine-Assisted Bone Age Labeling.

Mutasa S, Chang PD, Ruzal-Shapiro C, Ayyala R.

J Digit Imaging. 2018 Aug;31(4):513-519. doi: 10.1007/s10278-018-0053-3.

PMID:
29404850
5.

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.

6.

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.

7.

Learning to Predict Ischemic Stroke Growth on Acute CT Perfusion Data by Interpolating Low-Dimensional Shape Representations.

Lucas C, Kemmling A, Bouteldja N, Aulmann LF, Madany Mamlouk A, Heinrich MP.

Front Neurol. 2018 Nov 26;9:989. doi: 10.3389/fneur.2018.00989. eCollection 2018.

8.

PMLB: a large benchmark suite for machine learning evaluation and comparison.

Olson RS, La Cava W, Orzechowski P, Urbanowicz RJ, Moore JH.

BioData Min. 2017 Dec 11;10:36. doi: 10.1186/s13040-017-0154-4. eCollection 2017.

9.

Benchmarking deep learning models on large healthcare datasets.

Purushotham S, Meng C, Che Z, Liu Y.

J Biomed Inform. 2018 Jul;83:112-134. doi: 10.1016/j.jbi.2018.04.007. Epub 2018 Jun 5.

10.

Deep 3D Convolutional Encoder Networks With Shortcuts for Multiscale Feature Integration Applied to Multiple Sclerosis Lesion Segmentation.

Brosch T, Tang LY, Youngjin Yoo, Li DK, Traboulsee A, Tam R.

IEEE Trans Med Imaging. 2016 May;35(5):1229-1239. doi: 10.1109/TMI.2016.2528821. Epub 2016 Feb 11.

PMID:
26886978
11.

Skin lesion segmentation in dermoscopy images via deep full resolution convolutional networks.

Al-Masni MA, Al-Antari MA, Choi MT, Han SM, Kim TS.

Comput Methods Programs Biomed. 2018 Aug;162:221-231. doi: 10.1016/j.cmpb.2018.05.027. Epub 2018 May 19.

PMID:
29903489
12.

Machine learning for outcome prediction of acute ischemic stroke post intra-arterial therapy.

Asadi H, Dowling R, Yan B, Mitchell P.

PLoS One. 2014 Feb 10;9(2):e88225. doi: 10.1371/journal.pone.0088225. eCollection 2014.

13.

Deep Learning for Brain MRI Segmentation: State of the Art and Future Directions.

Akkus Z, Galimzianova A, Hoogi A, Rubin DL, Erickson BJ.

J Digit Imaging. 2017 Aug;30(4):449-459. doi: 10.1007/s10278-017-9983-4. Review.

14.

Deep convolutional neural networks for pan-specific peptide-MHC class I binding prediction.

Han Y, Kim D.

BMC Bioinformatics. 2017 Dec 28;18(1):585. doi: 10.1186/s12859-017-1997-x.

15.

Improving automated multiple sclerosis lesion segmentation with a cascaded 3D convolutional neural network approach.

Valverde S, Cabezas M, Roura E, González-Villà S, Pareto D, Vilanova JC, Ramió-Torrentà L, Rovira À, Oliver A, Lladó X.

Neuroimage. 2017 Jul 15;155:159-168. doi: 10.1016/j.neuroimage.2017.04.034. Epub 2017 Apr 19.

PMID:
28435096
16.

The RSNA Pediatric Bone Age Machine Learning Challenge.

Halabi SS, Prevedello LM, Kalpathy-Cramer J, Mamonov AB, Bilbily A, Cicero M, Pan I, Pereira LA, Sousa RT, Abdala N, Kitamura FC, Thodberg HH, Chen L, Shih G, Andriole K, Kohli MD, Erickson BJ, Flanders AE.

Radiology. 2019 Feb;290(2):498-503. doi: 10.1148/radiol.2018180736. Epub 2018 Nov 27.

PMID:
30480490
17.

3D fully convolutional networks for subcortical segmentation in MRI: A large-scale study.

Dolz J, Desrosiers C, Ben Ayed I.

Neuroimage. 2018 Apr 15;170:456-470. doi: 10.1016/j.neuroimage.2017.04.039. Epub 2017 Apr 24. Review.

PMID:
28450139
18.

Exploiting the potential of unlabeled endoscopic video data with self-supervised learning.

Ross T, Zimmerer D, Vemuri A, Isensee F, Wiesenfarth M, Bodenstedt S, Both F, Kessler P, Wagner M, Müller B, Kenngott H, Speidel S, Kopp-Schneider A, Maier-Hein K, Maier-Hein L.

Int J Comput Assist Radiol Surg. 2018 Jun;13(6):925-933. doi: 10.1007/s11548-018-1772-0. Epub 2018 Apr 27.

PMID:
29704196
19.

Brain tumor segmentation using holistically nested neural networks in MRI images.

Zhuge Y, Krauze AV, Ning H, Cheng JY, Arora BC, Camphausen K, Miller RW.

Med Phys. 2017 Oct;44(10):5234-5243. doi: 10.1002/mp.12481. Epub 2017 Aug 20.

20.

Skin lesion classification with ensembles of deep convolutional neural networks.

Harangi B.

J Biomed Inform. 2018 Oct;86:25-32. doi: 10.1016/j.jbi.2018.08.006. Epub 2018 Aug 10.

PMID:
30103029

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