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Carlton Chu
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2020 – today
- 2020
- [j12]Geoffrey C. Y. Tan, Carlton Chu, Yu Teng Lee, Clarence Chih King Tan, John Ashburner, Nicholas W. Wood
, Richard S. J. Frackowiak
The influence of microsatellite polymorphisms in sex steroid receptor genes ESR1, ESR2 and AR on sex differences in brain structure. NeuroImage 221: 117087 (2020)
2010 – 2019
- 2018
- [i3]Stanislav Nikolov, Sam Blackwell, Ruheena Mendes, Jeffrey De Fauw, Clemens Meyer, Cían Hughes, Harry Askham, Bernardino Romera-Paredes, Alan Karthikesalingam, Carlton Chu, Dawn Carnell, Cheng Boon, Derek D'Souza, Syed Ali Moinuddin, Kevin Sullivan, DeepMind Radiographer Consortium, Hugh Montgomery, Geraint Rees, Ricky Sharma, Mustafa Suleyman, Trevor Back, Joseph R. Ledsam, Olaf Ronneberger:
Deep learning to achieve clinically applicable segmentation of head and neck anatomy for radiotherapy. CoRR abs/1809.04430 (2018) - 2017
- [j11]Pierre Bellec, Carlton Chu, François Chouinard-Decorte, Yassine Benhajali, Daniel S. Margulies
The Neuro Bureau ADHD-200 Preprocessed repository. NeuroImage 144: 275-286 (2017) - 2016
- [j10]Hui Zhang, Shruti Japee, Rachel Nolan, Carlton Chu, Ning Liu, Leslie G. Ungerleider:
Face-selective regions differ in their ability to classify facial expressions. NeuroImage 130: 77-90 (2016) - [i2]Jeffrey De Fauw, Pearse A. Keane
Automated analysis of retinal imaging using machine learning techniques for computer vision. F1000Research 5: 1573 (2016) - [i1]Carlton Chu, Jeffrey De Fauw, Nenad Tomasev
Applying machine learning to automated segmentation of head and neck tumour volumes and organs at risk on radiotherapy planning CT and MRI scans. F1000Research 5: 2104 (2016) - 2013
- [j9]Javier Gonzalez-Castillo
Effects of image contrast on functional MRI image registration. NeuroImage 67: 163-174 (2013) - [j8]Jessica Schrouff
PRoNTo: Pattern Recognition for Neuroimaging Toolbox. Neuroinformatics 11(3): 319-337 (2013) - 2012
- [j7]Carlton Chu, Ai-Ling Hsu
Does feature selection improve classification accuracy? Impact of sample size and feature selection on classification using anatomical magnetic resonance images. NeuroImage 60(1): 59-70 (2012) - 2011
- [j6]Carlton Chu, Yizhao Ni
Kernel regression for fMRI pattern prediction. NeuroImage 56(2): 662-673 (2011) - [j5]Carlton Chu, Janaina Mourão Miranda, Yu-Chin Chiu
Utilizing temporal information in fMRI decoding: Classifier using kernel regression methods. NeuroImage 58(2): 560-571 (2011) - [c2]Carlton Chu, Daniel A. Handwerker
Measuring the Consistency of Global Functional Connectivity Using Kernel Regression Methods. PRNI 2011: 41-44 - 2010
- [j4]Andre F. Marquand
Quantitative prediction of subjective pain intensity from whole-brain fMRI data using Gaussian processes. NeuroImage 49(3): 2178-2189 (2010) - [j3]Cynthia M. Stonnington, Carlton Chu, Stefan Klöppel
Predicting clinical scores from magnetic resonance scans in Alzheimer's disease. NeuroImage 51(4): 1405-1413 (2010)
2000 – 2009
- 2008
- [j2]Karl J. Friston
Bayesian decoding of brain images. NeuroImage 39(1): 181-205 (2008) - [j1]Cynthia M. Stonnington, Geoffrey C. Y. Tan, Stefan Klöppel
Interpreting scan data acquired from multiple scanners: A study with Alzheimer's disease. NeuroImage 39(3): 1180-1185 (2008) - [c1]Yizhao Ni
Kernel methods for fMRI pattern prediction. IJCNN 2008: 692-697
Coauthor Index
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