PPT-Preprocessing

Author : trish-goza | Published Date : 2016-09-10

II Between Subjects John Ashburner Wellcome Trust Centre for Neuroimaging 12 Queen Square London UK Preprocessing overview fMRI timeseries Motion Correct Coregister

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Preprocessing: Transcript

II Between Subjects John Ashburner Wellcome Trust Centre for Neuroimaging 12 Queen Square London UK Preprocessing overview fMRI timeseries Motion Correct Coregister Deformation. 1 Mirek Riedewald Some slides based on presentation by Jiawei Han and Micheline Kamber Motivation • Garbage - in, garbage - out – Cannot get good mining results from bad data • Ne : . Coregistration. and Spatial Normalisation. Cassy . Fiford. and . Demis. Kia. Methods for Dummies 2014. With thanks to Gabriel Ziegler. 1. . Preprocessing. Recap. 2. . Coregistration. 3. Spatial Normalisation. . in. i. ncremental. SAT. Alexander Nadel. 1. , . Vadim Ryvchin. 1,2. , and . Ofer. Strichman. 2. 1 – Intel, Haifa, Israel. 2 – Technion, Haifa, Israel. SAT’12, Trento, Italy. Introduction. Methods & models for fMRI data . analysis in . neuroeconomics. 17 April 2010. Klaas Enno Stephan . Laboratory for Social and Neural Systrems Research. Institute for Empirical Research in Economics. Lars Kasper, PhD. TNU & MR-Technology Group. Institute for Biomedical Engineering, UZH & ETHZ. Generous slide support:. Guillaume . Flandin. Ged. Ridgway. Klaas. Enno Stephan. John . Ashburner. Acquisition, preprocessing and analysis of spectra. Raman . spectrometer. . scheme. Acquisition, preprocessing and analysis of Raman spectra. 2. Credits: http://. www.doitpoms.ac.uk. /. tlplib. /. raman. Presenter: Nizar Habash. COMS E6998: Topics in Computer Science: Machine Translation. February 7, 2013. Reading Set #1. Papers Discussed. Nizar Habash and Fatiha Sadat. 2006. . Arabic Preprocessing Schemes for Statistical Machine Translation. 严超赣. Chao-Gan Yan, Ph.D.. yancg@psych.ac.cn. http://. rfmri.org. /. yan. Institute of Psychology, Chinese Academy of Sciences. DPARSF. (Yan and Zang, 2010). 2. Data Processing Assistant for Resting-State fMRI (DPARSF). Ahmedul Kabir. TA, CS 548, Spring 2015. 1. Preprocessing Techniques Covered. Standardization and Normalization. Missing . value . replacement. Resampling. Discretization. Feature . Selection. Dimensionality Reduction: PCA. Learning Objectives. Be . able to describe when and why image corrections are appropriate or . necessary. Give . examples of some common approaches to image . correction. Understand the processing steps of Landsat data. Time framing . Frequency model. Fourier transform. Spectrogram. Preprocessing Ch2 , v8c. 1. . Revision: Raw data and PCM. Human listening range 20Hz . . 20K Hz. CD Hi-Fi quality music: 44.1KHz (sampling) 16bit. . Mohsen Ghafoorian. a,b. , Nico Karssemeijer. a. , Inge van Uden. c. , Frank-Erik de Leeuw. c. , Tom Heskes. b. , Elena Marchiori. b. and Bram Platel. a. a. Diagnostic Image Analysis Group, Radiology Department, . 严超赣. Chao-Gan Yan, Ph.D.. yancg@psych.ac.cn. http://. rfmri.org. /. yan. Institute of Psychology, Chinese Academy of Sciences. DPARSF. (Yan and Zang, 2010). 2. Data Processing Assistant for Resting-State fMRI (DPARSF). HCP . D. ata. Qunqun. Y. u. . Dr.. . Steve. . Marron. ,. . Dr.. . Kai. . Zhang. . &. . Dr.. . Ben. . Risk. University. . of. . North. . Carolina. . at. . Chapel. . Hill. Human. .

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