mri data using geometric deep learning
play

MRI data using geometric deep learning Fernanda L. Ribeiro, Steffen - PowerPoint PPT Presentation

Jan 23, 2024 •37 likes •97 views

DeepRetinotopy : Predicting the functional organization of human visual cortex from structural MRI data using geometric deep learning Fernanda L. Ribeiro, Steffen Bollmann, Alexander M. Puckett Retinotopic organization of the visual cortex

  1. DeepRetinotopy : Predicting the functional organization of human visual cortex from structural MRI data using geometric deep learning Fernanda L. Ribeiro, Steffen Bollmann, Alexander M. Puckett

  2. Retinotopic organization of the visual cortex http://mriquestions.com/visual.html Dougherty et al., 2003 MIDL 2020 2

  3. Retinotopic mapping with geometric deep learning MIDL 2020 3

  4. Individual differences in retinotopic maps MIDL 2020 4

  5. Error and individual variability in retinotopic maps MIDL 2020 5

  6. Questions/comments? Check out our complete manuscript on bioRxiv: https://www.biorxiv.org/content/10.1101/2020.02.11.934471v2 fernanda.ribeiro@uq.edu.au @NandaRibeiro93 @sbollmann_MRI @pucketta_a MIDL 2020 6

Download Presentation
Download Policy: The content available on the website is offered to you 'AS IS' for your personal information and use only. It cannot be commercialized, licensed, or distributed on other websites without prior consent from the author. To download a presentation, simply click this link. If you encounter any difficulties during the download process, it's possible that the publisher has removed the file from their server.

Recommend

Geometric Deep Learning going beyond Euclidean data Michael Bronstein Imperial College London /

Geometric Deep Learning going beyond Euclidean data Michael Bronstein Imperial College London /

Geometric Deep Learning going beyond Euclidean data Michael Bronstein Imperial College London / Twitter Perceptron ( " ! " ( # ! # + * = sign / 0 1 ( $ ! $ & = ( $)" 1 simplest neural network Rosenblatt 1957

1.55k views • 117 slides
Geometric View to Deep Learning David Xianfeng Gu 1 1 Computer Science & Applied Mathematics

Geometric View to Deep Learning David Xianfeng Gu 1 1 Computer Science & Applied Mathematics

Geometric View to Deep Learning David Xianfeng Gu 1 1 Computer Science & Applied Mathematics SUNY at Stony Brook University Center of Mathematical Sciences and Appications Harvard University Valse Webinar David Gu Geometric Understanding

1.08k views • 86 slides
3D Deep Learning on Geometric Forms Hao Su Many 3D representations are available Candidates:

3D Deep Learning on Geometric Forms Hao Su Many 3D representations are available Candidates:

3D Deep Learning on Geometric Forms Hao Su Many 3D representations are available Candidates: multi-view images depth map volumetric polygonal mesh point cloud primitive-based CAD models 3D representation Candidates: multi-view images

1.32k views • 86 slides
3D Deep Learning on Geometric Forms Hao Su Many 3D representations are available Candidates:

3D Deep Learning on Geometric Forms Hao Su Many 3D representations are available Candidates:

3D Deep Learning on Geometric Forms Hao Su Many 3D representations are available Candidates: multi-view images depth map volumetric polygonal mesh point cloud primitive-based CAD models 3D representation Candidates: multi-view images

1.34k views • 75 slides
Image Classification with DIGITS NVIDIA Deep Learning Institute 1 DEEP LEARNING INSTITUTE DLI

Image Classification with DIGITS NVIDIA Deep Learning Institute 1 DEEP LEARNING INSTITUTE DLI

Image Classification with DIGITS NVIDIA Deep Learning Institute 1 DEEP LEARNING INSTITUTE DLI Mission Helping people solve challenging problems using AI and deep learning. Developers, data scientists and engineers Self-driving cars,

1.44k views • 72 slides
Minjie Wang Deep Learning Deep Learning trend in the past 10 years Caffe State-of-art DL

Minjie Wang Deep Learning Deep Learning trend in the past 10 years Caffe State-of-art DL

Tofu: Parallelizing Deep Learning Systems with Automatic Tiling Minjie Wang Deep Learning Deep Learning trend in the past 10 years Caffe State-of-art DL system is based on dataflow GPU#0 w1 w2 data g1 g2 Forward propagation

405 views • 38 slides
STRUCTURE INTO MACHINE LEARNING TRINITY OF AI ALGORITHMS COMPUTE DATA 2 DEEP LEARNING IS

STRUCTURE INTO MACHINE LEARNING TRINITY OF AI ALGORITHMS COMPUTE DATA 2 DEEP LEARNING IS

Anima Anandkumar BEYOND BLACK BOXES: INFUSING STRUCTURE INTO MACHINE LEARNING TRINITY OF AI ALGORITHMS COMPUTE DATA 2 DEEP LEARNING IS DATA-HUNGRY STRUCTURE-INFUSED LEARNING Learning Data Priors = + Learning Data Priors = + How

579 views • 44 slides
Effectiveness of Deep Learning Vs. Machine Learning in a Health Care Use Case RxToDx A Data

Effectiveness of Deep Learning Vs. Machine Learning in a Health Care Use Case RxToDx A Data

Effectiveness of Deep Learning Vs. Machine Learning in a Health Care Use Case RxToDx A Data Science Machine Learning/Deep Learning Show Case Dima Rekesh/Julie Zhu/Ravi Rajagopalan Optum Technology November, 2017 Analytics Machine

483 views • 32 slides
Deep Learning With Differential Privacy Presenter: Xiaojun Xu Deep Learning Framework

Deep Learning With Differential Privacy Presenter: Xiaojun Xu Deep Learning Framework

Deep Learning With Differential Privacy Presenter: Xiaojun Xu Deep Learning Framework Autonomous Driving Gaming Face Recognition Healthcare Deep Learning Framework Dataset Server Model Privacy Issues of Training Data Dataset Server

366 views • 33 slides
Foundations of Artificial Intelligence 14. Deep Learning Learning from Raw Data Joschka

Foundations of Artificial Intelligence 14. Deep Learning Learning from Raw Data Joschka

Foundations of Artificial Intelligence 14. Deep Learning Learning from Raw Data Joschka Boedecker and Wolfram Burgard and Frank Hutter and Bernhard Nebel and Michael Tangermann Albert-Ludwigs-Universit at Freiburg July 10, 2019 Motivation:

1.21k views • 68 slides
Edge-based Discovery of Training Data for Machine Learning CMU authors Deep Learning Recipe

Edge-based Discovery of Training Data for Machine Learning CMU authors Deep Learning Recipe

CSci 8980 Edge-based Discovery of Training Data for Machine Learning CMU authors Deep Learning Recipe Collect a large amount of data and label it Select a model and train a DNN Deploy the DNN for inference Labelled Data Some

409 views • 14 slides
Hao Su July 6, 2017 Outline Overview of 3D deep learning 3D deep learning algorithms

Hao Su July 6, 2017 Outline Overview of 3D deep learning 3D deep learning algorithms

Deep 3D Representation Learning for Visual Computing Hao Su July 6, 2017 Outline Overview of 3D deep learning 3D deep learning algorithms Conclusion 2 Outline Overview of 3D deep learning Background 3D deep learning tasks 3D deep

1.66k views • 122 slides
STARTING A DEEP LEARNING PROJECT Bryan Catanzaro, 11 May 2017 Supervised learning (learning

STARTING A DEEP LEARNING PROJECT Bryan Catanzaro, 11 May 2017 Supervised learning (learning

STARTING A DEEP LEARNING PROJECT Bryan Catanzaro, 11 May 2017 Supervised learning (learning from tagged data) X Y Input Output tag: Yes/No Image (Is it a coffee mug?) Yes Data: No Learning X Y mappings is hugely useful Andrew Ng

347 views • 23 slides
DEEP LEARNING ON RF DATA Adam Thompson | Senior Solutions Architect March 29, 2018 Background

DEEP LEARNING ON RF DATA Adam Thompson | Senior Solutions Architect March 29, 2018 Background

DEEP LEARNING ON RF DATA Adam Thompson | Senior Solutions Architect March 29, 2018 Background Information Signal Processing and Deep Learning Radio Frequency Data Nuances Complex Domain Representations and AGENDA Applications The Case

481 views • 27 slides
ACCELERATE DEEP LEARNING WITH NVIDIA'S DEEP LEARNING PLATFORM | STEPHEN JONES | GTC16 DEEP

ACCELERATE DEEP LEARNING WITH NVIDIA'S DEEP LEARNING PLATFORM | STEPHEN JONES | GTC16 DEEP

ACCELERATE DEEP LEARNING WITH NVIDIA'S DEEP LEARNING PLATFORM | STEPHEN JONES | GTC16 DEEP LEARNING EVERYWHERE INTERNET & CLOUD MEDICINE & BIOLOGY MEDIA & ENTERTAINMENT SECURITY & DEFENSE AUTONOMOUS MACHINES Image

307 views • 26 slides
Sense Making in an IOT World: Sensor Data Analysis with Deep Learning Natalia Vassilieva, PhD

Sense Making in an IOT World: Sensor Data Analysis with Deep Learning Natalia Vassilieva, PhD

GTC 2016 Sense Making in an IOT World: Sensor Data Analysis with Deep Learning Natalia Vassilieva, PhD Senior Research Manager Deep learning proof points as of today Vision Speech Text Other Search & information Interactive voice

351 views • 33 slides
Administrivia Enrollment Lottery Paper Reviews (Adobe) Data passwords My

Administrivia Enrollment Lottery Paper Reviews (Adobe) Data passwords My

Administrivia Enrollment Lottery Paper Reviews (Adobe) Data passwords My office hours Michael J. Black (and Frank Wood) - Feb 2005 Brown University Good Cop Bad Cop Two or three ways to think about this class

480 views • 33 slides
High-dimensional geometry of cortical population activity Marius Pachitariu University College

High-dimensional geometry of cortical population activity Marius Pachitariu University College

High-dimensional geometry of cortical population activity Marius Pachitariu University College London Part I: introduction to the brave new world of large - scale neuroscience Part II: large-scale data preprocessing with Suite2p

886 views • 57 slides
I590 Interactive Visual Analytics Week 3 Perception and Cognition D3 selections Khairi Reda |

I590 Interactive Visual Analytics Week 3 Perception and Cognition D3 selections Khairi Reda |

I590 Interactive Visual Analytics Week 3 Perception and Cognition D3 selections Khairi Reda | redak@iu.edu School of Informa5cs & Compu5ng, IUPUI Last week Last week Principles of Visual Integrity Last week Principles of Visual

1.3k views • 103 slides
Neurobiology HMS 230 Harvard/GSAS 78454 Visual Object Recognition Primary Visual Cortex Camille

Neurobiology HMS 230 Harvard/GSAS 78454 Visual Object Recognition Primary Visual Cortex Camille

Neurobiology HMS 230 Harvard/GSAS 78454 Visual Object Recognition Primary Visual Cortex Camille Gmez-Laberge Postdoctoral Fellow in Neurobiology October 3, 2016 Visual system Anatomy Physiology Functional organization Receptive field

451 views • 34 slides
Mechanisms underlying feature selectivity in primary sensory cortices Thomas Bessah In other

Mechanisms underlying feature selectivity in primary sensory cortices Thomas Bessah In other

Mechanisms underlying feature selectivity in primary sensory cortices Thomas Bessah In other to get access to the speakers comments, click on: Comments\show comments list Kaniza Triangle 0 o A 90 o L 90 o R A L A R pulvinar pretectum

662 views • 55 slides
Neural network representations and visual processing in brains Katja Seeliger [ www.ccnlab.net |

Neural network representations and visual processing in brains Katja Seeliger [ www.ccnlab.net |

Neural network representations and visual processing in brains Katja Seeliger [ www.ccnlab.net | Marcel van Gerven ] Neural network representations and visual processing in brains Computational Cognitive Neuroscience Lab Develop computational

405 views • 21 slides
CS 523: Multimedia Systems Angus Forbes creativecoding.evl.uic.edu/courses/cs523 Today -

CS 523: Multimedia Systems Angus Forbes creativecoding.evl.uic.edu/courses/cs523 Today -

CS 523: Multimedia Systems Angus Forbes creativecoding.evl.uic.edu/courses/cs523 Today - Convolutional Neural Networks - Work on Project 1 http://playground.tensorflow.org/ Convolutional Neural Networks ConvNets, or CNNs: - An approach to

645 views • 29 slides
Learning to See 1 Virginia R. de Sa Department of Cognitive Science UCSD Interests: Neural

Learning to See 1 Virginia R. de Sa Department of Cognitive Science UCSD Interests: Neural

Learning to See 1 Virginia R. de Sa Department of Cognitive Science UCSD Interests: Neural Computation, Biological and Machine Learning and Perception, Multi-sensory integration Outline 2 Introduction to the vision problem and the visual

617 views • 61 slides

More recommend