shape and texture prior for 2d 3d analysis synthesis of
play

Shape and texture prior for 2D/3D analysis/ synthesis of neural stem - PowerPoint PPT Presentation

Dec 07, 2023 •21 likes •151 views

A French-Singaporean joint laboratory Shape and texture prior for 2D/3D analysis/ synthesis of neural stem cells for fate prediction 2D differentiation and 3D

  1. ���������������������������� A French-Singaporean joint laboratory Shape and texture prior for 2D/3D analysis/ synthesis of neural stem cells for fate prediction 2D differentiation and 3D reconstruction www.ipal.cnrs.fr

  2. NEUROSPHERE FORMATION ASSAY Embriotic Mouse Brain Neurosphere Growth Differentiation of Progenitor Cell Neuron Astrocyte Progenitor Cell Oligodendrocyte Stem Cell ‣ Culture and purification “ in vitro ” of neural stem cell [1] . ‣ Identify “ proliferation ” and “ multi-potency ”. ‣ No tracks of the origin cell & low survivability. ‣ Three dimension proliferation & two dimension differentiation. [1] S. Ahmed. The culture of neural stem cells. Journal of cellular biochemistery, 2009. ⎋ 2

  3. DATA ‣ Phase contrast time lapse sequence of 2D images. ‣ 40x magnification with 3x3 binning. ‣ 464 x 346 spatial resolution & 20 min time resolution. ‣ Online microscope tracking [2] [2] C.-H. Huang, S. Sankaran, D. Racoceanu, S. Hariharan, and S. Ahmed. Online 3-d tracking of suspension cells imaged with phase-contrast microscopy. IEEE Transactions on Biomedical Engineering, 2012. ⎋ 3

  4. 2D-3D REGISTRATION REVIEW ‣ Review: [3] - Dimensionality problematic: projection, back-projection & reconstruction. 2D silhouette 2D silhouettes 2D silhouette back- projection projection 3D reconstruct model 3D model 3D model 3D model [3] P . Markelj, D. Tom ă zev ĭ c, B. Likar, and F. Pern ŭ s. A review of 3d/2d registration methods for image-guided interventions. Medical Image Analysis, 2012. ⎋ 4

  5. PROPOSED METHOD (1) Analysis (3) Registration - Optimisation 2D data stop criterion 2D Cell Detection Registration e g a s m l e I d Convergence e o p Observation projected m loop o data c t s s e o B r c i M 3D Models 3D data Projection optimisation Generation (2) Synthesis ‣ Analysis - cell detection ‣ Synthesis - model generation ‣ Registration / Optimisation - rank & optimise selected model ⎋ 5

  6. CELL DETECTION IN CLUSTER Input Image ROI Hough Partial Level Set Circle Detection Local Maxima Output Detection Detection ⎋ 6

  7. 2D IMAGE - 3D MODEL REGISTRATION ‣ Criteria Shape Texture Topology Observation Texture modelisation 1 r (xc,yc) Model -r (xc,yc) r Registration Feature based Intensity based ⎋ 7

  8. PROPOSED METHOD M 1 Projection 1 E 1 M 2 E 2 Projection 2 Observation t E i M i Projection i Score ⎋ 8

  9. RESULTS Raw Temporary Detection results Registration error Model selected ⎋ 9

  10. CELL DETECTION IN CLUSTER VIDEO ⎋ 10

  11. FUTURE WORK ‣ Model generation - Integrate a dynamic generation. New Cell Model Probability ⎋ 11

  12. NEXT STEPS ‣ From animal to human stem cells (skin) ‣ A suite of integrated microscopy systems for imaging anatomies of complex 3D+T (4D) cell culture systems ‣ Drug testing platform for biologists using high-throughput imaging ‣ Next generation of neurodegenerative diseases treatments ⎋ 12

  13. Image & Pervasive Access Lab International joint research unit - UMI CNRS 2955 www.ipal.cnrs.fr ⎋

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

Shape from Texture Texture Discrimination 1 Texture Texture Synthesis Goal of texture

Shape from Texture Texture Discrimination 1 Texture Texture Synthesis Goal of texture

Texture Modeling Texture What is texture? Easy to recognize, hard to define Deterministic/regular textures (thing-like) Stochastic textures (stuff-like) Tasks What is texture? Discrimination / Segmentation An

312 views • 29 slides
Texture Synthesis Given a texture, create more CS176: Texture Synthesis All examples from Wei

Texture Synthesis Given a texture, create more CS176: Texture Synthesis All examples from Wei

Texture Synthesis Given a texture, create more CS176: Texture Synthesis All examples from Wei & Levoy CS 176 Winter 2011 CS 176 Winter 2011 1 2 Texture Synthesis Texture Synthesis Dont expect too much And amazing successes All

347 views • 3 slides
Solid Texture Synthesis Solid Texture Synthesis Solid Texture Synthesis from 2D Exemplars from

Solid Texture Synthesis Solid Texture Synthesis Solid Texture Synthesis from 2D Exemplars from

Solid Textures Solid Textures Solid Texture Synthesis Solid Texture Synthesis Solid Texture Synthesis from 2D Exemplars from 2D Exemplars from 2D Exemplars Johannes Kopf, University of Konstanz Chi-Wing Fu, Hong Kong Sc & Tech Daniel

268 views • 10 slides
Texture S ynthesis Daniel Cohen-Or + = + = = The Goal of Texture Synthesis input image

Texture S ynthesis Daniel Cohen-Or + = + = = The Goal of Texture Synthesis input image

Texture S ynthesis Daniel Cohen-Or + = + = = The Goal of Texture Synthesis input image SYNTHESIS True (infinite) texture generated image Given a finite sample (large enough) of some texture, the goal is to synthesize other samples

978 views • 68 slides
How to use Gradient and Multi-Texture 1. Many situations, we need use the gradient texture for our

How to use Gradient and Multi-Texture 1. Many situations, we need use the gradient texture for our

How to use Gradient and Multi-Texture 1. Many situations, we need use the gradient texture for our shape or text, so let s learn how to use our gradient and multi-texture functions. First, crate a shape. 2. Select this shape, switch to color

196 views • 3 slides
Outline Texture Synthesis What is Texture? How to Synthesize? Graphcut Textures

Outline Texture Synthesis What is Texture? How to Synthesize? Graphcut Textures

Graphcut Textures: Image and Video Synthesis using Graph Cuts (Kwatra, et al) presented by Adeel Bhutta Outline Texture Synthesis What is Texture? How to Synthesize? Graphcut Textures Main Idea, Contribution Patch

588 views • 20 slides
Shape from X: perspective, texture, shading Thurs. Feb. 15, 2018 1 Level of Analysis in

Shape from X: perspective, texture, shading Thurs. Feb. 15, 2018 1 Level of Analysis in

COMP 546 Lecture 11 Shape from X: perspective, texture, shading Thurs. Feb. 15, 2018 1 Level of Analysis in Perception high - behavior: what is the task ? what problem is being solved? - brain areas and pathways - neural coding -

638 views • 42 slides
1 Prior Work Stereology Prior Work Stereology Prior Work Texture Synthesis Prior

1 Prior Work Stereology Prior Work Stereology Prior Work Texture Synthesis Prior

Objective Objective Stereological Techniques Given a 2D slice through an aggregate material, for Solid Textures create a 3D volume with a comparable appearance. Rob Jagnow Julie Dorsey Holly Rushmeier MIT Yale University Yale University

636 views • 6 slides
Texture S ynthesis Daniel Cohen-Or Texture Weathering + = The slides are based of Efros and

Texture S ynthesis Daniel Cohen-Or Texture Weathering + = The slides are based of Efros and

Texture S ynthesis Daniel Cohen-Or Texture Weathering + = The slides are based of Efros and Freeman Efros&Freeman Image Quilting + = + = The Goal of Texture Synthesis input image SYNTHESIS True (infinite) texture generated

1.45k views • 100 slides
2) Synthesis Issues: 1) Discrimination/Analysis (Freeman) 1 Many more issues What is texture?

2) Synthesis Issues: 1) Discrimination/Analysis (Freeman) 1 Many more issues What is texture?

Announcements Texture For future problems sets: email matlab code by Edge detectors find differences in 11am, due date (same as deadline to hand in overall intensity. hardcopy). Average intensity is only simplest Todays

553 views • 8 slides
Shape Statistics for Image Segmentation with Prior Guillaume Charpiat PhD Defense - 2006,

Shape Statistics for Image Segmentation with Prior Guillaume Charpiat PhD Defense - 2006,

Introduction Shapes and Shape Metrics Variational Shape Warping Statistics Segmentation with prior Summary Shape Statistics for Image Segmentation with Prior Guillaume Charpiat PhD Defense - 2006, December 13 PhD Supervisor: Olivier

1.1k views • 84 slides
Texture Analysis and Segmentation Texture Analysis and Segmentation using Modulation Models

Texture Analysis and Segmentation Texture Analysis and Segmentation using Modulation Models

Texture Analysis and Segmentation Texture Analysis and Segmentation using Modulation Models Department of Mathematics, UCLA I Image Processing Seminar P i S i Iasonas Kokkinos Department of Statistics, UCLA Joint work with Georgios

639 views • 34 slides
Texture What is texture? Easy to recognize, hard to define Deterministic textures

Texture What is texture? Easy to recognize, hard to define Deterministic textures

Texture What is texture? Easy to recognize, hard to define Deterministic textures (thing-like) Stochastic textures (stuff-like) Tasks Discrimination / Segmentation Classification Texture synthesis

555 views • 34 slides
Surfaces How to carry to surface? Texture Synthesis: Surfaces and RD from Wei & Levoy = +

Surfaces How to carry to surface? Texture Synthesis: Surfaces and RD from Wei & Levoy = +

Surfaces How to carry to surface? Texture Synthesis: Surfaces and RD from Wei & Levoy = + Textures Textures Images surface given as mesh synthesis into textures synthesis onto vertices (fine enough) CS 176 Winter 2011 CS

1.24k views • 4 slides
Analysis of Informa.on The Visual Variables Size Value Texture Color

Analysis of Informa.on The Visual Variables Size Value Texture Color

Analysis of Informa.on The Visual Variables Size Value Texture Color Orienta.on Shape 2D Plane - 8 variables to work with - The components of graphic system The Level of Variables Level = perceptual proper.es

604 views • 39 slides
Photometric stereo for the measurement of surface texture and shape YAN YAN

Photometric stereo for the measurement of surface texture and shape YAN YAN

Photometric stereo for the measurement of surface texture and shape YAN YAN yany14@mails.tsinghua.edu.cn Main point Introduction of Background Building the sensor optical system Photometric stereo algorithm Results

540 views • 10 slides
Enhancing OPC differentiation in the context of MS The right approach? Charles

Enhancing OPC differentiation in the context of MS The right approach? Charles

Enhancing OPC differentiation in the context of MS The right approach? Charles ffrench-Constant MRC Centre for Regenerative Medicine University of Edinburgh Disclosures Advisory work for Bluerock, Roche. Previous collaborations with

521 views • 33 slides
Review of answers from experts to EMEA questions Paediatric Rheumatology Expert Meeting, London

Review of answers from experts to EMEA questions Paediatric Rheumatology Expert Meeting, London

Review of answers from experts to EMEA questions Paediatric Rheumatology Expert Meeting, London 4 th December 2009 Richard Vesel Design of the studies Controversial issue Withdrawal design: Carry over of positive effect

664 views • 16 slides
Proposal for an international registry for juvenile idiopathic arthritis patients treated with

Proposal for an international registry for juvenile idiopathic arthritis patients treated with

Proposal for an international registry for juvenile idiopathic arthritis patients treated with methotrexate Nicola Ruperto, MD, MPH PRINTO Senior Scientist Istituto G. Gaslini Genova (ITALY) EULAR Centre of Excellence in Rheumatology 2008-2013

785 views • 31 slides
An Integrated Platform Based on Bacterial Microcompartment(BMC) for de novo Proteinaceous

An Integrated Platform Based on Bacterial Microcompartment(BMC) for de novo Proteinaceous

An Integrated Platform Based on Bacterial Microcompartment(BMC) for de novo Proteinaceous Artificial Organelles USTC iGEM 2010 About our ideas Problems in chemical production Bacteria will be harder to stand this circumstance with the

441 views • 32 slides
Exam Success 29 April 2016 Exam Success Context The uncontrollables The controllables

Exam Success 29 April 2016 Exam Success Context The uncontrollables The controllables

Exam Success 29 April 2016 Exam Success Context The uncontrollables The controllables Practical Advice Emotional Well Being Context Pastoral preparation up to this point Fighting ground Why do we do mocks and Jan

721 views • 44 slides
External oligonucleotide standards enable cross laboratory and exchange of real-time PCR data Jo

External oligonucleotide standards enable cross laboratory and exchange of real-time PCR data Jo

External oligonucleotide standards enable cross laboratory and exchange of real-time PCR data Jo Vandesompele professor, Ghent University co-founder and CEO, Biogazelle Roche Molecular Biology Days Vilvoorde, 7 oktober, 2009 biomarker

202 views • 18 slides
UNITED STATES SECURITIES AND EXCHANGE COMMISSION Washington, D.C. 20549 FORM 10-Q Quarterly

UNITED STATES SECURITIES AND EXCHANGE COMMISSION Washington, D.C. 20549 FORM 10-Q Quarterly

UNITED STATES SECURITIES AND EXCHANGE COMMISSION Washington, D.C. 20549 FORM 10-Q Quarterly Report Pursuant to Section 13 or 15(d) of the Securities Exchange Act of 1934 for the Quarter Ended April 2, 2016 Transition Report Pursuant to

552 views • 51 slides
Continuous Manufacturing Framing a Future for Patients Paul C. Collins, Ph.D. and Carla

Continuous Manufacturing Framing a Future for Patients Paul C. Collins, Ph.D. and Carla

Continuous Manufacturing Framing a Future for Patients Paul C. Collins, Ph.D. and Carla Luciani, Ph.D. Small Molecule Design and Development Eli Lilly and Company Indianapolis, Indiana April 9-11, 2019 4th FDA/PQRI Conference on Advancing

637 views • 29 slides

More recommend