PG-4035, Virtual Microscopy in the cloud, by Wojciech Tarnawski
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PG-4035, Virtual Microscopy in the cloud, by Wojciech Tarnawski

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Presentation PG-4035, Virtual Microscopy in the cloud, by Wojciech Tarnawski at the AMD Developer Summit (APU13) Nov. 11-13, 2013.

Presentation PG-4035, Virtual Microscopy in the cloud, by Wojciech Tarnawski at the AMD Developer Summit (APU13) Nov. 11-13, 2013.

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PG-4035, Virtual Microscopy in the cloud, by Wojciech Tarnawski PG-4035, Virtual Microscopy in the cloud, by Wojciech Tarnawski Presentation Transcript

  • VIRTUAL  MICROSCOPY  IN  THE  CLOUD   WOJCIECH  TARNAWSKI  ,  CSO      MICROSCOPEIT  LTD.   1   |      PRESENTATION  TITLE      |      NOVEMBER  21,  2013      |      CONFIDENTIAL  
  • Virtual  Microscopy  in  the  Cloud   Wojciech  Tarnawski,  PhD,  CSO   MicroscopeIT  Ltd.,  Wroclaw,  Poland   2   |      PRESENTATION  TITLE      |      NOVEMBER  21,  2013      |      CONFIDENTIAL  
  • MICROSCOPY  IS  COMPLICATED   !  Different formats, different producers. !  Different software for different image processing tasks. !  Image analysis takes time. !  Open Source vs. Commercial Software. !  Image types: 2D (fluorescence, phase-contrast), 3D (confocal), 4D (3D objects in time), different channels targeting different molecular elements. 3   |      PRESENTATION  TITLE      |      NOVEMBER  21,  2013      |      CONFIDENTIAL   CreaMve  Commons  2.0,  Nicole  Yeary's  photos  via  GeRy  Images  
  • WHAT  IS  VIRTUM?   Cloud Computing Image processing pipeline integrated accessed in the web browser. Acceleration Time consuming image analysis ported to GPU. Robust and fast workflow-based image analysis Save time thanks to intelligent algorithms with „visual” development. Image  credit:  leverhawk.com,  Why  is  cloud  integraMon  sMll  an  adopMon  barrier,  2012.   4   |      PRESENTATION  TITLE      |      NOVEMBER  21,  2013      |      CONFIDENTIAL   Information Retrieval Phenotype detection of biologically relevant information directly from images. Flexibility All formats, dimensions and modality supported
  •                                                     IN  ACTION   Our  system:  32  GPU  cards     (6  donated  by  AMD)   Data  acquisi:on                                                         Database   " Work-­‐flow  based  image  processing  and  task  scheduling   5   |      PRESENTATION  TITLE      |      NOVEMBER  21,  2013      |      CONFIDENTIAL  
  • FEATURES,  APPLICATIONS   Visualization (Virtual Microscopy) Medicine and biology Clinical trials Scientific research E-learning                                                         Teleconferencing teleconsultations Quantitative data analysis Biotechnology High-Content and High-Throughput Screening Data Analysis 6   |      PRESENTATION  TITLE      |      NOVEMBER  21,  2013      |      CONFIDENTIAL  
  •   2D  Image  Series                  Viewer Visualiza:on                WSI  VisualizaMon                              3D  Image  Series                            Movie  ProjecMon                  3D  Geometry                          Rendering                                                            ReconstrucMon   Input  Data  Types Not  Ordered                    WSI            Image    z-­‐stacks      Time-­‐Lapse                                            Time-­‐Lapse Images (  Image  Pyramids)                                      Image  Series Z-­‐Stacks 7   |      PRESENTATION  TITLE      |      NOVEMBER  21,  2013      |      CONFIDENTIAL  
  • INPUT  DATA  TYPES  :  NOT-­‐ORDERED  SETS  AND  TIME-­‐LAPSE  IMAGE  SERIES   8   |      PRESENTATION  TITLE      |      NOVEMBER  21,  2013      |      CONFIDENTIAL  
  • INPUT  DATA  TYPES  :  Z-­‐STACKS  AND  TIME-­‐LAPSE  Z-­‐STACKS   9   |      PRESENTATION  TITLE      |      NOVEMBER  21,  2013      |      CONFIDENTIAL  
  • INPUT  DATA  TYPES  :  IMAGE  PYRAMID   10   |      PRESENTATION  TITLE      |      NOVEMBER  21,  2013      |      CONFIDENTIAL  
  •   2D  Image  Series                  Viewer Visualiza:on                WSI  VisualizaMon                              3D  Image  Series                            Movie  ProjecMon                  3D  Geometry                          Rendering                                                            ReconstrucMon   Input  Data  Types Not  Ordered                    WSI            Image    z-­‐stacks      Time-­‐Lapse                                            Time-­‐Lapse Images (  Image  Pyramids)                                      Image  Series Z-­‐Stacks Image  Processing  and  Analysis  Library 2-­‐3D  Mesurements            Image  Preprocessing      2-­‐3D  Object  SegmentaDon            2-­‐3D  Object  Analysis                    StaDsDcs Data  Analysis   2D  Image  Processing                        2-­‐3D  Image  ReconstrucDon                      Time-­‐Dependent  Analysis                                      Post-­‐Processing and  Analysis   11   |      PRESENTATION  TITLE      |      NOVEMBER  21,  2013      |      CONFIDENTIAL    
  • CLOUD  COMPONENTS    (BACK-­‐END)    1/3   Image  Processing  and  Analysis  Library  :  about  70  methods    tailored   for  microscopy    imaga  data  implemented  on  CPU  and  GPU 2-­‐3D  Mesurements      Image  Preprocessing  :  noise  removal,    contrast  improvement,  inhomogeneous   lighDng  removal,  opDcal  deconvoluDon,    2-­‐3D  Image  SDtching,  Histogram-­‐based   processing,  MulD-­‐channel  Image  Composing,  Image  ArithmeDc,  Edge  DetecDon,  …   etc. 2-­‐3D  Object  SegmentaDon    :  automaDc  or  machine-­‐learning  methods  for   segmentaDon  of  2-­‐3D  objects    e.g.  2-­‐3D  Cell  Tracking  Advanced  SegmentaDon  in   mulD-­‐dimensional  space  composed  with  texture  and  color  features,  AcDve  Contour   and  AcDve  Mesh,  Threshold  -­‐  and  Morphology  –  based    SegmentaDon,  Mean-­‐Shi[,   … 2-­‐3D  Object  Analysis  :  Split  into  2-­‐3D  Ellipsoids    e.g.  for  highly  clustered  cells  ,   Morphology  Operatos  ,  Weighted  Distance  Transform,  Voronoi  TriangulaDon,  Object   RecogniDon  module  for  Cell  Phase  ClassificaDon  by  Markov  chains 12   |      PRESENTATION  TITLE      |      NOVEMBER  21,  2013      |      CONFIDENTIAL   StaDsDcs  Module  –  PCA,  Basic  StaDsDcs,  Cluster  Analysis,  
  • 3D  IMAGE  SEGMENTATION  :  ACTIVE  MESH   13   |      PRESENTATION  TITLE      |      NOVEMBER  21,  2013      |      CONFIDENTIAL  
  • CLOUD  COMPONENTS    (BACK-­‐END)    1/3   Image  Processing  and  Analysis  Library  :  about  70  methods    tailored   for  microscopy    imaga  data  implemented  on  CPU  and  GPU Workflow-­‐based  image  processing   *    A  Robust  Algorithm  for  Segmen:ng  and  Tracking  Clustered  Cells  in  Time-­‐Lapse  Fluorescent  Microscopy   Tarnawski,  W.  ;  Kurtcuoglu,  V.  ;  Lorek,  P.  ;  Bodych,  M.  ;RoRer,  J.  ;  Muszkieta,  M.  ;  Piwowar,  L.  ;  Poulikakos,  D.  ;Majkowski,  M.  ;  Ferrari,  A.     Biomedical  and  Health  InformaMcs,  IEEE  Journal  of    Volume:  17  ,  Issue:  4    PublicaMon  Year:  2013  ,  Page(s):  862  -­‐  869     14   |      PRESENTATION  TITLE      |      NOVEMBER  21,  2013      |      CONFIDENTIAL  
  • WORKFLOW  –  BASED  IMAGE  PROCESSING  AND  ANALYSIS   15   |      PRESENTATION  TITLE      |      NOVEMBER  21,  2013      |      CONFIDENTIAL  
  • USE  CASES   !  Detection of nuclei and cytoplasm in 80 000 images (512x512 pixels) takes about 2 hours on multicore CPU (AMD  Athlon(tm)  II  X4  640  Processor).  GPU provided up to 4x acceleration !  Optical deconvolution : about 25x acceleration for 512x512 image !  3D-dimensional diffuse filter on image-stack (z-stack with 1920x1080) : about 10x acceleration 16   |      PRESENTATION  TITLE      |      NOVEMBER  21,  2013      |      CONFIDENTIAL  
  • CLOUD  COMPONENTS    (BACK-­‐END)    2/3   Image  Processing  and  Analysis  Library  :  about  70  methods    tailored   for  microscopy    imaga  data  implemented  on  CPU  and  GPU  Task  Scheduler  to  provide  image  analysis  results  for  many  users. Scheduling  approach  :          Scheduler  –>  Executor  –>  Worker  –>  Task -­‐  Schedules  image  processing  tasks  on  the  CPU  &  GPU  cluster.     -­‐  Monitors  CPU,  GPU,  memory,  storage  usage.     -­‐  OpMmizes  scalability.     17   |      PRESENTATION  TITLE      |      NOVEMBER  21,  2013      |      CONFIDENTIAL  
  • CLOUD  COMPONENTS     (BACK-­‐END)    3/3   Image  Processing  and  Analysis  Library  :  about  70  methods    tailored  for   microscopy    imaga  data  implemented  on  CPU  and  GPU  Task  Scheduler  to  provide  image  analysis  results  for  many  users. Database  Module    -­‐  to  store  the  microscopic  image  data Database  Module    provides  upload  data  module  that  supports: •   about    100  microscopic  image  data  formats  (i.e.    lsm,  nd2,  oly,    mulD-­‐ channel  ,  16-­‐bit  Dff,  basic  graphic  formats,  …) •   compressed  images  series    (zip) •   filename  parser  to  upload    image  series  ordered  by  channel,  z-­‐stack   layers,  Dme-­‐points,  … •   users  data  are  fully  organized •   users  can  be  assigned  to  many  projects 18   |      PRESENTATION  TITLE      |      NOVEMBER  21,  2013      |      CONFIDENTIAL  
  • PROJECT  DATA  ORGANIZATION   19   |      PRESENTATION  TITLE      |      NOVEMBER  21,  2013      |      CONFIDENTIAL  
  • CLIENT  (GUI)  COMPONENTS   Graphical  User  Interface    (GUI)  installed  as  a  plugin  in  the  web  browser:   !  Designed  for  touch-­‐based  devices.   !  Designed  to  tag  microscopic  image  series  with  metadata.   !  Includes  different  viewers  to  visualize  mulM-­‐dimensional  images.   !  Provides  „visual”  interface  to  design  the  workflow  for  image  processing  and  analysis.   !  Provides  tools  to  select  the  image  regions  for  futher  iamge  analysis.   20   |      PRESENTATION  TITLE      |      NOVEMBER  21,  2013      |      CONFIDENTIAL  
  • !  MicroscopeIT  Ltd.     Kutnowska  1-­‐2   Wroclaw,  Poland   !  Contact:  wojciech.tarnawski@microscopeit.com   Tel.  +48  605  111  445   Skype:tar_woj   21   |      PRESENTATION  TITLE      |      NOVEMBER  21,  2013      |      CONFIDENTIAL  
  • DISCLAIMER  &  ATTRIBUTION   The  informaMon  presented  in  this  document  is  for  informaMonal  purposes  only  and  may  contain  technical  inaccuracies,  omissions  and  typographical  errors.     The  informaMon  contained  herein  is  subject  to  change  and  may  be  rendered  inaccurate  for  many  reasons,  including  but  not  limited  to  product  and  roadmap   changes,  component  and  motherboard  version  changes,  new  model  and/or  product  releases,  product  differences  between  differing  manufacturers,  sotware   changes,  BIOS  flashes,  firmware  upgrades,  or  the  like.  AMD  assumes  no  obligaMon  to  update  or  otherwise  correct  or  revise  this  informaMon.  However,  AMD   reserves  the  right  to  revise  this  informaMon  and  to  make  changes  from  Mme  to  Mme  to  the  content  hereof  without  obligaMon  of  AMD  to  noMfy  any  person  of   such  revisions  or  changes.     AMD  MAKES  NO  REPRESENTATIONS  OR  WARRANTIES  WITH  RESPECT  TO  THE  CONTENTS  HEREOF  AND  ASSUMES  NO  RESPONSIBILITY  FOR  ANY   INACCURACIES,  ERRORS  OR  OMISSIONS  THAT  MAY  APPEAR  IN  THIS  INFORMATION.     AMD  SPECIFICALLY  DISCLAIMS  ANY  IMPLIED  WARRANTIES  OF  MERCHANTABILITY  OR  FITNESS  FOR  ANY  PARTICULAR  PURPOSE.  IN  NO  EVENT  WILL  AMD  BE   LIABLE  TO  ANY  PERSON  FOR  ANY  DIRECT,  INDIRECT,  SPECIAL  OR  OTHER  CONSEQUENTIAL  DAMAGES  ARISING  FROM  THE  USE  OF  ANY  INFORMATION   CONTAINED  HEREIN,  EVEN  IF  AMD  IS  EXPRESSLY  ADVISED  OF  THE  POSSIBILITY  OF  SUCH  DAMAGES.     ATTRIBUTION   ©  2013  Advanced  Micro  Devices,  Inc.  All  rights  reserved.  AMD,  the  AMD  Arrow  logo  and  combinaMons  thereof  are  trademarks  of  Advanced  Micro  Devices,   Inc.  in  the  United  States  and/or  other  jurisdicMons.    SPEC    is  a  registered  trademark  of  the  Standard  Performance  EvaluaMon  CorporaMon  (SPEC).  Other   names  are  for  informaMonal  purposes  only  and  may  be  trademarks  of  their  respecMve  owners.   22   |      PRESENTATION  TITLE      |      NOVEMBER  21,  2013      |      CONFIDENTIAL