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A Markov Random Fields Approach to the Gating o...

Avatar for Kevin Brosnan Kevin Brosnan
September 08, 2016
Research
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A Markov Random Fields Approach to the Gating of Flow Cytometry Data

Royal Statistical Society Conference Prize winning session

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Kevin Brosnan

September 08, 2016
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Transcript

  1. A U T O M A T E D G

    A T I N G O F F L O W C Y T O M E T R Y D A T A V I A M A R K O V R A N D O M F I E L D S K e v i n B r o s n a n , U n i v e r s i t y o f L i m e r i c k

  2. P R E S E N T A T I

    O N O U T L I N E Flow Cytometry Existing methods Markov Random Fields Cluster Identification Results Further Work

  3. F L O W C Y T O M E

    T R Y …

  4. W h a t i s f l o w

    c y t o m e t r y ? Flow Cyto metry

  5. D a t a S t o r a g

    e …

  6. F l o w C y t o m e

    t r y D a t a …

  7. E X I S T I N G M E

    T H O D S …

  8. I n d u s t r y S t

    a n d a r d … Expert 2 Expert 1

  9. M o d e l B a s e d

    C l u s t e r i n g …

  10. t - d i s t r i b u

    t i o n M i x t u r e s …

  11. M A R K O V R A N D

    O M F I E L D S …
  12. None

  13. I D E N T I F Y I N

    G C L U S T E R S …

  14. Connected Components Labelling…

  15. R E S U L T S …

  16. Original Segmentation Probability Map Area Area Granularity

  17. F U R T H E R W O R

    K …
  18. None

  19. T H A N K S F O R L

    I S T E N I N G ! A N Y Q U E S T I O N S ?