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A Markov Random Fields Approach to the Gating of Flow Cytometry Data
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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
Kevin Brosnan
September 08, 2016
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Transcript
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
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
F L O W C Y T O M E
T R Y …
W h a t i s f l o w
c y t o m e t r y ? Flow Cyto metry
D a t a S t o r a g
e …
F l o w C y t o m e
t r y D a t a …
E X I S T I N G M E
T H O D S …
I n d u s t r y S t
a n d a r d … Expert 2 Expert 1
M o d e l B a s e d
C l u s t e r i n g …
t - d i s t r i b u
t i o n M i x t u r e s …
M A R K O V R A N D
O M F I E L D S …
None
I D E N T I F Y I N
G C L U S T E R S …
Connected Components Labelling…
R E S U L T S …
Original Segmentation Probability Map Area Area Granularity
F U R T H E R W O R
K …
None
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 ?