Diabetic retinopathy early detection assisted by PDE constrained optimisation

Abstract: 

Diabetic  retinopathy  remains  one  of  the leading causes for vision impairment among working adults. The goal  of  this  paper  is  to  employ  variational  data  assimilation  to achieve early detection so as to prevent the condition from being irreversible. Method: The forward computational fluid dynamics simulation  adopted  by  previous  research  has  been  proven  to  be insufficient due to the non-patient-specific boundary conditions. A PDE constrained optimisation approach is proposed to infer the blood flow information via manipulating inlets/outlets boundary conditions as control variables. Results: The assimilated solutions were  compared  to  the in vivo results.  It  is  shown  a  better agreement  is  achieved.  Conclusion:  The  study  demonstrates  the variational  data  assimilation  is  a  feasible  methodology  to  assist diabetic  retinopathy  early  detection. Significance:  The  approach enables  the  definition  of  the  patient-specific  models  based  on  a small number of particle velocimetry experimental measurements which crucially need not be obtained at the vessels corresponding to the inlets/outlets.

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