InitRech 2015/2016, sujet 13

Summary

Female pelvic disorder such as the organ prolapse becomes a very common problem as a woman ages.About 20 to 30% women suffer from the severe degree of prolapse and more than 60% of women who are over 60 years are affected by this pathology.These problems are connected to the mobility of female pelvic system.In this system, a meaningful analysis of medical images usually decides the physicain's diagnosis.However, a human perception or a medical experience cannot be avoided and these two factors may cause the variability in the diagnoses.Hence a semi-automatic method is proposed as an important preliminary step for futher studies and modeling for organ shapes detection.The use of B-splines and offsets has been introduced as an algorithm to create thick surfaces of hollow pelvic organs.This modelling was a step between segmentation and physical modelling.Besides this, a new B-spline-like method is introduced because it is more consistent with the numercial approch.Finally, the model-to-image correlation can be regarded as an energy minimisation problem.To solve this problem,fisrt of all,we should find the spatial correspondance of two medical images, one of which is the virtual image generated from the model.

Main Contribution

The proposed approach can be formulated as an optimisation procedure in the view of computation.Hence, 4 major parts are needed: 1.input data(3D static and 2D dynamic MR images) 2.a mathematical model with variables to be optimised(B-spline Model) 3.a cost function that links the model to the input data(Cost Function Formulation) 4.an optimiser that finds the optimal values of the parameters to minimise the cost function(Optimisation)