Prone-to-supine breast tumor registration using landmarks

Prone-to-supine breast tumor registration using landmarks

Yeh, Haoming (TU Delft Electrical Engineering, Mathematics and Computer Science)

Hildebrandt, K.A. (mentor)
Eisemann, E. (graduation committee)
Zhang, X. (graduation committee)
Ambrosini, P. (mentor)

Delft University of Technology

Computer Science | Bioinformatics

2023-04-20

During the preoperative planning for breast-conserving surgery, the surgeon makes use of an MRI scan of the breast cancer patient in the prone position to accurately locate the tumour. However, surgery is performed with the patient in the supine position. The surgeon needs to mentally translate the location of the tumour from the prone position towards the supine position. The usage of mixed reality systems in the form of the Microsoft HoloLens could visually aid the surgeon by projecting the tumour in the supine position onto the patient. This requires us to obtain the tumour in the supine position by dealing with the prone-to-supine breast image registration problem.
We propose to maximize the overlap between the prone and supine surfaces of the breast through the use of soft constraints to guide the deformation. An initial subspace FEM simulation pulls the prone and supine surfaces towards each other at specified landmark correspondences between the surfaces. The resulting prone surface is projected onto the supine surface and these surface vertices are restricted to tangential movement across the surface of the breast. The tissues at the interior of the breast are deformed accordingly. Our experiments with synthesized data indicate the robustness of our method under various scenarios, except for the rigid misalignment between the prone and supine meshes. This problem of misalignment also affects the experiments with real-world data, which results in distances greater than 12mmbetween the centroids of the resulting deformed tumour and the ground-truth tumour.

deformable simulation
Breast cancer
breast conserving surgery
Finite Element Method
Constrained Optimization
nonrigid alignment
tumour registration
subspace simulation
Landmarks
Elasticity

http://resolver.tudelft.nl/uuid:c146bf27-de87-4520-81c7-b081cc7c9b18

Student theses

master thesis

© 2023 Haoming Yeh