Searched for: author%3A%22Grewal%2C+M.%22
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Deist, Timo M. (author), Grewal, M. (author), Dankers, Frank J.W.M. (author), Alderliesten, T. (author), Bosman, P.A.N. (author)
Real-world problems are often multi-objective, with decision-makers unable to specify a priori which trade-off between the conflicting objectives is preferable. Intuitively, building machine learning solutions in such cases would entail providing multiple predictions that span and uniformly cover the Pareto front of all optimal trade-off...
conference paper 2023
Grewal, M. (author), Wiersma, Jan (author), Westerveld, Henrike (author), Bosman, P.A.N. (author), Alderliesten, T. (author)
Purpose: Deformable image registration (DIR) can benefit from additional guidance using corresponding landmarks in the images. However, the benefits thereof are largely understudied, especially due to the lack of automatic landmark detection methods for three-dimensional (3D) medical images. Approach: We present a deep convolutional neural...
journal article 2023
Bosma, Martijn M.A. (author), Dushatskiy, A. (author), Grewal, M. (author), Alderliesten, T. (author), Bosman, P.A.N. (author)
Deep Neural Networks (DNNs) have the potential for making various clinical procedures more time-efficient by automating medical image segmentation. Due to their strong, in some cases human-level, performance, they have become the standard approach in this field. The design of the best possible medical image segmentation DNNs, however, is task...
conference paper 2022