The impact of manual threshold selection in medical additive manufacturing. - Maureen van Eijnatten; Juha Koivisto; Kalle Karhu; Tymour Forouzanfar; Jan Wolff (Int. J. Comput. Assist. Radiol. Surg., 2017)

CT image segmentation of bone for medical additive manufacturing using a convolutional neural network. - Jordi Minnema; Maureen van Eijnatten; Wouter M. Kouw; Faruk Diblen; Adriënne Mendrik; Jan Wolff (Comput. Biol. Medicine, 2018)

A Cone-Beam X-Ray CT Data Collection Designed for Machine Learning. - Henri Der Sarkissian; Felix Lucka; Maureen van Eijnatten; Giulia Colacicco; Sophia Bethany Coban; Kees Joost Batenburg (CoRR, 2019)

Parallel-beam X-ray CT datasets of apples with internal defects and label balancing for machine learning. - Sophia Bethany Coban; Vladyslav Andriiashen; Poulami Somanya Ganguly; Maureen van Eijnatten; Kees Joost Batenburg (CoRR, 2020)

3D deformable registration of longitudinal abdominopelvic CT images using unsupervised deep learning. - Maureen van Eijnatten; Leonardo Rundo; Kees Joost Batenburg; Felix Lucka; Emma Beddowes; Carlos Caldas; Ferdia A. Gallagher; Evis Sala; Carola-Bibiane Schönlieb; Ramona Woitek (Comput. Methods Programs Biomed., 2021)

Comparison of convolutional neural network training strategies for cone-beam CT image segmentation. - Jordi Minnema; Jan Wolff; Juha Koivisto; Felix Lucka; Kees Joost Batenburg; Tymour Forouzanfar; Maureen van Eijnatten (Comput. Methods Programs Biomed., 2021)

Quantitative Comparison of Deep Learning-Based Image Reconstruction Methods for Low-Dose and Sparse-Angle CT Applications. - Johannes Leuschner; Maximilian Schmidt; Poulami Somanya Ganguly; Vladyslav Andriiashen; Sophia Bethany Coban; Alexander Denker; Dominik F. Bauer; Amir Hadjifaradji; Kees Joost Batenburg; Peter Maass; Maureen van Eijnatten (J. Imaging, 2021)