Vacancies

Contact: Liselot Goris

Breast cancer detection by artificial intelligence (AI) has shown promising results, with neural networks demonstrating comparable or even superior performance to radiologists when interpreting mammograms [1,2].

Physical phantoms can provide standardised test objects for testing the performance of imaging systems and computer-aided diagnosis. 

Goals

• To 3D print realistic compressed breast phantoms by implementing the technique as described in [3].
• To acquire and/or process images in different conditions to test the resilience of AI algorithms for mammography screening.

Contact information and supervision: Liselot Goris, This email address is being protected from spambots. You need JavaScript enabled to view it. & Ioannis Sechopoulos, This email address is being protected from spambots. You need JavaScript enabled to view it..

The project duration is 6-9 months.

This project is based at the University of Twente’s multi-modality medical imaging group (M3I).

References:

1. Rodriguez-Ruiz et al  2019 J Natl Cancer Inst. 111(9):916-922. DOI. 

2. Sarah D. Verboom et al 2024 Proceedings volume 12927 Medical Imaging 2024: computer aided diagnosis. DOI.

3. Stephan Schopphoven et al 2019 Phys. Med. Biol. 64 215005. DOI.