University of Twente Student Theses
Exploring the Prognostic Value of Deep Learning Image-to-Image Registration for Immunotherapy Patient Monitoring
Loohuis, Ingmar (2022) Exploring the Prognostic Value of Deep Learning Image-to-Image Registration for Immunotherapy Patient Monitoring.
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| Abstract: | CT imaging is performed for the monitoring of treatment response in cancer patients receiving immunotherapy. RECIST is currently used for prognostication but has several limitations. This study implements a novel deep learning approach, the prognostic AI Monitor (PAM) on a large pancancer dataset that predicts survival by quantifying morphological deformations. The approach used to quantify these deformations was to pretrain a deep learning network to perform image registration in an unsupervised fashion. From the pre-trained network, features can be extracted that represent the deformations and these can be linked to 1-year survival. To provide explainability, these latent space was disentangled using the Hessian Penalty. |
| Item Type: | Essay (Master) |
| Faculty: | TNW: Science and Technology |
| Subject: | 44 medicine, 54 computer science |
| Programme: | Technical Medicine MSc (60033) |
| Link to this item: | https://purl.utwente.nl/essays/90489 |
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