Ine Dirks

Computer-aided detection and segmentation of malignant melanoma lesions on whole-body <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si2.svg"><mml:msup><mml:mrow/><mml:mn>18</mml:mn></mml:msup></mml:math>F-FDG PET/CT using an interpretable deep learning approach

Ine Dirks, Marleen Keyaerts, Bart Neyns et al. · Computer Methods and Programs in Biomedicine · 2022 · 27 citations · Full text

Medicine, Oncology, Radiology +17

Comparative study of deep learning methods for the automatic segmentation of lung, lesion and lesion type in CT scans of COVID-19 patients

Sofie Tilborghs, Ine Dirks, Lucas Fidon et al. · arXiv (Cornell University) · 2020 · 14 citations · Full text

Medicine, Computer Science, Radiology +15

Comparative study of deep learning methods for the automatic segmentation of lung, lesion and lesion type in CT scans of COVID-19 patients

Sofie Tilborghs, Ine Dirks, Lucas Fidon et al. · VUBIR (Vrije Universiteit Brussel) · 2020 · 11 citations · Full text

Medicine, Computer Science, Radiology +15

Development and Validation of a Predictive Model for Metastatic Melanoma Patients Treated with Pembrolizumab Based on Automated Analysis of Whole-Body [18F]FDG PET/CT Imaging and Clinical Features

Ine Dirks, Marleen Keyaerts, Iris Dirven et al. · Cancers · 2023 · 10 citations · Full text

Medicine, Nuclear Medicine, Oncology +17