Published in Nature: Scientific Reports, 2025
We developed a 3D aggressive lesion object detection model which can be used to detect and segment aggressive prostate cancer lesions, and recommend whether or not a biopsy is needed
Published in Radiology: Artificial Intelligence, 2025
How different scanner manufacturers and the inclusion of endorectal coils images can affect the performance of 3D deep learning models for prostate cancer classification.
Published in Computers in Biology and Medicine, 2024
Developing domain-shift invariant models, regarding scanner manufacturer, for prostate whole gland, zone and lesion segmentation
Published in Cancers, 2023
Evaluation of SOTA segmentation models for prostate whole gland and zone segmentation
Published in Biology, 2021
Developing ML and DL models for detecting the presence of emerging contaminants