330 citations · 333 across the 8 of their papers we have counts for
5 papers · 1 filter
CT-CLIP Representations for Multimodal Lung Cancer Survival Prediction
Sofie Allgöwer, Mikael Johansson, Andreas Hallqvist +4
Accurate prognosis prediction is important for treatment planning in lung cancer, but deep learning-driven survival modelling is often limited by the scarcity of curated imaging co…
CEVAR: Centerline Embedding Extraction for Endovascular Aneurysm Repair
Roman Naeem, Timo Niiniskorpi, Charlotte Sandström +6
Long-term mortality rates after endovascular aneurysm repair (EVAR) remain elevated due to post-EVAR rupture caused by loss of seal in stent graft sealing zones. Structured CT revi…
Exemplar Diffusion: Improving Medical Object Detection with Opportunistic Labels
Victor Wåhlstrand, Jennifer Alvén, Ida Häggström
We present a framework to take advantage of existing labels at inference, called \textit{exemplars}, in order to improve the performance of object detection in medical images. The…
H&E-based Computational Biomarker Enables Universal EGFR Screening for Lung Adenocarcinoma
Gabriele Campanella, David Ho, Ida Häggström +4
Lung cancer is the leading cause of cancer death worldwide, with lung adenocarcinoma being the most prevalent form of lung cancer. EGFR positive lung adenocarcinomas have been show…
DeepPET: A deep encoder-decoder network for directly solving the PET reconstruction inverse problem
Ida Häggström, C. Ross Schmidtlein, Gabriele Campanella +1
Positron emission tomography (PET) is a cornerstone of modern radiology. The ability to detect cancer and metastases in whole body scans fundamentally changed cancer diagnosis and…