13 citations · 32 across the 9 of their papers we have counts for
4 papers · 1 filter
Extremely weakly-supervised blood vessel segmentation with physiologically based synthesis and domain adaptation
Peidi Xu, Olga Sosnovtseva, Charlotte Mehlin Sørensen +2
Accurate analysis and modeling of renal functions require a precise segmentation of the renal blood vessels. Micro-CT scans provide image data at higher resolutions, making more sm…
Localise to segment: crop to improve organ at risk segmentation accuracy
Abraham George Smith, Denis Kutnár, Ivan Richter Vogelius +2
Increased organ at risk segmentation accuracy is required to reduce cost and complications for patients receiving radiotherapy treatment. Some deep learning methods for the segment…
Auto-segmentation of Hip Joints using MultiPlanar UNet with Transfer learning
Peidi Xu, Faezeh Moshfeghifar, Torkan Gholamalizadeh +3
Accurate geometry representation is essential in developing finite element models. Although generally good, deep-learning segmentation approaches with only few data have difficulti…
Reducing Annotation Need in Self-Explanatory Models for Lung Nodule Diagnosis
Jiahao Lu, Chong Yin, Oswin Krause +3
Feature-based self-explanatory methods explain their classification in terms of human-understandable features. In the medical imaging community, this semantic matching of clinical…