452 citations · 761 across the 23 of their papers we have counts for
10 papers · 1 filter
Active learning using adaptable task-based prioritisation
Shaheer U. Saeed, João Ramalhinho, Mark Pinnock +9
Supervised machine learning-based medical image computing applications necessitate expert label curation, while unlabelled image data might be relatively abundant. Active learning…
Bayesian Pseudo Labels: Expectation Maximization for Robust and Efficient Semi-Supervised Segmentation
Mou-Cheng Xu, Yukun Zhou, Chen Jin +5
This paper concerns pseudo labelling in segmentation. Our contribution is fourfold. Firstly, we present a new formulation of pseudo-labelling as an Expectation-Maximization (EM) al…
Few-shot Semantic Segmentation with Self-supervision from Pseudo-classes
Yiwen Li, Gratianus Wesley Putra Data, Yunguan Fu +2
Despite the success of deep learning methods for semantic segmentation, few-shot semantic segmentation remains a challenging task due to the limited training data and the generalis…
Adaptable image quality assessment using meta-reinforcement learning of task amenability
Shaheer U. Saeed, Yunguan Fu, Vasilis Stavrinides +8
The performance of many medical image analysis tasks are strongly associated with image data quality. When developing modern deep learning algorithms, rather than relying on subjec…
Development and evaluation of intraoperative ultrasound segmentation with negative image frames and multiple observer labels
Liam F Chalcroft, Jiongqi Qu, Sophie A Martin +8
When developing deep neural networks for segmenting intraoperative ultrasound images, several practical issues are encountered frequently, such as the presence of ultrasound frames…
Assisted Probe Positioning for Ultrasound Guided Radiotherapy Using Image Sequence Classification
Alexander Grimwood, Helen McNair, Yipeng Hu +3
Effective transperineal ultrasound image guidance in prostate external beam radiotherapy requires consistent alignment between probe and prostate at each session during patient set…