172 citations · 195 across the 12 of their papers we have counts for
12 papers
Parallel Watershed Partitioning: GPU-Based Hierarchical Image Segmentation
Varduhi Yeghiazaryan, Yeva Gabrielyan, Irina Voiculescu
Many image processing applications rely on partitioning an image into disjoint regions whose pixels are 'similar.' The watershed and waterfall transforms are established mathematic…
Infant hip screening using multi-class ultrasound scan segmentation
Andrew Stamper, Abhinav Singh, James McCouat +1
Developmental dysplasia of the hip (DDH) is a condition in infants where the femoral head is incorrectly located in the hip joint. We propose a deep learning algorithm for segmenti…
Triple-View Feature Learning for Medical Image Segmentation
Ziyang Wang, Irina Voiculescu
Deep learning models, e.g. supervised Encoder-Decoder style networks, exhibit promising performance in medical image segmentation, but come with a high labelling cost. We propose T…
Learning Underrepresented Classes from Decentralized Partially Labeled Medical Images
Nanqing Dong, Michael Kampffmeyer, Irina Voiculescu
Using decentralized data for federated training is one promising emerging research direction for alleviating data scarcity in the medical domain. However, in contrast to large-scal…
Revisiting Vicinal Risk Minimization for Partially Supervised Multi-Label Classification Under Data Scarcity
Nanqing Dong, Jiayi Wang, Irina Voiculescu
Due to the high human cost of annotation, it is non-trivial to curate a large-scale medical dataset that is fully labeled for all classes of interest. Instead, it would be convenie…
Federated Contrastive Learning for Decentralized Unlabeled Medical Images
Nanqing Dong, Irina Voiculescu
A label-efficient paradigm in computer vision is based on self-supervised contrastive pre-training on unlabeled data followed by fine-tuning with a small number of labels. Making p…
Negational Symmetry of Quantum Neural Networks for Binary Pattern Classification
Nanqing Dong, Michael Kampffmeyer, Irina Voiculescu +1
Entanglement is a physical phenomenon, which has fueled recent successes of quantum algorithms. Although quantum neural networks (QNNs) have shown promising results in solving simp…
Towards Robust Partially Supervised Multi-Structure Medical Image Segmentation on Small-Scale Data
Nanqing Dong, Michael Kampffmeyer, Xiaodan Liang +3
The data-driven nature of deep learning (DL) models for semantic segmentation requires a large number of pixel-level annotations. However, large-scale and fully labeled medical dat…
Deep learning for detection and segmentation of artefact and disease instances in gastrointestinal endoscopy
Sharib Ali, Mariia Dmitrieva, Noha Ghatwary +34
The Endoscopy Computer Vision Challenge (EndoCV) is a crowd-sourcing initiative to address eminent problems in developing reliable computer aided detection and diagnosis endoscopy…
RAR-U-Net: a Residual Encoder to Attention Decoder by Residual Connections Framework for Spine Segmentation under Noisy Labels
Ziyang Wang, Zhengdong Zhang, Irina Voiculescu
Segmentation algorithms for medical images are widely studied for various clinical and research purposes. In this paper, we propose a new and efficient method for medical image seg…
A Single RGB Camera Based Gait Analysis with a Mobile Tele-Robot for Healthcare
Ziyang Wang
With the increasing awareness of high-quality life, there is a growing need for health monitoring devices running robust algorithms in home environment. Health monitoring technolog…
Deep Learning in Medical Ultrasound Image Segmentation: a Review
Ziyang Wang
Applying machine learning technologies, especially deep learning, into medical image segmentation is being widely studied because of its state-of-the-art performance and results. I…