469 citations · 682 across the 15 of their papers we have counts for
15 papers
Deep Joint Denoising and Detection for Enhanced Intracellular Particle Analysis
Yao Yao, Ihor Smal, Ilya Grigoriev +2
Reliable analysis of intracellular dynamic processes in time-lapse fluorescence microscopy images requires complete and accurate tracking of all small particles in all time frames…
FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare
Karim Lekadir, Aasa Feragen, Abdul Joseph Fofanah +117
Despite major advances in artificial intelligence (AI) for medicine and healthcare, the deployment and adoption of AI technologies remain limited in real-world clinical practice. I…
hist2RNA: An efficient deep learning architecture to predict gene expression from breast cancer histopathology images
Raktim Kumar Mondol, Ewan K. A. Millar, Peter H Graham +3
Gene expression can be used to subtype breast cancer with improved prediction of risk of recurrence and treatment responsiveness over that obtained using routine immunohistochemist…
Breast Cancer Histopathology Image based Gene Expression Prediction using Spatial Transcriptomics data and Deep Learning
Md Mamunur Rahaman, Ewan K. A. Millar, Erik Meijering
Tumour heterogeneity in breast cancer poses challenges in predicting outcome and response to therapy. Spatial transcriptomics technologies may address these challenges, as they pro…
Hybrid Dual Mean-Teacher Network With Double-Uncertainty Guidance for Semi-Supervised Segmentation of MRI Scans
Jiayi Zhu, Bart Bolsterlee, Brian V. Y. Chow +2
Semi-supervised learning has made significant progress in medical image segmentation. However, existing methods primarily utilize information acquired from a single dimensionality…
IKD+: Reliable Low Complexity Deep Models For Retinopathy Classification
Shreyas Bhat Brahmavar, Rohit Rajesh, Tirtharaj Dash +6
Deep neural network (DNN) models for retinopathy have estimated predictive accuracies in the mid-to-high 90%. However, the following aspects remain unaddressed: State-of-the-art mo…
Fully Elman Neural Network: A Novel Deep Recurrent Neural Network Optimized by an Improved Harris Hawks Algorithm for Classification of Pulmonary Arterial Wedge Pressure
Masoud Fetanat, Michael Stevens, Pankaj Jain +3
Heart failure (HF) is one of the most prevalent life-threatening cardiovascular diseases in which 6.5 million people are suffering in the USA and more than 23 million worldwide. Me…
MKIS-Net: A Light-Weight Multi-Kernel Network for Medical Image Segmentation
Tariq M. Khan, Muhammad Arsalan, Antonio Robles-Kelly +1
Image segmentation is an important task in medical imaging. It constitutes the backbone of a wide variety of clinical diagnostic methods, treatments, and computer-aided surgeries.…
Neural Network Compression by Joint Sparsity Promotion and Redundancy Reduction
Tariq M. Khan, Syed S. Naqvi, Antonio Robles-Kelly +1
Compression of convolutional neural network models has recently been dominated by pruning approaches. A class of previous works focuses solely on pruning the unimportant filters to…
From Nano to Macro: Overview of the IEEE Bio Image and Signal Processing Technical Committee
Selin Aviyente, Alejandro Frangi, Erik Meijering +6
The Bio Image and Signal Processing (BISP) Technical Committee (TC) of the IEEE Signal Processing Society (SPS) promotes activities within the broad technical field of biomedical i…
Metrics reloaded: Recommendations for image analysis validation
Lena Maier-Hein, Annika Reinke, Patrick Godau +71
Increasing evidence shows that flaws in machine learning (ML) algorithm validation are an underestimated global problem. Particularly in automatic biomedical image analysis, chosen…
Leveraging Image Complexity in Macro-Level Neural Network Design for Medical Image Segmentation
Tariq M. Khan, Syed S. Naqvi, Erik Meijering
Recent progress in encoder-decoder neural network architecture design has led to significant performance improvements in a wide range of medical image segmentation tasks. However,…
Adaptive Distributed Resampling Algorithm with Non-Proportional Allocation
Ömer Demirel, Ihor Smal, Wiro Niessen +2
The distributed resampling algorithm with proportional allocation (RNA) is key to implementing particle filtering applications on parallel computer systems. We extend the original…
Piecewise Constant Sequential Importance Sampling for Fast Particle Filtering
Ömer Demirel, Ihor Smal, Wiro J. Niessen +2
Particle filters are key algorithms for object tracking under non-linear, non-Gaussian dynamics. The high computational cost of particle filters, however, hampers their applicabili…
PPF - A Parallel Particle Filtering Library
Ömer Demirel, Ihor Smal, Wiro Niessen +2
We present the parallel particle filtering (PPF) software library, which enables hybrid shared-memory/distributed-memory parallelization of particle filtering (PF) algorithms combi…