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08/16/2023
Prediction of post-radiotherapy recurrence volumes in head and neck squamous cell carcinoma using 3D U-Net segmentation
Locoregional recurrences (LRR) are still a frequent site of treatment fa...
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04/10/2023
Localise to segment: crop to improve organ at risk segmentation accuracy
Increased organ at risk segmentation accuracy is required to reduce cost...
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04/09/2023
Transformer Utilization in Medical Image Segmentation Networks
Owing to success in the data-rich domain of natural images, Transformers...
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03/17/2023
MedNeXt: Transformer-driven Scaling of ConvNets for Medical Image Segmentation
There has been exploding interest in embracing Transformer-based archite...
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01/13/2023
Neural Image Compression with a Diffusion-Based Decoder
Diffusion probabilistic models have recently achieved remarkable success...
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01/13/2023
Explicit Temporal Embedding in Deep Generative Latent Models for Longitudinal Medical Image Synthesis
Medical imaging plays a vital role in modern diagnostics and treatment. ...
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01/05/2023
CRADL: Contrastive Representations for Unsupervised Anomaly Detection and Localization
Unsupervised anomaly detection in medical imaging aims to detect and loc...
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07/20/2022
Interpreting Latent Spaces of Generative Models for Medical Images using Unsupervised Methods
Generative models such as Generative Adversarial Networks (GANs) and Var...
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09/15/2021
Patch-based medical image segmentation using Quantum Tensor Networks
Tensor networks are efficient factorisations of high dimensional tensors...
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06/23/2021
Continuous-Time Deep Glioma Growth Models
The ability to estimate how a tumor might evolve in the future could hav...
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06/22/2021
RootPainter3D: Interactive-machine-learning enables rapid and accurate contouring for radiotherapy
Organ-at-risk contouring is still a bottleneck in radiotherapy, with man...
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06/09/2021
GP-ConvCNP: Better Generalization for Convolutional Conditional Neural Processes on Time Series Data
Neural Processes (NPs) are a family of conditional generative models tha...
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04/12/2021
Common Limitations of Image Processing Metrics: A Picture Story
While the importance of automatic image analysis is increasing at an eno...
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02/13/2021
Segmenting two-dimensional structures with strided tensor networks
Tensor networks provide an efficient approximation of operations involvi...
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11/28/2019
A Case for the Score: Identifying Image Anomalies using Variational Autoencoder Gradients
Through training on unlabeled data, anomaly detection has the potential ...
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11/27/2019
High- and Low-level image component decomposition using VAEs for improved reconstruction and anomaly detection
Variational Auto-Encoders have often been used for unsupervised pretrain...
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07/09/2019
Deep Probabilistic Modeling of Glioma Growth
Existing approaches to modeling the dynamics of brain tumor growth, spec...
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07/04/2019
Unsupervised Anomaly Localization using Variational Auto-Encoders
An assumption-free automatic check of medical images for potentially ove...
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04/17/2019
nnU-Net: Breaking the Spell on Successful Medical Image Segmentation
Fueled by the diversity of datasets, semantic segmentation is a popular ...
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03/11/2019
A cross-center smoothness prior for variational Bayesian brain tissue segmentation
Suppose one is faced with the challenge of tissue segmentation in MR ima...
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02/28/2019
Segmentation of Roots in Soil with U-Net
Plant root research can provide a way to attain stress-tolerant crops th...
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12/14/2018
Context-encoding Variational Autoencoder for Unsupervised Anomaly Detection
Unsupervised learning can leverage large-scale data sources without the ...
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11/21/2018
Graph Refinement based Tree Extraction using Mean-Field Networks and Graph Neural Networks
Graph refinement, or the task of obtaining subgraphs of interest from ov...
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10/17/2018
Learning to quantify emphysema extent: What labels do we need?
Accurate assessment of pulmonary emphysema is crucial to assess disease ...
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09/27/2018
nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation
The U-Net was presented in 2015. With its straight-forward and successfu...
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06/23/2018
Extracting Tree-structures in CT data by Tracking Multiple Statistically Ranked Hypotheses
In this work, we adapt a method based on multiple hypothesis tracking (M...
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06/19/2018
Feature learning based on visual similarity triplets in medical image analysis: A case study of emphysema in chest CT scans
Supervised feature learning using convolutional neural networks (CNNs) c...
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04/12/2018
Extraction of Airways using Graph Neural Networks
We present extraction of tree structures, such as airways, from image da...
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04/10/2018
Mean Field Network based Graph Refinement with application to Airway Tree Extraction
We present tree extraction in 3D images as a graph refinement task, of o...
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08/07/2017
Extraction of Airways with Probabilistic State-space Models and Bayesian Smoothing
Segmenting tree structures is common in several image processing applica...
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11/24/2016
Extraction of airway trees using multiple hypothesis tracking and template matching
Knowledge of airway tree morphology has important clinical applications ...
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03/29/2013