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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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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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Deep Probabilistic Modeling of Glioma Growth
Existing approaches to modeling the dynamics of brain tumor growth, spec...
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Unsupervised Anomaly Localization using Variational Auto-Encoders
An assumption-free automatic check of medical images for potentially ove...
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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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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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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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Context-encoding Variational Autoencoder for Unsupervised Anomaly Detection
Unsupervised learning can leverage large-scale data sources without the ...
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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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Learning to quantify emphysema extent: What labels do we need?
Accurate assessment of pulmonary emphysema is crucial to assess disease ...
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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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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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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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Extraction of Airways using Graph Neural Networks
We present extraction of tree structures, such as airways, from image da...
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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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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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Extraction of airway trees using multiple hypothesis tracking and template matching
Knowledge of airway tree morphology has important clinical applications ...
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Geometric tree kernels: Classification of COPD from airway tree geometry
Methodological contributions: This paper introduces a family of kernels ...
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