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CT-To-MR Conditional Generative Adversarial Networks for Ischemic Stroke Lesion Segmentation

Infarcted brain tissue resulting from acute stroke readily shows up as h...
04/30/2019 ∙ by Jonathan Rubin, et al. ∙ 18 ∙ share

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An Adaptive Intelligence Algorithm for Undersampled Knee MRI Reconstruction: Application to the 2019 fastMRI Challenge

Adaptive intelligence aims at empowering machine learning techniques wit...
04/15/2020 ∙ by Nicola Pezzotti, et al. ∙ 11 ∙ share

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3D medical image segmentation with labeled and unlabeled data using autoencoders at the example of liver segmentation in CT images

Automatic segmentation of anatomical structures with convolutional neura...
03/17/2020 ∙ by Cheryl Sital, et al. ∙ 7 ∙ share

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Spatial sensitivity analysis for urban land use prediction with physics-constrained conditional generative adversarial networks

Accurately forecasting urban development and its environmental and clima...
07/22/2019 ∙ by Adrian Albert, et al. ∙ 5 ∙ share

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Towards an automated method based on Iterated Local Search optimization for tuning the parameters of Support Vector Machines

We provide preliminary details and formulation of an optimization strate...
07/11/2017 ∙ by Sergio Consoli, et al. ∙ 0 ∙ share

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Generating Time-Based Label Refinements to Discover More Precise Process Models

Process mining is a research field focused on the analysis of event data...
05/25/2017 ∙ by Niek Tax, et al. ∙ 0 ∙ share

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Mining Process Model Descriptions of Daily Life through Event Abstraction

Process mining techniques focus on extracting insight in processes from ...
05/25/2017 ∙ by Niek Tax, et al. ∙ 0 ∙ share

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An Ensemble Boosting Model for Predicting Transfer to the Pediatric Intensive Care Unit

Our work focuses on the problem of predicting the transfer of pediatric ...
07/16/2017 ∙ by Jonathan Rubin, et al. ∙ 0 ∙ share

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Can Pretrained Neural Networks Detect Anatomy?

Convolutional neural networks demonstrated outstanding empirical results...
12/18/2015 ∙ by Vlado Menkovski, et al. ∙ 0 ∙ share

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Recognizing Abnormal Heart Sounds Using Deep Learning

The work presented here applies deep learning to the task of automated c...
07/14/2017 ∙ by Jonathan Rubin, et al. ∙ 0 ∙ share

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Design and Processing of Invertible Orientation Scores of 3D Images for Enhancement of Complex Vasculature

The enhancement and detection of elongated structures in noisy image dat...
07/07/2017 ∙ by M. H. J. Janssen, et al. ∙ 0 ∙ share

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Heuristic Approaches for Generating Local Process Models through Log Projections

Local Process Model (LPM) discovery is focused on the mining of a set of...
10/10/2016 ∙ by Niek Tax, et al. ∙ 0 ∙ share

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On Generation of Time-based Label Refinements

Process mining is a research field focused on the analysis of event data...
09/12/2016 ∙ by Niek Tax, et al. ∙ 0 ∙ share

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Deeply-Supervised CNN for Prostate Segmentation

Prostate segmentation from Magnetic Resonance (MR) images plays an impor...
03/22/2017 ∙ by Qikui Zhu, et al. ∙ 0 ∙ share

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Multiscale Event Detection in Social Media

Event detection has been one of the most important research topics in so...
04/25/2014 ∙ by Xiaowen Dong, et al. ∙ 0 ∙ share

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Condensed Memory Networks for Clinical Diagnostic Inferencing

Diagnosis of a clinical condition is a challenging task, which often req...
12/06/2016 ∙ by Aaditya Prakash, et al. ∙ 0 ∙ share

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Neural Paraphrase Generation with Stacked Residual LSTM Networks

In this paper, we propose a novel neural approach for paraphrase generat...
10/10/2016 ∙ by Aaditya Prakash, et al. ∙ 0 ∙ share

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A Data-Driven Approach for Semantic Role Labeling from Induced Grammar Structures in Language

Semantic roles play an important role in extracting knowledge from text....
06/20/2016 ∙ by Vivek Datla, et al. ∙ 0 ∙ share

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Personalized Driver Stress Detection with Multi-task Neural Networks using Physiological Signals

Stress can be seen as a physiological response to everyday emotional, me...
11/15/2017 ∙ by Aaqib Saeed, et al. ∙ 0 ∙ share

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Designing virus-resistant, high-performance networks: a game-formation approach

Designing an optimal network topology while balancing multiple, possibly...
08/19/2017 ∙ by Stojan Trajanovski, et al. ∙ 0 ∙ share

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DR-BiLSTM: Dependent Reading Bidirectional LSTM for Natural Language Inference

We present a novel deep learning architecture to address the natural lan...
02/15/2018 ∙ by Reza Ghaeini, et al. ∙ 0 ∙ share

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Large Scale Automated Reading of Frontal and Lateral Chest X-Rays using Dual Convolutional Neural Networks

The MIMIC-CXR dataset is (to date) the largest publicly released chest x...
04/20/2018 ∙ by Jonathan Rubin, et al. ∙ 0 ∙ share

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Maximum weight spectrum codes with reduced length

A q-ary linear code of dimension k is called a maximum weight spectrum (...
06/14/2018 ∙ by Gérard D. Cohen, et al. ∙ 0 ∙ share

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Minimum Labelling bi-Connectivity

A labelled, undirected graph is a graph whose edges have assigned labels...
07/02/2018 ∙ by Josè Andrès Moreno Pèrez, et al. ∙ 0 ∙ share

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Online Heart Rate Prediction using Acceleration from a Wrist Worn Wearable

In this paper we study the prediction of heart rate from acceleration us...
06/25/2018 ∙ by Ryan McConville, et al. ∙ 0 ∙ share

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Learning behavioral context recognition with multi-stream temporal convolutional networks

Smart devices of everyday use (such as smartphones and wearables) are in...
08/27/2018 ∙ by Aaqib Saeed, et al. ∙ 0 ∙ share

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Patient Subtyping with Disease Progression and Irregular Observation Trajectories

Patient subtyping based on temporal observations can lead to significant...
10/21/2018 ∙ by Nikhil Galagali, et al. ∙ 0 ∙ share

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Clinical Concept Extraction with Contextual Word Embedding

Automatic extraction of clinical concepts is an essential step for turni...
10/24/2018 ∙ by Henghui Zhu, et al. ∙ 0 ∙ share

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Ischemic Stroke Lesion Segmentation in CT Perfusion Scans using Pyramid Pooling and Focal Loss

We present a fully convolutional neural network for segmenting ischemic ...
11/02/2018 ∙ by S. Mazdak Abulnaga, et al. ∙ 0 ∙ share

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Evolutionary Construction of Convolutional Neural Networks

Neuro-Evolution is a field of study that has recently gained significant...
01/02/2019 ∙ by Marijn van Knippenberg, et al. ∙ 0 ∙ share

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Learning a sparse database for patch-based medical image segmentation

We introduce a functional for the learning of an optimal database for pa...
06/25/2019 ∙ by Moti Freiman, et al. ∙ 0 ∙ share

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Deep learning-based prediction of kinetic parameters from myocardial perfusion MRI

The quantification of myocardial perfusion MRI has the potential to prov...
07/27/2019 ∙ by Cian M. Scannell, et al. ∙ 0 ∙ share

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Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging

Limitations on bandwidth and power consumption impose strict bounds on d...
08/15/2019 ∙ by Iris A. M. Huijben, et al. ∙ 0 ∙ share

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Perceptual Image Anomaly Detection

We present a novel method for image anomaly detection, where algorithms ...
09/12/2019 ∙ by Nina Tuluptceva, et al. ∙ 0 ∙ share

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Continual Learning for Domain Adaptation in Chest X-ray Classification

Over the last years, Deep Learning has been successfully applied to a br...
01/16/2020 ∙ by Matthias Lenga, et al. ∙ 0 ∙ share

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Service Selection using Predictive Models and Monte-Carlo Tree Search

This article proposes a method for automated service selection to improv...
02/12/2020 ∙ by Cliff Laschet, et al. ∙ 0 ∙ share

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4D Semantic Cardiac Magnetic Resonance Image Synthesis on XCAT Anatomical Model

We propose a hybrid controllable image generation method to synthesize a...
02/17/2020 ∙ by Samaneh Abbasi-Sureshjani, et al. ∙ 0 ∙ share

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Towards Ultrafast MRI via Extreme k-Space Undersampling and Superresolution

We went below the MRI acceleration factors (a.k.a., k-space undersamplin...
03/04/2021 ∙ by Aleksandr Belov, et al. ∙ 0 ∙ share

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