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Segmenting two-dimensional structures with strided tensor networks


Feb 13, 2021
Raghavendra Selvan, Erik B Dam, Jens Petersen

* Accepted to be presented at the 27th international conference on Information Processing in Medical Imaging (IPMI-2021), Bornholm, Denmark. Source code at https://github.com/raghavian/strided-tenet 

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Dynamic $β$-VAEs for quantifying biodiversity by clustering optically recorded insect signals


Feb 10, 2021
Klas Rydhmer, Raghavendra Selvan

* 9 pages, 6 figures 

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Multi-layered tensor networks for image classification


Nov 13, 2020
Raghavendra Selvan, Silas Ørting, Erik B Dam

* 6 pages. Accepted to the First Workshop on Quantum Tensor Networks in Machine Learning. In conjunction with 34th NeurIPS, 2020. Source code at https://github.com/raghavian/mltn 

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Locally orderless tensor networks for classifying two- and three-dimensional medical images


Sep 25, 2020
Raghavendra Selvan, Silas Ørting, Erik B Dam

* Source code will be available at https://github.com/raghavian/LoTeNet_pytorch/ 

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Carbontracker: Tracking and Predicting the Carbon Footprint of Training Deep Learning Models


Jul 06, 2020
Lasse F. Wolff Anthony, Benjamin Kanding, Raghavendra Selvan

* Accepted to be presented at the ICML Workshop on "Challenges in Deploying and monitoring Machine Learning Systems", 2020. Source code at this link https://github.com/lfwa/carbontracker/ 

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Uncertainty quantification in medical image segmentation with Normalizing Flows


Jun 04, 2020
Raghavendra Selvan, Frederik Faye, Jon Middleton, Akshay Pai

* 12 pages 

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Lung Segmentation from Chest X-rays using Variational Data Imputation


May 20, 2020
Raghavendra Selvan, Erik B. Dam, Sofus Rischel, Kaining Sheng, Mads Nielsen, Akshay Pai

* Source code, training data and the trained models are available here: https://github.com/raghavian/lungVAE/ 

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Tensor Networks for Medical Image Classification


Apr 21, 2020
Raghavendra Selvan, Erik B Dam

* Accepted for publication at International Conference on Medical Imaging with Deep Learning (MIDL), 2020. Reviews on Openreview here: https://openreview.net/forum?id=jjk6bxk07G 

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A joint 3D UNet-Graph Neural Network-based method for Airway Segmentation from chest CTs


Aug 22, 2019
Antonio Garcia-Uceda Juarez, Raghavendra Selvan, Zaigham Saghir, Marleen de Bruijne


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Segmentation of Roots in Soil with U-Net


Mar 18, 2019
Abraham George Smith, Jens Petersen, Raghavendra Selvan, Camilla Ruø Rasmussen


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Graph Refinement based Tree Extraction using Mean-Field Networks and Graph Neural Networks


Nov 21, 2018
Raghavendra Selvan, Thomas Kipf, Max Welling, Jesper H Pedersen, Jens Petersen, Marleen de Bruijne

* 10 pages. Journal preprint 

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Extracting Tree-structures in CT data by Tracking Multiple Statistically Ranked Hypotheses


Jun 23, 2018
Raghavendra Selvan, Jens Petersen, Jesper H Pedersen, Marleen de Bruijne

* 8 pages 

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Extraction of Airways using Graph Neural Networks


Apr 12, 2018
Raghavendra Selvan, Thomas Kipf, Max Welling, Jesper H. Pedersen, Jens Petersen, Marleen de Bruijne

* Extended Abstract submitted to MIDL, 2018. 3 pages 

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Mean Field Network based Graph Refinement with application to Airway Tree Extraction


Apr 10, 2018
Raghavendra Selvan, Max Welling, Jesper H. Pedersen, Jens Petersen, Marleen de Bruijne

* 10 pages. Preprint 

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Extraction of Airways with Probabilistic State-space Models and Bayesian Smoothing


Aug 07, 2017
Raghavendra Selvan, Jens Petersen, Jesper H. Pedersen, Marleen de Bruijne

* 10 pages. Pre-print of the paper accepted at Workshop on Graphs in Biomedical Image Analysis. MICCAI 2017. Quebec City 

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Extraction of airway trees using multiple hypothesis tracking and template matching


Nov 24, 2016
Raghavendra Selvan, Jens Petersen, Jesper H. Pedersen, Marleen de Bruijne

* 12 pages. Presented at the MICCAI Pulmonary Image Analysis Workshop, Athens, Greece, 2016 

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