activity
20172022
most citedOne Network to Segment Them All: A General, Lightweight System for Accurate 3D Medical Image Segmentation

68 citations · 130 across the 7 of their papers we have counts for

collaborators
Showing 2020Show all

5 papers · 1 filter

cs.CV20201 cited

Multi-layered tensor networks for image classification

Raghavendra Selvan, Silas Ørting, Erik B Dam

The recently introduced locally orderless tensor network (LoTeNet) for supervised image classification uses matrix product state (MPS) operations on grids of transformed image patc…

cs.CV2020

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

Raghavendra Selvan, Silas Ørting, Erik B Dam

Tensor networks are factorisations of high rank tensors into networks of lower rank tensors and have primarily been used to analyse quantum many-body problems. Tensor networks have…

eess.IV2020

The International Workshop on Osteoarthritis Imaging Knee MRI Segmentation Challenge: A Multi-Institute Evaluation and Analysis Framework on a Standardized Dataset

Arjun D. Desai, Francesco Caliva, Claudia Iriondo +26

Purpose: To organize a knee MRI segmentation challenge for characterizing the semantic and clinical efficacy of automatic segmentation methods relevant for monitoring osteoarthriti…

eess.IV202045 cited

Lung Segmentation from Chest X-rays using Variational Data Imputation

Raghavendra Selvan, Erik B. Dam, Nicki S. Detlefsen +4

Pulmonary opacification is the inflammation in the lungs caused by many respiratory ailments, including the novel corona virus disease 2019 (COVID-19). Chest X-rays (CXRs) with suc…

cs.LG202010 cited

Tensor Networks for Medical Image Classification

Raghavendra Selvan, Erik B Dam

With the increasing adoption of machine learning tools like neural networks across several domains, interesting connections and comparisons to concepts from other domains are comin…