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Chen Qin

30 papers hereh-index 253.4k citations49 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author9
  • middle author19
  • last author1

Across the 29 of 30 papers where every author was matched, so the position is known.

fields
  • eess.IV21
  • cs.CV9
same name
  • Chen Qin — 9 papers, h 3
  • Chen Qin — 7 papers, h 7
  • Chen Qin — 6 papers, h 7
  • Chen Qin — 5 papers, h 1
  • Chen Qin — 4 papers, h 2
  • Chen Qin — 2 papers, h 0

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20172024
most citedDeep learning for cardiac image segmentation: A review

870 citations · 1k across the 29 of their papers we have counts for

collaborators
Showing 2020Show all

4 papers · 1 filter

eess.IV2020★ 2 cited

Deep Network Interpolation for Accelerated Parallel MR Image Reconstruction

Chen Qin, Jo Schlemper, Kerstin Hammernik +3

We present a deep network interpolation strategy for accelerated parallel MR image reconstruction. In particular, we examine the network interpolation in parameter space between a…

eess.IV2020★ 1 cited

Biomechanics-informed Neural Networks for Myocardial Motion Tracking in MRI

Chen Qin, Shuo Wang, Chen Chen +3

Image registration is an ill-posed inverse problem which often requires regularisation on the solution space. In contrast to most of the current approaches which impose explicit re…

eess.IV2020★ 17 cited

Deep Generative Model-based Quality Control for Cardiac MRI Segmentation

Shuo Wang, Giacomo Tarroni, Chen Qin +7

In recent years, convolutional neural networks have demonstrated promising performance in a variety of medical image segmentation tasks. However, when a trained segmentation model…

eess.IV2020★ 10 cited

Realistic Adversarial Data Augmentation for MR Image Segmentation

Chen Chen, Chen Qin, Huaqi Qiu +6

Neural network-based approaches can achieve high accuracy in various medical image segmentation tasks. However, they generally require large labelled datasets for supervised learni…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.