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researcher

H. An

4 papers here

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

author position
  • middle author4

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • eess.IV3
  • physics.med-ph1
same name
  • H. An — 22 papers, h 25
  • H. An — 19 papers, h 33
  • H. An — 1 paper, h 17
  • H. An — 1 paper
  • H. An — 1 paper, h 19
  • H. An — 1 paper

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
20192022
most citedDeep Image Reconstruction using Unregistered Measurements without Groundtruth

4 citations · 5 across the 2 of their papers we have counts for

collaborators

4 papers

eess.IV2022★ 1 cited

Image Reconstruction for MRI using Deep CNN Priors Trained without Groundtruth

Weijie Gan, Cihat Eldeniz, Jiaming Liu +3

We propose a new plug-and-play priors (PnP) based MR image reconstruction method that systematically enforces data consistency while also exploiting deep-learning priors. Our prior…

eess.IV2020★ 4 cited

Deep Image Reconstruction using Unregistered Measurements without Groundtruth

Weijie Gan, Yu Sun, Cihat Eldeniz +3

One of the key limitations in conventional deep learning based image reconstruction is the need for registered pairs of training images containing a set of high-quality groundtruth…

eess.IV2019

RARE: Image Reconstruction using Deep Priors Learned without Ground Truth

Jiaming Liu, Yu Sun, Cihat Eldeniz +3

Regularization by denoising (RED) is an image reconstruction framework that uses an image denoiser as a prior. Recent work has shown the state-of-the-art performance of RED with le…

physics.med-ph2019

Bone Material Analogues for PET/MRI Phantoms

Dharshan Chandramohan, Peng Cao, Misung Han +6

Purpose: To develop bone material analogues that can be used in construction of phantoms for simultaneous PET/MRI systems. Methods: Plaster was used as the basis for the bone mater…

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