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Detecting Outliers with Poisson Image Interpolation

Detecting Outliers with Poisson Image Interpolation

6 July 2021
Jeremy Tan
Benjamin Hou
Thomas Day
J. Simpson
Daniel Rueckert
Bernhard Kainz
    MedIm
ArXiv (abs)PDFHTMLGithub (7★)

Papers citing "Detecting Outliers with Poisson Image Interpolation"

12 / 12 papers shown
Title
Guided Reconstruction with Conditioned Diffusion Models for Unsupervised Anomaly Detection in Brain MRIs
Guided Reconstruction with Conditioned Diffusion Models for Unsupervised Anomaly Detection in Brain MRIs
F. Behrendt
Debayan Bhattacharya
R. Mieling
Lennart Maack
Julia Kruger
R. Opfer
Alexander Schlaefer
DiffMMedIm
78
10
0
07 Dec 2023
Unsupervised Brain Anomaly Detection and Segmentation with Transformers
Unsupervised Brain Anomaly Detection and Segmentation with Transformers
W. H. Pinaya
Petru-Daniel Tudosiu
Robert J. Gray
G. Rees
P. Nachev
Sebastien Ourselin
M. Jorge Cardoso
ViTMedIm
66
61
0
23 Feb 2021
Anomaly detection through latent space restoration using
  vector-quantized variational autoencoders
Anomaly detection through latent space restoration using vector-quantized variational autoencoders
Sergio Naval Marimont
G. Tarroni
DRL
169
58
0
12 Dec 2020
Detecting Outliers with Foreign Patch Interpolation
Detecting Outliers with Foreign Patch Interpolation
Jeremy Tan
Benjamin Hou
James Batten
Huaqi Qiu
Bernhard Kainz
MedIm
56
49
0
09 Nov 2020
Pseudo-healthy synthesis with pathology disentanglement and adversarial
  learning
Pseudo-healthy synthesis with pathology disentanglement and adversarial learning
Tian Xia
A. Chartsias
Sotirios A. Tsaftaris
MedIm
44
39
0
20 Apr 2020
Momentum Contrast for Unsupervised Visual Representation Learning
Momentum Contrast for Unsupervised Visual Representation Learning
Kaiming He
Haoqi Fan
Yuxin Wu
Saining Xie
Ross B. Girshick
SSL
216
12,136
0
13 Nov 2019
Generating Diverse High-Fidelity Images with VQ-VAE-2
Generating Diverse High-Fidelity Images with VQ-VAE-2
Ali Razavi
Aaron van den Oord
Oriol Vinyals
DRLBDL
151
1,828
0
02 Jun 2019
Deep Neural Networks Improve Radiologists' Performance in Breast Cancer
  Screening
Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening
Nan Wu
Jason Phang
Jungkyu Park
Yiqiu Shen
Zhe Huang
...
S. G. Kim
Laura Heacock
Linda Moy
Kyunghyun Cho
Krzysztof J. Geras
MedIm
49
501
0
20 Mar 2019
Deep Anomaly Detection Using Geometric Transformations
Deep Anomaly Detection Using Geometric Transformations
I. Golan
Ran El-Yaniv
111
607
0
28 May 2018
mixup: Beyond Empirical Risk Minimization
mixup: Beyond Empirical Risk Minimization
Hongyi Zhang
Moustapha Cissé
Yann N. Dauphin
David Lopez-Paz
NoLa
316
9,811
0
25 Oct 2017
Wide Residual Networks
Wide Residual Networks
Sergey Zagoruyko
N. Komodakis
356
8,002
0
23 May 2016
Building a Framework for Predictive Science
Building a Framework for Predictive Science
Michael McKerns
Leif Strand
Tim Sullivan
Alta Fang
M. Aivazis
AI4CE
110
174
0
06 Feb 2012
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