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Leveraging the Mahalanobis Distance to enhance Unsupervised Brain MRI
  Anomaly Detection

Leveraging the Mahalanobis Distance to enhance Unsupervised Brain MRI Anomaly Detection

17 July 2024
F. Behrendt
Debayan Bhattacharya
R. Mieling
Lennart Maack
Julia Kruger
R. Opfer
Alexander Schlaefer
ArXivPDFHTML

Papers citing "Leveraging the Mahalanobis Distance to enhance Unsupervised Brain MRI Anomaly Detection"

5 / 5 papers shown
Title
MAD-AD: Masked Diffusion for Unsupervised Brain Anomaly Detection
MAD-AD: Masked Diffusion for Unsupervised Brain Anomaly Detection
Farzad Beizaee
Gregory A. Lodygensky
Christian Desrosiers
Jose Dolz
DiffM
MedIm
37
0
0
24 Feb 2025
Patched Diffusion Models for Unsupervised Anomaly Detection in Brain MRI
Patched Diffusion Models for Unsupervised Anomaly Detection in Brain MRI
F. Behrendt
Debayan Bhattacharya
Julia Kruger
R. Opfer
Alexander Schlaefer
DiffM
MedIm
29
40
0
07 Mar 2023
Unsupervised Pathology Detection: A Deep Dive Into the State of the Art
Unsupervised Pathology Detection: A Deep Dive Into the State of the Art
I. Lagogiannis
Felix Meissen
Georgios Kaissis
Daniel Rueckert
OOD
83
18
0
01 Mar 2023
Anomaly Detection via Reverse Distillation from One-Class Embedding
Anomaly Detection via Reverse Distillation from One-Class Embedding
Hanqiu Deng
Xingyu Li
UQCV
106
448
0
26 Jan 2022
U-Net: Convolutional Networks for Biomedical Image Segmentation
U-Net: Convolutional Networks for Biomedical Image Segmentation
Olaf Ronneberger
Philipp Fischer
Thomas Brox
SSeg
3DV
288
75,800
0
18 May 2015
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