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Few Labeled Atlases are Necessary for Deep-Learning-Based Segmentation
v1v2v3v4 (latest)

Few Labeled Atlases are Necessary for Deep-Learning-Based Segmentation

13 August 2019
H. Lee
M. Sabuncu
Adrian Dalca
ArXiv (abs)PDFHTML

Papers citing "Few Labeled Atlases are Necessary for Deep-Learning-Based Segmentation"

5 / 5 papers shown
Multi-Atlas Segmentation and Spatial Alignment of the Human Embryo in
  First Trimester 3D Ultrasound
Multi-Atlas Segmentation and Spatial Alignment of the Human Embryo in First Trimester 3D UltrasoundMachine Learning for Biomedical Imaging (MLBI), 2022
W. Bastiaansen
M. Rousian
R. Steegers-Theunissen
W. Niessen
A. Koning
S. Klein
270
4
0
14 Feb 2022
Generative Adversarial Registration for Improved Conditional Deformable
  Templates
Generative Adversarial Registration for Improved Conditional Deformable TemplatesIEEE International Conference on Computer Vision (ICCV), 2021
Neel Dey
Mengwei Ren
Adrian Dalca
Guido Gerig
GANMedIm
275
42
0
07 May 2021
Atlas-ISTN: Joint Segmentation, Registration and Atlas Construction with
  Image-and-Spatial Transformer Networks
Atlas-ISTN: Joint Segmentation, Registration and Atlas Construction with Image-and-Spatial Transformer Networks
Matthew Sinclair
A. Schuh
K. Hahn
K. Petersen
Ying Bai
James Batten
M. Schaap
Ben Glocker
276
38
0
18 Dec 2020
An Auto-Encoder Strategy for Adaptive Image Segmentation
An Auto-Encoder Strategy for Adaptive Image SegmentationInternational Conference on Medical Imaging with Deep Learning (MIDL), 2020
Evan M. Yu
Juan Eugenio Iglesias
Adrian Dalca
M. Sabuncu
112
16
0
29 Apr 2020
SynthMorph: learning contrast-invariant registration without acquired
  images
SynthMorph: learning contrast-invariant registration without acquired images
Malte Hoffmann
Benjamin Billot
Douglas N. Greve
Juan Eugenio Iglesias
Bruce Fischl
Adrian Dalca
MedIm
464
239
0
21 Apr 2020
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