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A Survey of Crowdsourcing in Medical Image Analysis
v1v2 (latest)

A Survey of Crowdsourcing in Medical Image Analysis

25 February 2019
S. Ørting
Andrew Doyle
A. Hilten
Matthias Hirth
Oana Inel
C. Madan
Panagiotis Mavridis
Helen Spiers
Veronika Cheplygina
ArXiv (abs)PDFHTML

Papers citing "A Survey of Crowdsourcing in Medical Image Analysis"

16 / 16 papers shown
Title
Crowdsourced human-based computational approach for tagging peripheral blood smear sample images from Sickle Cell Disease patients using non-expert users
Crowdsourced human-based computational approach for tagging peripheral blood smear sample images from Sickle Cell Disease patients using non-expert users
José María Buades Rubio
Gabriel Moyà Alcover
Antoni Jaume-i-Capó
N. Petrovic
70
1
0
13 Jan 2025
How does self-supervised pretraining improve robustness against noisy
  labels across various medical image classification datasets?
How does self-supervised pretraining improve robustness against noisy labels across various medical image classification datasets?
Bidur Khanal
Binod Bhattarai
Bishesh Khanal
Cristian A. Linte
NoLa
50
1
0
15 Jan 2024
Augmenting Chest X-ray Datasets with Non-Expert Annotations
Augmenting Chest X-ray Datasets with Non-Expert Annotations
Veronika Cheplygina
Cathrine Damgaard
Dovile Juodelyte
Veronika Cheplygina
Amelia Jiménez-Sánchez
145
4
0
05 Sep 2023
Labeling instructions matter in biomedical image analysis
Labeling instructions matter in biomedical image analysis
Tim Radsch
Annika Reinke
V. Weru
M. Tizabi
Nicholas Schreck
A. Emre Kavur
Bunyamin Pekdemir
T. Ross
A. Kopp-Schneider
Lena Maier-Hein
77
57
0
20 Jul 2022
Terabyte-scale supervised 3D training and benchmarking dataset of the
  mouse kidney
Terabyte-scale supervised 3D training and benchmarking dataset of the mouse kidney
W. Kuo
D. Rossinelli
G. Schulz
R. Wenger
S. Hieber
B. Müller
V. Kurtcuoglu
56
9
0
04 Aug 2021
Label noise in segmentation networks : mitigation must deal with bias
Label noise in segmentation networks : mitigation must deal with bias
Eugene Vorontsov
Samuel Kadoury
NoLa
73
19
0
05 Jul 2021
NuCLS: A scalable crowdsourcing, deep learning approach and dataset for
  nucleus classification, localization and segmentation
NuCLS: A scalable crowdsourcing, deep learning approach and dataset for nucleus classification, localization and segmentation
M. Amgad
Lamees A. Atteya
Hagar Hussein
K. Mohammed
Ehab Hafiz
...
Critical Care
David Manthey
Atlanta
D. Neurology
Lurie Cancer Center
87
75
0
18 Feb 2021
Vessel-CAPTCHA: an efficient learning framework for vessel annotation
  and segmentation
Vessel-CAPTCHA: an efficient learning framework for vessel annotation and segmentation
Vien Ngoc Dang
Francesco Galati
Rosa Cortese
G. Giacomo
Viola Marconeto
Pratek Mathur
Karim Lekadir
Marco Lorenzi
F. Prados
Maria A. Zuluaga
MedIm
80
36
0
22 Jan 2021
Few-shot Medical Image Segmentation using a Global Correlation Network
  with Discriminative Embedding
Few-shot Medical Image Segmentation using a Global Correlation Network with Discriminative Embedding
Liyan Sun
Chenxin Li
Xinghao Ding
Yue Huang
Guisheng Wang
Yizhou Yu
86
120
0
10 Dec 2020
Crowdsourcing Airway Annotations in Chest Computed Tomography Images
Crowdsourcing Airway Annotations in Chest Computed Tomography Images
Veronika Cheplygina
A. Perez-Rovira
Wieying Kuo
H. Tiddens
Marleen de Bruijne
49
3
0
20 Nov 2020
Learning to Segment from Scribbles using Multi-scale Adversarial
  Attention Gates
Learning to Segment from Scribbles using Multi-scale Adversarial Attention Gates
Gabriele Valvano
Andrea Leo
Sotirios A. Tsaftaris
83
5
0
02 Jul 2020
EXACT: A collaboration toolset for algorithm-aided annotation of images
  with annotation version control
EXACT: A collaboration toolset for algorithm-aided annotation of images with annotation version control
Christian Marzahl
Marc Aubreville
C. Bertram
Jennifer K. Maier
Christian Bergler
Christine Kröger
J. Voigt
Katharina Breininger
R. Klopfleisch
Andreas Maier
59
33
0
30 Apr 2020
Are fast labeling methods reliable? A case study of computer-aided
  expert annotations on microscopy slides
Are fast labeling methods reliable? A case study of computer-aided expert annotations on microscopy slides
Christian Marzahl
C. Bertram
Marc Aubreville
Anne Petrick
Kristina Weiler
...
Alina Langenhagen
A. Jasensky
J. Voigt
R. Klopfleisch
Andreas Maier
49
16
0
13 Apr 2020
Learning to segment images with classification labels
Learning to segment images with classification labels
Ozan Ciga
Anne L. Martel
VLM
52
25
0
28 Dec 2019
Deep neural network models for computational histopathology: A survey
Deep neural network models for computational histopathology: A survey
C. Srinidhi
Ozan Ciga
Anne L. Martel
AI4CE
175
584
0
28 Dec 2019
Fooling the Crowd with Deep Learning-based Methods
Fooling the Crowd with Deep Learning-based Methods
Christian Marzahl
Marc Aubreville
C. Bertram
Stefan Gerlach
Jennifer K. Maier
J. Voigt
Jenny Hill
R. Klopfleisch
Andreas Maier
51
4
0
30 Nov 2019
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