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Selective Synthetic Augmentation with HistoGAN for Improved
  Histopathology Image Classification

Selective Synthetic Augmentation with HistoGAN for Improved Histopathology Image Classification

10 November 2021
Yuan Xue
Jiarong Ye
Qianying Zhou
L. R. Long
Sameer Kiran Antani
Z. Xue
Carl Cornwell
R. Zaino
K. Cheng
Xiaolei Huang
    MedIm
ArXivPDFHTML

Papers citing "Selective Synthetic Augmentation with HistoGAN for Improved Histopathology Image Classification"

14 / 14 papers shown
Title
Method and Software Tool for Generating Artificial Databases of
  Biomedical Images Based on Deep Neural Networks
Method and Software Tool for Generating Artificial Databases of Biomedical Images Based on Deep Neural Networks
O. Berezsky
Petro B. Liashchynskyi
O. Pitsun
G. Melnyk
GAN
MedIm
29
0
0
25 May 2024
Two-stage Cytopathological Image Synthesis for Augmenting Cervical
  Abnormality Screening
Two-stage Cytopathological Image Synthesis for Augmenting Cervical Abnormality Screening
Zhenrong Shen
Manman Fei
Xin Wang
Jiangdong Cai
Sheng Wang
Lichi Zhang
Qian Wang
MedIm
34
0
0
22 Feb 2024
Domain Generalization in Computational Pathology: Survey and Guidelines
Domain Generalization in Computational Pathology: Survey and Guidelines
Mostafa Jahanifar
M. Raza
Kesi Xu
T. Vuong
R. Jewsbury
...
Neda Zamanitajeddin
Jin Tae Kwak
S. Raza
F. Minhas
Nasir M. Rajpoot
OOD
28
17
0
30 Oct 2023
Adaptive Input-image Normalization for Solving the Mode Collapse Problem
  in GAN-based X-ray Images
Adaptive Input-image Normalization for Solving the Mode Collapse Problem in GAN-based X-ray Images
Muhammad Muneeb Saad
M. H. Rehmani
Ruairi O'Reilly
MedIm
GAN
24
1
0
21 Sep 2023
CellGAN: Conditional Cervical Cell Synthesis for Augmenting
  Cytopathological Image Classification
CellGAN: Conditional Cervical Cell Synthesis for Augmenting Cytopathological Image Classification
Zhenrong Shen
Mao-Hong Cao
Sheng Wang
Lichi Zhang
Qian Wang
MedIm
15
7
0
12 Jul 2023
Data Efficient Contrastive Learning in Histopathology using Active
  Sampling
Data Efficient Contrastive Learning in Histopathology using Active Sampling
Tahsin Reasat
David S. Smith
MedIm
18
0
0
28 Mar 2023
NASDM: Nuclei-Aware Semantic Histopathology Image Generation Using
  Diffusion Models
NASDM: Nuclei-Aware Semantic Histopathology Image Generation Using Diffusion Models
A. Shrivastava
P. T. Fletcher
DiffM
MedIm
19
22
0
20 Mar 2023
HistoStarGAN: A Unified Approach to Stain Normalisation, Stain Transfer
  and Stain Invariant Segmentation in Renal Histopathology
HistoStarGAN: A Unified Approach to Stain Normalisation, Stain Transfer and Stain Invariant Segmentation in Renal Histopathology
Jelica Vasiljević
Friedrich Feuerhake
Cédric Wemmert
T. Lampert
MedIm
43
3
0
18 Oct 2022
Automated segmentation and morphological characterization of placental
  histology images based on a single labeled image
Automated segmentation and morphological characterization of placental histology images based on a single labeled image
A. Rabbani
M. Babaei
M. Gharib
15
1
0
07 Oct 2022
SIAN: Style-Guided Instance-Adaptive Normalization for Multi-Organ
  Histopathology Image Synthesis
SIAN: Style-Guided Instance-Adaptive Normalization for Multi-Organ Histopathology Image Synthesis
Haotian Wang
Min Xian
Aleksandar Vakanski
Bryar Shareef
MedIm
37
6
0
02 Sep 2022
A Multi-attribute Controllable Generative Model for Histopathology Image
  Synthesis
A Multi-attribute Controllable Generative Model for Histopathology Image Synthesis
Jiarong Ye
Yuan Xue
Peter Liu
R. Zaino
K. Cheng
Xiaolei Huang
MedIm
24
7
0
10 Nov 2021
PDBL: Improving Histopathological Tissue Classification with
  Plug-and-Play Pyramidal Deep-Broad Learning
PDBL: Improving Histopathological Tissue Classification with Plug-and-Play Pyramidal Deep-Broad Learning
Jiatai Lin
Guoqiang Han
Xipeng Pan
Hao Chen
Danyi Li
...
Haiming Li
C. Liang
Li Liang
Zaiyi Liu
Chu Han
22
33
0
04 Nov 2021
Conditional Image Synthesis With Auxiliary Classifier GANs
Conditional Image Synthesis With Auxiliary Classifier GANs
Augustus Odena
C. Olah
Jonathon Shlens
GAN
238
3,190
0
30 Oct 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
285
9,136
0
06 Jun 2015
1