Generation of Realistic (in silico) Histopathologic Images Using Generative Models Based on Deep Neural Networks

被引:0
|
作者
Benhamida, Jamal [1 ]
Rajanna, Arjun [2 ]
Sirintrapun, S. Joseph
Fuchs, Thomas [2 ]
机构
[1] Mem Sloan Kettering, San Francisco, CA USA
[2] Mem Sloan Kettering Canc Ctr, 1275 York Ave, New York, NY 10021 USA
关键词
D O I
暂无
中图分类号
R-3 [医学研究方法]; R3 [基础医学];
学科分类号
1001 ;
摘要
1630
引用
收藏
页码:584 / 584
页数:1
相关论文
共 50 条
  • [1] Generation of Realistic (in silico) Histopathologic Images Using Generative Models Based on Deep Neural Networks
    Benhamida, Jamal
    Rajanna, Arjun
    Sirintrapun, S. Joseph
    Fuchs, Thomas
    MODERN PATHOLOGY, 2018, 31 : 584 - 584
  • [2] Realistic generation of diffusion-weighted magnetic resonance brain images with deep generative models
    Hirte, Alejandro Ungria
    Platscher, Moritz
    Joyce, Thomas
    Heit, Jeremy J.
    Tranvinh, Eric
    Federau, Christian
    MAGNETIC RESONANCE IMAGING, 2021, 81 : 60 - 66
  • [3] Generative Models for Fashion Industry using Deep Neural Networks
    Lomov, Ildar
    Makarov, Ilya
    2019 2ND INTERNATIONAL CONFERENCE ON COMPUTER APPLICATIONS & INFORMATION SECURITY (ICCAIS), 2019,
  • [4] Unsupervised Images Generation Based on Sloan Digital Sky Survey with Deep Convolutional Generative Neural Networks
    Zhang, Guanghua
    Wang, Fubao
    Duan, Weijun
    2018 10TH INTERNATIONAL CONFERENCE ON ADVANCED INFOCOMM TECHNOLOGY (ICAIT), 2018, : 167 - 173
  • [5] OPENING DEEP NEURAL NETWORKS WITH GENERATIVE MODELS
    Vendramini, Marcos
    Oliveira, Hugo
    Machado, Alexei
    dos Santos, Jefersson A.
    2021 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP), 2021, : 1314 - 1318
  • [6] Scenario Generation for Market Risk Models Using Generative Neural Networks
    Flaig, Solveig
    Junike, Gero
    RISKS, 2022, 10 (11)
  • [7] Generation of Realistic Navigation Paths for Web Site Testing Using Recurrent Neural Networks and Generative Adversarial Neural Networks
    Pavanetto, Silvio
    Brambilla, Marco
    WEB ENGINEERING, ICWE 2020, 2020, 12128 : 244 - 258
  • [8] SIMULATING PATHO-REALISTIC ULTRASOUND IMAGES USING DEEP GENERATIVE NETWORKS WITH ADVERSARIAL LEARNING
    Tom, Francis
    Sheet, Debdoot
    2018 IEEE 15TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI 2018), 2018, : 1174 - 1177
  • [9] Comparison of Deep Generative Models for the Generation of Handwritten Character Images
    Kirbiyik, Omer
    Simsar, Enis
    Cemgil, A. Taylan
    2019 27TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU), 2019,
  • [10] Generation method of pavement crack images based on deep convolutional generative adversarial networks
    Pei L.
    Sun Z.
    Sun J.
    Li W.
    Zhang H.
    Zhongnan Daxue Xuebao (Ziran Kexue Ban)/Journal of Central South University (Science and Technology), 2021, 52 (11): : 3899 - 3906