ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2006.02569
  4. Cited By
Automated segmentation of retinal fluid volumes from structural and
  angiographic optical coherence tomography using deep learning

Automated segmentation of retinal fluid volumes from structural and angiographic optical coherence tomography using deep learning

3 June 2020
Yukun Guo
T. Hormel
Honglian Xiong
Jie Wang
T. Hwang
Yali Jia
ArXivPDFHTML

Papers citing "Automated segmentation of retinal fluid volumes from structural and angiographic optical coherence tomography using deep learning"

15 / 15 papers shown
Title
M2U-Net: Effective and Efficient Retinal Vessel Segmentation for
  Resource-Constrained Environments
M2U-Net: Effective and Efficient Retinal Vessel Segmentation for Resource-Constrained Environments
Tim Laibacher
Tillman Weyde
Sepehr Jalali
49
35
0
19 Nov 2018
Recurrent Residual Convolutional Neural Network based on U-Net (R2U-Net)
  for Medical Image Segmentation
Recurrent Residual Convolutional Neural Network based on U-Net (R2U-Net) for Medical Image Segmentation
Md. Zahangir Alom
Mahmudul Hasan
C. Yakopcic
T. Taha
V. Asari
SSeg
83
1,019
0
20 Feb 2018
Encoder-Decoder with Atrous Separable Convolution for Semantic Image
  Segmentation
Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation
Liang-Chieh Chen
Yukun Zhu
George Papandreou
Florian Schroff
Hartwig Adam
SSeg
432
13,132
0
07 Feb 2018
Cystoid macular edema segmentation of Optical Coherence Tomography
  images using fully convolutional neural networks and fully connected CRFs
Cystoid macular edema segmentation of Optical Coherence Tomography images using fully convolutional neural networks and fully connected CRFs
Fangliang Bai
M. Marques
S. Gibson
MedIm
23
11
0
15 Sep 2017
Pyramid Scene Parsing Network
Pyramid Scene Parsing Network
Hengshuang Zhao
Jianping Shi
Xiaojuan Qi
Xiaogang Wang
Jiaya Jia
VOS
SSeg
658
12,007
0
04 Dec 2016
The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for
  Semantic Segmentation
The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation
S. Jégou
M. Drozdzal
David Vazquez
Adriana Romero
Yoshua Bengio
SSeg
172
1,580
0
28 Nov 2016
RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic
  Segmentation
RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation
Guosheng Lin
Anton Milan
Chunhua Shen
Ian Reid
AI4TS
SSeg
253
2,848
0
20 Nov 2016
DeepLab: Semantic Image Segmentation with Deep Convolutional Nets,
  Atrous Convolution, and Fully Connected CRFs
DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs
Liang-Chieh Chen
George Papandreou
Iasonas Kokkinos
Kevin Patrick Murphy
Alan Yuille
SSeg
242
18,232
0
02 Jun 2016
Fully Convolutional Networks for Semantic Segmentation
Fully Convolutional Networks for Semantic Segmentation
Evan Shelhamer
Jonathan Long
Trevor Darrell
VOS
SSeg
738
37,846
0
20 May 2016
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
2.2K
193,878
0
10 Dec 2015
Multi-Scale Context Aggregation by Dilated Convolutions
Multi-Scale Context Aggregation by Dilated Convolutions
Feng Yu
V. Koltun
SSeg
268
8,442
0
23 Nov 2015
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image
  Segmentation
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
Vijay Badrinarayanan
Alex Kendall
R. Cipolla
SSeg
1.1K
15,798
0
02 Nov 2015
U-Net: Convolutional Networks for Biomedical Image Segmentation
U-Net: Convolutional Networks for Biomedical Image Segmentation
Olaf Ronneberger
Philipp Fischer
Thomas Brox
SSeg
3DV
1.8K
77,133
0
18 May 2015
How transferable are features in deep neural networks?
How transferable are features in deep neural networks?
J. Yosinski
Jeff Clune
Yoshua Bengio
Hod Lipson
OOD
231
8,336
0
06 Nov 2014
Going Deeper with Convolutions
Going Deeper with Convolutions
Christian Szegedy
Wei Liu
Yangqing Jia
P. Sermanet
Scott E. Reed
Dragomir Anguelov
D. Erhan
Vincent Vanhoucke
Andrew Rabinovich
460
43,649
0
17 Sep 2014
1