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Gleason Grading of Histology Prostate Images through Semantic Segmentation via Residual U-Net

Gleason Grading of Histology Prostate Images through Semantic Segmentation via Residual U-Net

Amartya Kalapahar
Julio Silva-Rodríguez
Adrián Colomer
Fernando López-Mir
Valery Naranjo
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Papers citing "Gleason Grading of Histology Prostate Images through Semantic Segmentation via Residual U-Net"

5 / 5 papers shown
Title
Self-supervised learning of a tailored Convolutional Auto Encoder for histopathological prostate grading
Self-supervised learning of a tailored Convolutional Auto Encoder for histopathological prostate grading
Zahra Tabatabaei
Adrián Colomer
K. Engan
Javier Oliver
Valery Naranjo
MedIm
41
4
0
21 Mar 2023
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
30
1
0
07 Oct 2022
A review of machine learning approaches, challenges and prospects for computational tumor pathology
A review of machine learning approaches, challenges and prospects for computational tumor pathology
Liangrui Pan
Zhichao Feng
Shaoliang Peng
AI4CE
76
7
0
31 May 2022
Acoustic Echo Cancellation using Residual U-Nets
Acoustic Echo Cancellation using Residual U-Nets
J. Silva-Rodríguez
Manuel F. Dolz
M. Ferrer
Adrián Castelló
V. Naranjo
G. Piñero
89
2
0
20 Sep 2021
WeGleNet: A Weakly-Supervised Convolutional Neural Network for the Semantic Segmentation of Gleason Grades in Prostate Histology Images
WeGleNet: A Weakly-Supervised Convolutional Neural Network for the Semantic Segmentation of Gleason Grades in Prostate Histology Images
Julio Silva-Rodríguez
Adrián Colomer
Valery Naranjo
92
43
0
21 May 2021