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

22 May 2020

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 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 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 Liangrui Pan Zhichao Feng Shaoliang Peng AI4CE 76 7 0 31 May 2022
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 Julio Silva-Rodríguez Adrián Colomer Valery Naranjo 92 43 0 21 May 2021