Meningioma segmentation in T1-weighted MRI leveraging global context and attention mechanisms

19 January 2021

Papers citing "Meningioma segmentation in T1-weighted MRI leveraging global context and attention mechanisms"

7 / 7 papers shown

Title
Segmentation of glioblastomas in early post-operative multi-modal MRI with deep neural networks Ragnhild Holden Helland Alexandros Ferles André Pedersen I. Kommers H. Ardon ... O. Solheim P. D. W. Hamer Ingerid Reinertsen R. Eijgelaar D. Bouget 19 16 0 18 Apr 2023
Localise to segment: crop to improve organ at risk segmentation accuracy Abraham George Smith Denis Kutnár I. Vogelius S. Darkner Jens Petersen SSeg 25 2 0 10 Apr 2023
Preoperative brain tumor imaging: models and software for segmentation and standardized reporting D. Bouget André Pedersen A. Jakola V. Kavouridis K. Emblem ... M. Witte A. Zwinderman P. D. W. Hamer O. Solheim Ingerid Reinertsen 26 21 0 29 Apr 2022
Mediastinal lymph nodes segmentation using 3D convolutional neural network ensembles and anatomical priors guiding D. Bouget André Pedersen J. Vanel H. O. Leira T. Langø 18 27 0 11 Feb 2021
Brain Tumor Segmentation using an Ensemble of 3D U-Nets and Overall Survival Prediction using Radiomic Features Xue Feng Nicholas J. Tustison C. Meyer 40 224 0 03 Dec 2018
Learn To Pay Attention Saumya Jetley Nicholas A. Lord Namhoon Lee Philip H. S. Torr 67 437 0 06 Apr 2018
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation Vijay Badrinarayanan Alex Kendall R. Cipolla SSeg 446 15,637 0 02 Nov 2015