DS6, Deformation-aware Semi-supervised Learning: Application to Small
Vessel Segmentation with Noisy Training Data

DS6, Deformation-aware Semi-supervised Learning: Application to Small Vessel Segmentation with Noisy Training Data

18 June 2020

Mahantesh Pattadkal

Chompunuch Sarasaen

Florian Dubost

Hendrik Mattern

Marleen de Bruijne

Andreas Nürnberger

Papers citing "DS6, Deformation-aware Semi-supervised Learning: Application to Small Vessel Segmentation with Noisy Training Data"

17 / 17 papers shown

Title
TorchIO: A Python library for efficient loading, preprocessing, augmentation and patch-based sampling of medical images in deep learning Fernando Pérez-García Rachel Sparks Sébastien Ourselin MedIm LM&MA 196 430 0 09 Mar 2020
A Survey on Deep Learning-based Architectures for Semantic Segmentation on 2D images Irem Ülkü Erdem Akagündüz SSeg 56 192 0 21 Dec 2019
PyTorch: An Imperative Style, High-Performance Deep Learning Library Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury ... Sasank Chilamkurthy Benoit Steiner Lu Fang Junjie Bai Soumith Chintala ODL 361 42,299 0 03 Dec 2019
Semi-Supervised Medical Image Segmentation via Learning Consistency under Transformations Gerda Bortsova Florian Dubost Laurens Hogeweg Ioannis Katramados Marleen de Bruijne 55 179 0 04 Nov 2019
Multi Scale Supervised 3D U-Net for Kidney and Tumor Segmentation Wenshuai Zhao Zengfeng Zeng SSeg 33 14 0 09 Aug 2019
Joint segmentation and classification of retinal arteries/veins from fundus images Fantin Girard C. Kavalec Farida Cheriet 43 97 0 04 Mar 2019
A Novel Focal Tversky loss function with improved Attention U-Net for lesion segmentation Nabila Abraham N. Khan SSeg MedIm 63 702 0 18 Oct 2018
Semi-supervised Skin Lesion Segmentation via Transformation Consistent Self-ensembling Model Xiaomeng Li Lequan Yu Hao Chen Chi-Wing Fu Pheng-Ann Heng MedIm 60 135 0 12 Aug 2018
AirLab: Autograd Image Registration Laboratory Robin Sandkühler C. Jud Simon Andermatt Philippe C. Cattin 38 53 0 26 Jun 2018
Imperfect Segmentation Labels: How Much Do They Matter? N. Heller Joshua Dean Nikolaos Papanikolopoulos 53 37 0 12 Jun 2018
Attention U-Net: Learning Where to Look for the Pancreas Ozan Oktay Jo Schlemper Loic Le Folgoc M. J. Lee M. Heinrich ... Jingyu Sun Nils Y. Hammerla Bernhard Kainz Ben Glocker Daniel Rueckert SSeg 145 5,018 0 11 Apr 2018
Mixed Precision Training Paulius Micikevicius Sharan Narang Jonah Alben G. Diamos Erich Elsen ... Boris Ginsburg Michael Houston Oleksii Kuchaiev Ganesh Venkatesh Hao Wu 149 1,792 0 10 Oct 2017
Segmentation of Intracranial Arterial Calcification with Deeply Supervised Residual Dropout Networks Gerda Bortsova Gijs van Tulder Florian Dubost Tingying Peng Nassir Navab A. van der Lugt D. Bos Marleen de Bruijne 51 15 0 04 Jun 2017
A Survey on Deep Learning in Medical Image Analysis G. Litjens Thijs Kooi B. Bejnordi A. Setio F. Ciompi Mohsen Ghafoorian Jeroen van der Laak Bram van Ginneken C. I. Sánchez OOD 604 10,759 0 19 Feb 2017
3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation Özgün Çiçek Ahmed Abdulkadir S. Lienkamp Thomas Brox Olaf Ronneberger 3DV 3DPC SSeg 3DH 148 6,516 0 21 Jun 2016
U-Net: Convolutional Networks for Biomedical Image Segmentation Olaf Ronneberger Philipp Fischer Thomas Brox SSeg 3DV 1.6K 76,917 0 18 May 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.4K 149,842 0 22 Dec 2014