activity
20182026
most citedMONAI: An open-source framework for deep learning in healthcare

452 citations · 561 across the 24 of their papers we have counts for

collaborators
Showing 2019Show all

5 papers · 1 filter

cs.CV20194 cited

NeurReg: Neural Registration and Its Application to Image Segmentation

Wentao Zhu, Andriy Myronenko, Ziyue Xu +5

Registration is a fundamental task in medical image analysis which can be applied to several tasks including image segmentation, intra-operative tracking, multi-modal image alignme…

eess.IV2019

3D Kidneys and Kidney Tumor Semantic Segmentation using Boundary-Aware Networks

Andriy Myronenko, Ali Hatamizadeh

Automated segmentation of kidneys and kidney tumors is an important step in quantifying the tumor's morphometrical details to monitor the progression of the disease and accurately…

cs.CV2019

End-to-End Boundary Aware Networks for Medical Image Segmentation

Ali Hatamizadeh, Demetri Terzopoulos, Andriy Myronenko

Fully convolutional neural networks (CNNs) have proven to be effective at representing and classifying textural information, thus transforming image intensity into output class mas…

cs.CV201940 cited

When Unseen Domain Generalization is Unnecessary? Rethinking Data Augmentation

Ling Zhang, Xiaosong Wang, Dong Yang +7

Recent advances in deep learning for medical image segmentation demonstrate expert-level accuracy. However, in clinically realistic environments, such methods have marginal perform…

eess.IV2019

4D CNN for semantic segmentation of cardiac volumetric sequences

Andriy Myronenko, Dong Yang, Varun Buch +6

We propose a 4D convolutional neural network (CNN) for the segmentation of retrospective ECG-gated cardiac CT, a series of single-channel volumetric data over time. While only a sm…