Hough-CNN: Deep learning for segmentation of deep brain regions in MRI and ultrasound

Fausto Milletarì; Seyed‐Ahmad Ahmadi; Christine Kroll; Annika Plate; Verena Rozanski; Juliana Maiostre; Johannes Levin; Olaf Dietrich; Birgit Ertl‐Wagner; Kai Bötzel; Nassir Navab

doi:10.1016/j.cviu.2017.04.002

Keywords

Computer scienceArtificial intelligenceSegmentationConvolutional neural networkPattern recognition (psychology)Deep learningHough transformCurse of dimensionalityAbstractionComputer visionImage (mathematics)

Affiliated Institutions

Related Publications

Swin-Unet: Unet-Like Pure Transformer for Medical Image Segmentation

Hu Cao , Yueyue Wang , Joy Chen +4 more

In the past few years, convolutional neural networks (CNNs) have achieved milestones in medical image analysis. Especially, the deep neural networks based on U-shaped architectu...

2023 Lecture notes in computer science 2757 citations

Object Detection via a Multi-region and Semantic Segmentation-Aware CNN Model

Spyros Gidaris , Nikos Komodakis

We propose an object detection system that relies on a multi-region deep convolutional neural network (CNN) that also encodes semantic segmentation-aware features. The resulting...

2015 799 citations

Convolutional Neural Networks for Medical Image Analysis: Full Training or Fine Tuning?

Nima Tajbakhsh , J. Shin , Suryakanth Gurudu +4 more

Training a deep convolutional neural network (CNN) from scratch is difficult because it requires a large amount of labeled training data and a great deal of expertise to ensure ...

2016 IEEE Transactions on Medical Imaging 2961 citations

Image Super-Resolution Using Deep Convolutional Networks

Chao Dong , Chen Change Loy , Kaiming He +1 more

We propose a deep learning method for single image super-resolution (SR). Our method directly learns an end-to-end mapping between the low/high-resolution images. The mapping is...

2015 IEEE Transactions on Pattern Analysis... 9271 citations

Efficient Piecewise Training of Deep Structured Models for Semantic Segmentation

Guosheng Lin , Chunhua Shen , Anton van den Hengel +1 more

Recent advances in semantic image segmentation have mostly been achieved by training deep convolutional neural networks (CNNs). We show how to improve semantic segmentation thro...

2016 844 citations

Publication Info

Year: 2017
Type: article
Volume: 164
Pages: 92-102
Citations: 375
Access: Closed

External Links

View on DOI.org

Social Impact

Altmetric

Hough-CNN: Deep learning for segmentation of deep brain regions in MRI and ultrasound

PlumX Metrics

Social media, news, blog, policy document mentions

Citation Metrics

375

OpenAlex

Cite This

APA Style

                            
                                    Fausto Milletarì, 
                                
                                    Seyed‐Ahmad Ahmadi, 
                                
                                    Christine Kroll
                                
                                et al.
                            
                            (2017). 
                            Hough-CNN: Deep learning for segmentation of deep brain regions in MRI and ultrasound. 
                            Computer Vision and Image Understanding
                            , 164
                            
                            , 92-102.
                            https://doi.org/10.1016/j.cviu.2017.04.002

Identifiers

DOI: 10.1016/j.cviu.2017.04.002