Multiple Objects Localization Using Image Segmentation with U-Net

Author(s):  
Dominik Stursa ◽  
Petr Dolezel ◽  
Daniel Honc
2016 ◽  
Vol 10 (4) ◽  
pp. 314-324 ◽  
Author(s):  
Mazlinda Ibrahim ◽  
Ke Chen ◽  
Lavdie Rada

Image segmentation and registration are two of the most challenging tasks in medical imaging. They are closely related because both tasks are often required simultaneously. In this article, we present an improved variational model for a joint segmentation and registration based on active contour without edges and the linear curvature model. The proposed model allows large deformation to occur by solving in this way the difficulties other jointly performed segmentation and registration models have in case of encountering multiple objects into an image or their highly dependence on the initialisation or the need for a pre-registration step, which has an impact on the segmentation results. Through different numerical results, we show that the proposed model gives correct registration results when there are different features inside the object to be segmented or features that have clear boundaries but without fine details in which the old model would not be able to cope.


2009 ◽  
Vol 27 (8) ◽  
pp. 1223-1227 ◽  
Author(s):  
Mark Polak ◽  
Hong Zhang ◽  
Minghong Pi

2020 ◽  
Vol 2020 ◽  
pp. 1-18 ◽  
Author(s):  
Chaolu Feng ◽  
Jinzhu Yang ◽  
Chunhui Lou ◽  
Wei Li ◽  
Kun Yu ◽  
...  

Image segmentation is still an open problem especially when intensities of the objects of interest are overlapped due to the presence of intensity inhomogeneities. A bias correction embedded level set model is proposed in this paper where inhomogeneities are estimated by orthogonal primary functions. First, an inhomogeneous intensity clustering energy is defined based on global distribution characteristics of the image intensities, and membership functions of the clusters described by the level set function are then introduced to define the data term energy of the proposed model. Second, a regularization term and an arc length term are also included to regularize the level set function and smooth its zero-level set contour, respectively. Third, the proposed model is extended to multichannel and multiphase patterns to segment colorful images and images with multiple objects, respectively. Experimental results and comparison with relevant models demonstrate the advantages of the proposed model in terms of bias correction and segmentation accuracy on widely used synthetic and real images and the BrainWeb and the IBSR image repositories.


Author(s):  
Junichi Shibata ◽  
Takehisa Yairi ◽  
Hirofumi Kanazaki ◽  
Youhei Shirasaka ◽  
Kazuo Machida

2010 ◽  
Vol 29 (12) ◽  
pp. 2023-2037 ◽  
Author(s):  
Yin Yin ◽  
Xiangmin Zhang ◽  
Rachel Williams ◽  
Xiaodong Wu ◽  
Donald D Anderson ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document