Literature DB >> 16894993

Ultrasound image segmentation: a survey.

J Alison Noble1, Djamal Boukerroui.   

Abstract

This paper reviews ultrasound segmentation paper methods, in a broad sense, focusing on techniques developed for medical B-mode ultrasound images. First, we present a review of articles by clinical application to highlight the approaches that have been investigated and degree of validation that has been done in different clinical domains. Then, we present a classification of methodology in terms of use of prior information. We conclude by selecting ten papers which have presented original ideas that have demonstrated particular clinical usefulness or potential specific to the ultrasound segmentation problem.

Mesh:

Year:  2006        PMID: 16894993     DOI: 10.1109/tmi.2006.877092

Source DB:  PubMed          Journal:  IEEE Trans Med Imaging        ISSN: 0278-0062            Impact factor:   10.048


  101 in total

1.  Segmentation of 3D radio frequency echocardiography using a spatio-temporal predictor.

Authors:  P C Pearlman; H D Tagare; B A Lin; A J Sinusas; J S Duncan
Journal:  Med Image Anal       Date:  2011-10-14       Impact factor: 8.545

2.  An effective approach of lesion segmentation within the breast ultrasound image based on the cellular automata principle.

Authors:  Yan Liu; H D Cheng; Jianhua Huang; Yingtao Zhang; Xianglong Tang
Journal:  J Digit Imaging       Date:  2012-10       Impact factor: 4.056

3.  Breast ultrasound image classification based on multiple-instance learning.

Authors:  Jianrui Ding; H D Cheng; Jianhua Huang; Jiafeng Liu; Yingtao Zhang
Journal:  J Digit Imaging       Date:  2012-10       Impact factor: 4.056

4.  3D ultrasound image segmentation using wavelet support vector machines.

Authors:  Hamed Akbari; Baowei Fei
Journal:  Med Phys       Date:  2012-06       Impact factor: 4.071

5.  Endocardial boundary extraction in left ventricular echocardiographic images using fast and adaptive B-spline snake algorithm.

Authors:  Mahdi Marsousi; Armin Eftekhari; Armen Kocharian; Javad Alirezaie
Journal:  Int J Comput Assist Radiol Surg       Date:  2010-03-16       Impact factor: 2.924

6.  Automatic kidney segmentation in ultrasound images using subsequent boundary distance regression and pixelwise classification networks.

Authors:  Shi Yin; Qinmu Peng; Hongming Li; Zhengqiang Zhang; Xinge You; Katherine Fischer; Susan L Furth; Gregory E Tasian; Yong Fan
Journal:  Med Image Anal       Date:  2019-11-08       Impact factor: 8.545

7.  Automated skin segmentation in ultrasonic evaluation of skin toxicity in breast cancer radiotherapy.

Authors:  Yi Gao; Allen Tannenbaum; Hao Chen; Mylin Torres; Emi Yoshida; Xiaofeng Yang; Yuefeng Wang; Walter Curran; Tian Liu
Journal:  Ultrasound Med Biol       Date:  2013-08-27       Impact factor: 2.998

8.  MITK-US: real-time ultrasound support within MITK.

Authors:  K März; A M Franz; A Seitel; A Winterstein; R Bendl; S Zelzer; M Nolden; H-P Meinzer; L Maier-Hein
Journal:  Int J Comput Assist Radiol Surg       Date:  2013-12-17       Impact factor: 2.924

9.  A dataset of laryngeal endoscopic images with comparative study on convolution neural network-based semantic segmentation.

Authors:  Max-Heinrich Laves; Jens Bicker; Lüder A Kahrs; Tobias Ortmaier
Journal:  Int J Comput Assist Radiol Surg       Date:  2019-01-16       Impact factor: 2.924

10.  A Dynamical Shape Prior for LV Segmentation from RT3D Echocardiography.

Authors:  Yun Zhu; Xenophon Papademetris; Albert J Sinusas; James S Duncan
Journal:  Med Image Comput Comput Assist Interv       Date:  2009
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