Literature DB >> 17252171

Level set contouring for breast tumor in sonography.

Yu-Len Huang1, Yu-Ru Jiang, Dar-Ren Chen, Woo Kyung Moon.   

Abstract

The echogenicity, echotexture, shape, and contour of a lesion are revealed to be effective sonographic features for physicians to identify a tumor as either benign or malignant. Automatic contouring for breast tumors in sonography may assist physicians without relevant experience, in making correct diagnoses. This study develops an efficient method for automatically detecting contours of breast tumors in sonography. First, a sophisticated preprocessing filter reduces the noise, but preserves the shape and contrast of the breast tumor. An adaptive initial contouring method is then performed to obtain an approximate circular contour of the tumor. Finally, the deformation-based level set segmentation automatically extracts the precise contours of breast tumors from ultrasound (US) images. The proposed contouring method evaluates US images from 118 patients with breast tumors. The contouring results, obtained with computer simulation, reveal that the proposed method always identifies similar contours to those obtained with manual sketching. The proposed method provides robust and fast automatic contouring for breast US images. The potential role of this approach might save much of the time required to sketch a precise contour with very high stability.

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Year:  2007        PMID: 17252171      PMCID: PMC3043893          DOI: 10.1007/s10278-006-1041-6

Source DB:  PubMed          Journal:  J Digit Imaging        ISSN: 0897-1889            Impact factor:   4.056


  21 in total

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Journal:  Biomed Tech (Berl)       Date:  2002       Impact factor: 1.411

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Authors:  Chung-Ming Chen; Yi-Hong Chou; Ko-Chung Han; Guo-Shian Hung; Chui-Mei Tiu; Hong-Jen Chiou; See-Ying Chiou
Journal:  Radiology       Date:  2003-02       Impact factor: 11.105

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Authors:  Yu-Len Huang; Dar-Ren Chen
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  9 in total

1.  Left ventricular myocardium segmentation on delayed phase of multi-detector row computed tomography.

Authors:  I-Chen Tsai; Yu-Len Huang; Po-Ting Liu; Min-Chi Chen
Journal:  Int J Comput Assist Radiol Surg       Date:  2012-04-19       Impact factor: 2.924

2.  Thick slices from tomosynthesis data sets: phantom study for the evaluation of different algorithms.

Authors:  Felix Diekmann; Henning Meyer; Susanne Diekmann; Sylvie Puong; Serge Muller; Ulrich Bick; Patrik Rogalla
Journal:  J Digit Imaging       Date:  2007-10-23       Impact factor: 4.056

Review 3.  Breast ultrasound image segmentation: a survey.

Authors:  Qinghua Huang; Yaozhong Luo; Qiangzhi Zhang
Journal:  Int J Comput Assist Radiol Surg       Date:  2017-01-09       Impact factor: 2.924

Review 4.  Automated breast tumor detection and segmentation with a novel computational framework of whole ultrasound images.

Authors:  Lei Liu; Kai Li; Wenjian Qin; Tiexiang Wen; Ling Li; Jia Wu; Jia Gu
Journal:  Med Biol Eng Comput       Date:  2018-01-02       Impact factor: 2.602

5.  Highly sensitive computer aided diagnosis system for breast tumor based on color Doppler flow images.

Authors:  Xian-Fen Diao; Xin-Yu Zhang; Tian-Fu Wang; Si-Ping Chen; Ying Yang; Ling Zhong
Journal:  J Med Syst       Date:  2010-04-23       Impact factor: 4.460

6.  Multiview Contouring for Breast Tumor on Magnetic Resonance Imaging.

Authors:  Dar-Ren Chen; Yao-Wen Chang; Hwa-Koon Wu; Wei-Chung Shia; Yu-Len Huang
Journal:  J Digit Imaging       Date:  2019-10       Impact factor: 4.056

7.  Malignant lesion segmentation in contrast-enhanced breast MR images based on the marker-controlled watershed.

Authors:  Yunfeng Cui; Yongqiang Tan; Binsheng Zhao; Laura Liberman; Rakesh Parbhu; Jennifer Kaplan; Maria Theodoulou; Clifford Hudis; Lawrence H Schwartz
Journal:  Med Phys       Date:  2009-10       Impact factor: 4.071

8.  Classification of Benign and Malignant Breast Tumors in Ultrasound Images with Posterior Acoustic Shadowing Using Half-Contour Features.

Authors:  Shuicai Wu; Zhuhuang Zhou; King-Jen Chang; Wei-Ren Chen; Yung-Sheng Chen; Wen-Hung Kuo; Chung-Chih Lin; Po-Hsiang Tsui
Journal:  J Med Biol Eng       Date:  2015-04-11       Impact factor: 1.553

9.  A Novel Segmentation Approach Combining Region- and Edge-Based Information for Ultrasound Images.

Authors:  Yaozhong Luo; Longzhong Liu; Qinghua Huang; Xuelong Li
Journal:  Biomed Res Int       Date:  2017-04-27       Impact factor: 3.411

  9 in total

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