Literature DB >> 17282932

Automatic contouring for breast tumors in 2-d sonography.

Yu-Len Huang1, Dar-Ren Chen.   

Abstract

Automatic contouring for breast tumors using medical ultrasound (US) imaging may assist physicians, without relevant experience, in making correct diagnoses. This study utilizes the watershed transform and active contour model (ACM) to overcome the natural properties of US images, speckle, noise and tissue-related textures, to segment the breast tumors precisely. The watershed transform is performed as the automatic initial contouring procedure to maintain a rough tumor shape and boundary. Next, ACM automatically determines the exquisite contours of the tumor. The results of computer simulations reveal that the proposed method always identified similar contours and regions-of-interest (ROI) as were obtained by manual contouring (by an experienced physician) of the breast tumor in US images. As ultrasound imaging becomes more widespread, a functional automatic contouring is essential to clinical application. In computer-aided diagnosis (CAD) applications, moreover, automatic contouring can save much of the time required to sketch a precise contour, with very high stability.

Entities:  

Year:  2005        PMID: 17282932     DOI: 10.1109/IEMBS.2005.1617163

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  3 in total

Review 1.  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

2.  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

Review 3.  BUSIS: A Benchmark for Breast Ultrasound Image Segmentation.

Authors:  Yingtao Zhang; Min Xian; Heng-Da Cheng; Bryar Shareef; Jianrui Ding; Fei Xu; Kuan Huang; Boyu Zhang; Chunping Ning; Ying Wang
Journal:  Healthcare (Basel)       Date:  2022-04-14
  3 in total

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