Literature DB >> 18230538

On techniques for detecting circumscribed masses in mammograms.

S M Lai1, X Li, W F Biscof.   

Abstract

A method for detecting one type of breast tumor, circumscribed masses, in mammograms is presented. It relies on a combination of criteria used by experts, including the shape, brightness contrast, and uniform density of tumor areas. The method uses modified median filtering to enhance mammogram images and template matching to detect the tumors. In the template matching step, suspicious areas are identified by thresholding the cross-correlation values, and a percentile method is used to determine a threshold for each film. In addition, two tests are used to remove false alarms from the resulting candidates. The results obtained by applying these techniques to a set of test images are described. They are judged encouraging.

Entities:  

Year:  1989        PMID: 18230538     DOI: 10.1109/42.41491

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


  8 in total

1.  Computer-aided detection of breast masses on full field digital mammograms.

Authors:  Jun Wei; Berkman Sahiner; Lubomir M Hadjiiski; Heang-Ping Chan; Nicholas Petrick; Mark A Helvie; Marilyn A Roubidoux; Jun Ge; Chuan Zhou
Journal:  Med Phys       Date:  2005-09       Impact factor: 4.071

Review 2.  Anniversary paper: History and status of CAD and quantitative image analysis: the role of Medical Physics and AAPM.

Authors:  Maryellen L Giger; Heang-Ping Chan; John Boone
Journal:  Med Phys       Date:  2008-12       Impact factor: 4.071

3.  Detection of cancerous masses in mammograms by template matching: optimization of template brightness distribution by means of evolutionary algorithm.

Authors:  Marcin Bator; Mariusz Nieniewski
Journal:  J Digit Imaging       Date:  2012-02       Impact factor: 4.056

4.  Enhanced detection of normal retinal nerve-fiber striations using a charge-coupled device and digital filtering.

Authors:  D W Richards; J R Janesick; S T Elliot; A Dingizian; R Velthuizen; Q Wei; L P Clarke
Journal:  Graefes Arch Clin Exp Ophthalmol       Date:  1993-10       Impact factor: 3.117

5.  Mutual information-based template matching scheme for detection of breast masses: from mammography to digital breast tomosynthesis.

Authors:  Maciej A Mazurowski; Joseph Y Lo; Brian P Harrawood; Georgia D Tourassi
Journal:  J Biomed Inform       Date:  2011-05-01       Impact factor: 6.317

6.  Modelling the growth of solid tumours and incorporating a method for their classification using nonlinear elasticity theory.

Authors:  M A Chaplain; B D Sleeman
Journal:  J Math Biol       Date:  1993       Impact factor: 2.259

7.  A combined approach for the enhancement and segmentation of mammograms using modified fuzzy C-means method in wavelet domain.

Authors:  Subodh Srivastava; Neeraj Sharma; S K Singh; R Srivastava
Journal:  J Med Phys       Date:  2014-07

8.  Detection and Weak Segmentation of Masses in Gray-Scale Breast Mammogram Images Using Deep Learning.

Authors:  Young Jae Kim; Kwang Gi Kim
Journal:  Yonsei Med J       Date:  2022-01       Impact factor: 2.759

  8 in total

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