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Intensity Based Automatic Boundary Identification of Pectoral Muscle in Mammograms

  • Published:2016 Issue: Volume:79 Page:262-269
  • ISSN:1877-0509
  • Container-title:Procedia Computer Science
  • language:en
  • Short-container-title:Procedia Computer Science

Author:

Vikhe P.S.,Thool V.R.

Publisher

Elsevier BV

Subject

General Engineering

Reference16 articles.

1. http://www.wiau.man.ac.uk/services/MIAS/MIASweb.html.

2. American cancer society, cancer facts and fgures, American Cancer Society,Atlanta, Ga, 2005-2015.

3. Karthikeyan Ganesan, URajendra Acharya, Chua Kuang Chua, Lim Choo Min, KThomas Abraham, and K Ng, Computer-aided breast cancer detection using mammograms: A review, Biomedical Engineering, IEEE Reviews in, 6:77-98, 2013.

4. Computer-aided detection and diagnosis of breast cancer with mammography: recent advances;Jinshan Tang;Information Technology in Biomedicine, IEEE Transactions on,2009

5. Pectoral muscle segmentation: a review;Karthikeyan;Computer methods and programs in biomedicine,2013

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1. A New Fat-Removal-Based Preprocessing Pipeline for MLO View in Digital Mammograms;IEEE Access;2023

2. Review on pre-processing algorithms for breast density classification using digital mammograms;INTERNATIONAL CONFERENCE ON SMART MATERIALS AND STRUCTURES, ICSMS-2022;2023

3. Pectoral Muscle Removal Techniques: A review;2022 19th International Multi-Conference on Systems, Signals & Devices (SSD);2022-05-06

4. Segmentation and Classification Methods Of Mammograms: A Case Study;2022 6th International Conference on Devices, Circuits and Systems (ICDCS);2022-04-21

5. Suspicious Region Segmentation Using Deep Features in Breast Cancer Mammogram Images;2022 International Conference on Computer Science and Software Engineering (CSASE);2022-03-15
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