Literature DB >> 25086951

CADe for early detection of breast cancer-current status and why we need to continue to explore new approaches.

Robert M Nishikawa1, David Gur2.   

Abstract

The authors describe where we are in terms of using computer-aided detection (CADe) systems during clinical mammographic interpretations, what are the issues that we face, and why they believe that, despite disappointment in terms of verified added value when it comes to detection of soft tissue abnormalities, we need to continue to explore new approaches to improving CADe-alone performance levels and, more important perhaps, new approaches to optimal communication of CADe-generated information.
Copyright © 2014 AUR. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Computer-aided detection; breast imaging; computer-aided diagnosis; mammographic screening

Mesh:

Year:  2014        PMID: 25086951     DOI: 10.1016/j.acra.2014.05.018

Source DB:  PubMed          Journal:  Acad Radiol        ISSN: 1076-6332            Impact factor:   3.173


  13 in total

1.  Assessment of performance and reproducibility of applying a content-based image retrieval scheme for classification of breast lesions.

Authors:  Rohith Reddy Gundreddy; Maxine Tan; Yuchen Qiu; Samuel Cheng; Hong Liu; Bin Zheng
Journal:  Med Phys       Date:  2015-07       Impact factor: 4.071

2.  Applying a new quantitative image analysis scheme based on global mammographic features to assist diagnosis of breast cancer.

Authors:  Xuxin Chen; Abolfazl Zargari; Alan B Hollingsworth; Hong Liu; Bin Zheng; Yuchen Qiu
Journal:  Comput Methods Programs Biomed       Date:  2019-07-29       Impact factor: 5.428

3.  Development and Assessment of a New Global Mammographic Image Feature Analysis Scheme to Predict Likelihood of Malignant Cases.

Authors:  Morteza Heidari; Seyedehnafiseh Mirniaharikandehei; Wei Liu; Alan B Hollingsworth; Hong Liu; Bin Zheng
Journal:  IEEE Trans Med Imaging       Date:  2019-10-09       Impact factor: 10.048

4.  Applying a new computer-aided detection scheme generated imaging marker to predict short-term breast cancer risk.

Authors:  Seyedehnafiseh Mirniaharikandehei; Alan B Hollingsworth; Bhavika Patel; Morteza Heidari; Hong Liu; Bin Zheng
Journal:  Phys Med Biol       Date:  2018-05-15       Impact factor: 3.609

5.  Developing a new case based computer-aided detection scheme and an adaptive cueing method to improve performance in detecting mammographic lesions.

Authors:  Maxine Tan; Faranak Aghaei; Yunzhi Wang; Bin Zheng
Journal:  Phys Med Biol       Date:  2016-12-20       Impact factor: 3.609

6.  A new approach to develop computer-aided detection schemes of digital mammograms.

Authors:  Maxine Tan; Wei Qian; Jiantao Pu; Hong Liu; Bin Zheng
Journal:  Phys Med Biol       Date:  2015-05-18       Impact factor: 3.609

Review 7.  New targeted therapies for breast cancer: A focus on tumor microenvironmental signals and chemoresistant breast cancers.

Authors:  Armel Hervé Nwabo Kamdje; Paul Faustin Seke Etet; Lorella Vecchio; Richard Simo Tagne; Jeremie Mbo Amvene; Jean-Marc Muller; Mauro Krampera; Kiven Erique Lukong
Journal:  World J Clin Cases       Date:  2014-12-16       Impact factor: 1.337

8.  Computer-aided classification of mammographic masses using visually sensitive image features.

Authors:  Yunzhi Wang; Faranak Aghaei; Ali Zarafshani; Yuchen Qiu; Wei Qian; Bin Zheng
Journal:  J Xray Sci Technol       Date:  2017       Impact factor: 1.535

9.  A new approach to develop computer-aided diagnosis scheme of breast mass classification using deep learning technology.

Authors:  Yuchen Qiu; Shiju Yan; Rohith Reddy Gundreddy; Yunzhi Wang; Samuel Cheng; Hong Liu; Bin Zheng
Journal:  J Xray Sci Technol       Date:  2017       Impact factor: 1.535

10.  Applying a Random Projection Algorithm to Optimize Machine Learning Model for Breast Lesion Classification.

Authors:  Morteza Heidari; Sivaramakrishnan Lakshmivarahan; Seyedehnafiseh Mirniaharikandehei; Gopichandh Danala; Sai Kiran R Maryada; Hong Liu; Bin Zheng
Journal:  IEEE Trans Biomed Eng       Date:  2021-08-19       Impact factor: 4.756

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