Optimal reconstruction and quantitative image features for computer-aided diagnosis tools for breast CT-Reference-Cited by-同舟云学术

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Optimal reconstruction and quantitative image features for computer-aided diagnosis tools for breast CT

Published:2017-04-13 Issue:5 Volume:44 Page:1846-1856
ISSN:0094-2405
Container-title:Medical Physics
language:en
Short-container-title:Med. Phys.

Author:

Lee Juhun¹,Nishikawa Robert M.¹,Reiser Ingrid²,Boone John M.³

Affiliation:

1. Department of Radiology; University of Pittsburgh; Pittsburgh PA 15213 USA

2. Department of Radiology; The University of Chicago; Chicago IL 60637 USA

3. Department of Radiology; University of California Davis Medical Center; Sacramento CA 95817 USA

Funder

National Institutes of Health

Publisher

Wiley

Subject

General Medicine

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1002/mp.12214/fullpdf

Reference25 articles.

1. Dedicated breast computed tomography: The optimal cross-sectional imaging solution?;Lindfors;Radiol Clin North Am,2010

2. CADx of mammographic masses and clustered microcalcifications: A review;Elter;Med Phys,2009

3. Computer-aided diagnosis in medical imaging: Historical review, current status and future potential;Doi;Comput Med Imaging Graph,2007

4. A review of computer-aided diagnosis of breast cancer: Toward the detection of subtle signs;Rangayyan;J Franklin Inst,2007

5. A systematic review of computer-assisted diagnosis in diagnostic cancer imaging;Eadie;Eur J Radiol,2012

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1. Computational Techniques in PET/CT Image Processing for Breast Cancer: A Systematic Mapping Review;ACM Computing Surveys;2024-04-26

2. Deep learning-based segmentation of breast masses in dedicated breast CT imaging: Radiomic feature stability between radiologists and artificial intelligence;Computers in Biology and Medicine;2020-03

3. Relationship between computer segmentation performance and computer classification performance in breast CT: A simulation study using RGI segmentation and LDA classification;Medical Physics;2018-07-06

4. Optimization of computer aided detection systems: An evolutionary approach;Expert Systems with Applications;2018-06

5. Phase classification of mitotic events using selective dictionary learning for stem cell populations;Computers & Electrical Engineering;2018-04

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