A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Filters
Semi-automated segmentation and classification of digital breast tomosynthesis reconstructed images
2011
2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Preserved Fulltext
Digital breast tomosynthesis (DBT) is a limited-angle tomographic x-ray imaging technique that reduces the effect of tissue super position observed in planar mammography. ...
In this work, we provide a segmentation and classification method to extract potential lesions, as well as adipose, fibroglandular, muscle and skin tissue in reconstructed DBT images that serve as anatomic ...
The contents are solely the responsibility of the authors and do not represent the official views of the NIH or the NCI. ...
doi:10.1109/iembs.2011.6091528
pmid:22255752
pmcid:PMC3548319
dblp:conf/embc/VedanthamSKMKPP11
fatcat:cpyzkrkwond6fmyojzv5f22pt4
Breast tissue classification in digital breast tomosynthesis images using texture features: a feasibility study
2009
Medical Imaging 2009: Computer-Aided Diagnosis
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
Digital breast tomosynthesis (DBT) is a tomographic x-ray breast imaging modality that could allow volumetric breast density estimation. ...
Studies have shown the potential to automate breast density estimation by using computerized texture-based segmentation of the dense tissue in mammograms. ...
Digital breast tomosynthesis (DBT) is a 3D x-ray breast imaging modality in which tomographic images of the breast are reconstructed from multiple low-dose 2D x-ray source projection images 7 . ...
doi:10.1117/12.813812
dblp:conf/micad/KontosBBM09
fatcat:vmuwdwhqdrcqtaswxrtls7zzse
Differences in breast density assessment using mammography, tomosynthesis and MRI and their implications for practice
2013
British Journal of Radiology
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
The problem of image artefacts is very limited when using fully digital images on automated software. ...
Literature searching of PubMed highlights, through the number of articles related to breast density and also to digital breast tomosynthesis (DBT), that there is an increasing interest in breast density ...
doi:10.1259/bjr.20130528
pmid:24167184
pmcid:PMC3854572
fatcat:4rf2mvau7ba45fotqqsszmz43y
Front Matter: Volume 11312
2020
Medical Imaging 2020: Physics of Medical Imaging
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
using dual energy digital breast tomosynthesis 11312 0P An investigation of slot-scanning for mammography and breast CT 11312 0Q Deep convolutional neural network denoising for digital breast tomosynthesis ...
QUALITY ASSESSMENT AND OPTIMIZATION IN BREAST IMAGING
0H Factors affecting microcalcification detection of wide-angle digital breast tomosynthesis and strategies for improving performance 11312 0I ...
This award is co-sponsored by: The Medical Image Perception Society 2020 Recipients: ...
doi:10.1117/12.2570912
fatcat:vl6kcecvhvfr5ogs3og5czzvwq
Front Matter: Volume 7624
2010
Medical Imaging 2010: Computer-Aided Diagnosis
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
Srisomboon, BMA General Hospital (Thailand)
SESSION 10 BREAST MRI AND TOMOSYNTHESIS
1D Digital breast tomosynthesis: computerized detection of microcalcifications in reconstructed breast volume using ...
Helvie, Univ. of Michigan (United States)7624 1EThe reconstruction of microcalcification clusters in digital breast tomosynthesis C. P. S. Ho, C. E. Tromans, J. A. Schnabel, S. M. ...
doi:10.1117/12.856064
dblp:conf/micad/X10
fatcat:wiizcc3mbne5zl7h4b4y5lqbm4
Table of contents
2019
IEEE Transactions on Medical Imaging
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Budde, and T. van Walsum Joint Weakly and Semi-Supervised Deep Learning for Localization and Classification of Masses in Breast Ultrasound Images ...................................... S. Y. Shin, S. ...
Li Breast Cancer Diagnosis in Digital Breast Tomosynthesis: Effects of Training Sample Size on Multi-Stage Transfer Learning Using Deep Neural Nets ..................................................... ...
doi:10.1109/tmi.2019.2899275
fatcat:ttb63zhs7bdl5nu2xby66z4irq
Front Matter: Volume 11318
2020
Medical Imaging 2020: Imaging Informatics for Healthcare, Research, and Applications
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Utilization of CIDs allows articles to be fully citable as soon as they are published online, and connects the same identifier to all online and print versions of the publication. ...
Publication of record for individual papers is online in the SPIE Digital Library. SPIEDigitalLibrary.org Paper Numbering: Proceedings of SPIE follow an e-First publication model. ...
Contents
SESSION 3 DEEP LEARNING DIAGNOSTICS
0D Breast cancer classification from digital breast tomosynthesis using 3D multi-subvolume approach 11318 0E Automated detection of microaneurysms in color ...
doi:10.1117/12.2570206
fatcat:fman4hvttfhhjldpoo2pltdpcm
Breast composition: Measurement and clinical use
2015
Radiography
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
Automated volumetric approaches are explained while ultrasound, digital breast tomosynthesis, molecular breast imaging, and magnetic resonance imaging are introduced as valuable adjuncts to digital mammography ...
The relevance of breast density knowledge to mammographic practice and image interpretation is considered in the light of clinical assessment and notification of mammographic breast density (MBD). ...
Automated volumetric approaches are more preferable for MBD assessment, and ultrasound, digital breast tomosynthesis, molecular breast imaging, and magnetic resonance imaging are valuable adjuncts to digital ...
doi:10.1016/j.radi.2015.06.006
fatcat:4a4e2zpxz5epvmbhf324tv6pwy
Front Matter: Volume 12035
2022
Medical Imaging 2022: Image Perception, Observer Performance, and Technology Assessment
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
digital breast tomosynthesis (DBT) images [12035-1] 12035 09
Satisfaction of search (SOS) error and new lesions identification on imaging in central review for clinical trials OBSERVER PERFORMANCE AND ...
for ROC analysis of multi-reader multi-case diagnostic imaging studies [12035-19] 12035 0H Diagnostic performances of radiology trainees in reading digital breast tomosynthesis and the synthesized view ...
doi:10.1117/12.2638123
fatcat:avdabxr5rfbt3hk4emgzgr7z3i
Front Matter: Volume 6915
2008
Medical Imaging 2008: Computer-Aided Diagnosis
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
Numbers in the index correspond to the last two digits of the six-digit CID number. ...
Publication of record for individual papers is online in the SPIE Digital Library. ...
Giger, The Univ. of Chicago (USA) SESSION 2 BREAST TOMOSYNTHESIS 6915 05 Computer-aided detection of breast masses in tomosynthesis reconstructed volumes using information-theoretic similarity measures ...
doi:10.1117/12.797938
dblp:conf/micad/X08
fatcat:ofuszodznnbhdjgavmgo26tugi
Front Matter: Volume 10134
2017
Medical Imaging 2017: Computer-Aided Diagnosis
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
Utilization of CIDs allows articles to be fully citable as soon as they are published online, and connects the same identifier to all online and print versions of the publication. ...
Publication of record for individual papers is online in the SPIE Digital Library. SPIEDigitalLibrary.org Paper Numbering: Proceedings of SPIE follow an e-First publication model. ...
[10134-93]
10134 2Q
Automated assessment of breast tissue density in non-contrast 3D CT images without
image segmentation based on a deep CNN [10134-94]
10134 2R
Automated detection of microcalcification ...
doi:10.1117/12.2277119
dblp:conf/micad/X17
fatcat:ika7pheqxngdxejyvkss4dkbv4
Front Matter: Volume 9784
2016
Medical Imaging 2016: Image Processing
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
4 SEGMENTATION: BRAIN 9784 0G Segmentation and labeling of the ventricular system in normal pressure hydrocephalus using patch-based tissue classification and multi-atlas labeling [9784-15] 9784 0H Generation ...
estimation [9784-13] 9784 0F Automated segmentation of upper digestive tract from abdominal contrast-enhanced CT data using hierarchical statistical modeling of organ interrelations [9784-14] SESSION ...
/sigmoid via user-defined
templates [9784-113]
ix
Proc. of SPIE Vol. 9784 978401-9
Automatic segmentation of mammogram and tomosynthesis images [9784-114]
9784 38
Automated separation of merged ...
doi:10.1117/12.2240619
fatcat:kot6cogf4rf6dcjhkzdrr5gahi
Mammographic density. Measurement of mammographic density
2008
Breast Cancer Research
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
It is also possible to measure breast density with other imaging modalities, such as ultrasound and MRI, which do not require the use of ionizing radiation and may, therefore, be more suitable for use ...
Mammographic density has been strongly associated with increased risk of breast cancer. ...
with risk and the accuracy of breast cancer detection. ...
doi:10.1186/bcr2102
pmid:18598375
pmcid:PMC2481498
fatcat:cx6yg4qclfbjto4rz42g4jmasi
Automated Segmentation of Mass Regions in DBT Images Using a Dilated DCNN Approach
2022
Computational Intelligence and Neuroscience
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
To overcome the limitations of conventional breast screening methods based on digital mammography, a quasi-3D imaging technique, digital breast tomosynthesis (DBT) has been developed in the field of breast ...
Then the mass regions in DBT images are preliminarily segmented; each pixel is divided into two different kinds of labels. ...
LY16F010008) and also supported in part by the Medical and Health Science and Technology Plan of Zhejiang Province of China (Grant no. 2019RC224). ...
doi:10.1155/2022/9082694
pmid:35154309
pmcid:PMC8828338
fatcat:jieh6kifajaupm44w6e636w7oy
Mammography with deep learning for breast cancer detection
2024
Frontiers in Oncology
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2024; you can also visit the original URL.
The file type is application/pdf.
This paper aims to study the recent achievements of deep learning-based mammography for breast cancer detection and classification. ...
It is hoped that the research findings will assist investigators, engineers, and clinicians in developing more effective breast imaging tools that provide accurate diagnosis, sensitivity, and specificity ...
Digital breast tomosynthesis DBT was first introduced in the early 2000s. ...
doi:10.3389/fonc.2024.1281922
pmid:38410114
pmcid:PMC10894909
fatcat:ijey7tkyergbdmmgo7koglzrba
« Previous
Showing results 1 — 15 out of 121 results