Artificial intelligence for mammography and digital breast tomosynthesis: current concepts and future perspectives

KJ Geras, RM Mann, L Moy - Radiology, 2019 - pubs.rsna.org
Although computer-aided diagnosis (CAD) is widely used in mammography, conventional
CAD programs that use prompts to indicate potential cancers on the mammograms have not …

Digital breast tomosynthesis: concepts and clinical practice

A Chong, SP Weinstein, ES McDonald, EF Conant - Radiology, 2019 - pubs.rsna.org
Digital breast tomosynthesis (DBT) is emerging as the standard of care for breast imaging
based on improvements in both screening and diagnostic imaging outcomes. The additional …

Breast imaging reporting and data system (BI-RADS)

C D'Orsi, L Bassett, S Feig - … atlas, 4th edn. American College of …, 2018 - books.google.com
The American College of Radiology (ACR) Breast Imaging Reporting and Data System (BI-
RADS) 1 was initially a collaborative effort involving committees of the ACR, the National …

Five consecutive years of screening with digital breast tomosynthesis: outcomes by screening year and round

EF Conant, SP Zuckerman, ES McDonald… - Radiology, 2020 - pubs.rsna.org
Background Limited data exist beyond prevalence rounds of digital breast tomosynthesis
(DBT) screening. Purpose To compare DBT outcomes over multiple years and rounds to …

[HTML][HTML] Deep learning-based artificial intelligence for mammography

JH Yoon, EK Kim - Korean journal of radiology, 2021 - ncbi.nlm.nih.gov
During the past decade, researchers have investigated the use of computer-aided
mammography interpretation. With the application of deep learning technology, artificial …

Calcifications at digital breast tomosynthesis: imaging features and biopsy techniques

JV Horvat, DM Keating, H Rodrigues-Duarte… - Radiographics, 2019 - pubs.rsna.org
Full-field digital mammography (FFDM), the standard of care for breast cancer screening,
has some limitations. With the advent of digital breast tomosynthesis (DBT), improvements …

Computer-assisted frameworks for classification of liver, breast and blood neoplasias via neural networks: A survey based on medical images

A Brunetti, L Carnimeo, GF Trotta, V Bevilacqua - Neurocomputing, 2019 - Elsevier
Abstract Computer Aided Diagnosis (CAD) systems can support physicians in classifying
different kinds of breast cancer, liver cancer and blood tumours also revealed by images …

A performance comparison between shallow and deeper neural networks supervised classification of tomosynthesis breast lesions images

V Bevilacqua, A Brunetti, A Guerriero, GF Trotta… - Cognitive Systems …, 2019 - Elsevier
Abstract Computer Aided Decision (CAD) systems, based on 3D tomosynthesis imaging,
could support radiologists in classifying different kinds of breast lesions and then improve …

[HTML][HTML] False-negative results in lung cancer screening—evidence and controversies

EC Bartlett, M Silva, ME Callister, A Devaraj - Journal of Thoracic Oncology, 2021 - Elsevier
Identifying false-negative cases is an important quality metric in lung cancer screening, but it
has been infrequently and variably reported in previous studies. Although as a proportion of …

Breast MRI: false-negative results and missed opportunities

KE Korhonen, SP Zuckerman, SP Weinstein, J Tobey… - Radiographics, 2021 - pubs.rsna.org
Breast MRI is the most sensitive modality for the detection of breast cancer. However, false-
negative cases may occur, in which the cancer is not visualized at MRI and is instead …