Look how far we have come: BREAST cancer detection education on the international stage

PD Trieu, CR Mello-Thoms, ML Barron… - Frontiers in oncology, 2023 - frontiersin.org
The development of screening mammography over 30 years has remarkedly reduced breast
cancer–associated mortality by 20%-30% through detection of small cancer lesions at early …

Using radiomics-based machine learning to create targeted test sets to improve specific mammography reader cohort performance: A feasibility study

X Tao, Z Gandomkar, T Li, PC Brennan… - Journal of Personalized …, 2023 - mdpi.com
Mammography interpretation is challenging with high error rates. This study aims to reduce
the errors in mammography reading by mapping diagnostic errors against global …

AHIVE: Anatomy-aware Hierarchical Vision Encoding for Interactive Radiology Report Retrieval

S Yan, WK Cheung, IW Tsang, K Chiu… - Proceedings of the …, 2024 - openaccess.thecvf.com
Automatic radiology report generation using deep learning models has been recently
explored and found promising. Neural decoders are commonly used for the report …

The impact of prior mammograms on the diagnostic performance of Radiologists in early breast cancer detection: A focus on breast density, lesion features and …

PD Trieu, N Borecky, T Li, PC Brennan, ML Barron… - Cancers, 2023 - mdpi.com
Simple Summary This study explored the diagnostic efficacy of radiologists when reading
screening mammograms in the absence of previous images (NP), and with prior images …

Variations of image interpretations of radiologists from different populations in mammography and tomosynthesis with different levels of breast density

PD Trieu, Q Xiao, Y Gu, SJ Lewis… - Journal of Medical …, 2023 - spiedigitallibrary.org
Purpose This study aims to investigate the diagnostic performances of Australian and
Shanghai-based Chinese radiologists in reading full-field digital mammogram (FFDM) and …

[PDF][PDF] Microcalcification detection in mammograms using deep learning

MS Kahnouei, M Giti, MA Akhaee… - Iranian Journal of …, 2022 - brieflands.com
Background: Mammography is the most reliable and popular method in the clinical
diagnosis of breast cancer. Calcifications are subtle lesions in mammograms that can be …

Global Radiomic Features from Mammography for Predicting Difficult-To-Interpret Normal Cases

S Siviengphanom, Z Gandomkar, SJ Lewis… - Journal of Digital …, 2023 - Springer
This work aimed to investigate whether global radiomic features (GRFs) from mammograms
can predict difficult-to-interpret normal cases (NCs). Assessments from 537 readers …

Surgical and Radiology Trainees' Proficiency in Reading Mammograms: the Importance of Education for Cancer Localisation

JB Wells, SJ Lewis, M Barron, PD Trieu - Journal of Cancer Education, 2024 - Springer
Medical imaging with mammography plays a very important role in screening and diagnosis
of breast cancer, Australia's most common female cancer. The visualisation of cancers on …

[HTML][HTML] Learning effects in visual grading assessment of model-based reconstruction algorithms in abdominal Computed Tomography

B Kataria, J Öman, M Sandborg, Ö Smedby - European Journal of …, 2023 - Elsevier
Objectives Images reconstructed with higher strengths of iterative reconstruction algorithms
may impair radiologists' subjective perception and diagnostic performance due to changes …

Precancerous microcalcification detection of breast cancer mammogram images using linear time-invariant filtering Wiener method with Tophat transformation

R Jamil, M Dong, S Bano, A Javed, M Abdullah - 2023 - researchsquare.com
Breast microcalcifications, tiny calcium salt deposits, can develop anywhere in the breast
tissue. Breast microcalcifications are a frequent mammographic finding. For a proper …