VinDr-Mammo: A large-scale benchmark dataset for computer-aided diagnosis in full-field digital mammography

HT Nguyen, HQ Nguyen, HH Pham, K Lam, LT Le… - Scientific Data, 2023 - nature.com
… The recall rate of mammogram screening is around 11% with … system that helps improve
radiologist performance. At around … The codes used in this study were made publicly available. …

[HTML][HTML] VinDr-Mammo: A large-scale benchmark dataset for computer-aided detection and diagnosis in full-field digital mammography

HH Pham, HN Trung, HQ Nguyen - Sci Data, 2022 - physionet.org
… (CAD) tools for breast cancer screening in clinical practices [5… might hinder the performance
of deep learning networks [13]. … full-field digital mammography dataset, which can be used

Deep learning computer-aided diagnosis for breast lesion in digital mammogram

MA Al-Antari, MA Al-Masni, TS Kim - Deep Learning in Medical Image …, 2020 - Springer
applied over each region. Same preprocessing strategy is used for all mammograms that
useddetection performance of the YOLO detector. Examples of the qualitative breast lesion …

TTCNN: A breast cancer detection and classification towards computer-aided diagnosis using digital mammography in early stages

S Maqsood, R Damaševičius, R Maskeliūnas - Applied Sciences, 2022 - mdpi.com
… breast cancer in mammogram screening images using an “end-… performance on breast
cancer detection and classification. … for the identification of lesions in breast in the full-field digital

Automated breast cancer detection and classification in full field digital mammograms using two full and cropped detection paths approach

G Hamed, M Marey, SE Amin, MF Tolba - IEEE Access, 2021 - ieeexplore.ieee.org
… to classify the localized lesions to compare their performance … a detector with the 2-paths
of detection of a full mammogram … to obtain a successful computer-aided detection model to …

Effect of artificial intelligence–based computer-aided diagnosis on the screening outcomes of digital mammography: a matched cohort study

H Kim, JS Choi, K Kim, ES Ko, EY Ko, BK Han - European Radiology, 2023 - Springer
… In particular, full-field digital mammography (DM), which has … to improve the efficiency of
mammography-based screening by … This may be because our study used pure screening data …

… computer-aided detection synthesized mammograms and digital mammograms when used alone and in combination with tomosynthesis images in a virtual screening …

T Uematsu, K Nakashima, TL Harada, H Nasu… - Japanese Journal of …, 2023 - Springer
… of improved overall performance with digital mammograms (DM) when used along with DBT
… the reader performance of new SM and compare it with that of the original full-field DM; the …

Computer-aided detection and diagnosis of microcalcification clusters on full field digital mammograms based on deep learning method using neutrosophic boosting

G Cai, Y Guo, W Chen, H Zeng, Y Zhou… - Multimedia Tools and …, 2020 - Springer
… FFDM, with a solid-state detector of amorphous selenium, the pixel size … used to evaluate
the performance of the proposed diagnosis system. Note that the INbreast dataset is only used

Artificial intelligence computer-aided detection enhances synthesized mammograms: comparison with original digital mammograms alone and in combination with …

T Uematsu, K Nakashima, TL Harada, H Nasu… - Breast Cancer, 2023 - Springer
… original full-field digital mammograms (DMs) can be replaced with synthesized mammograms
in both screening … To compare reader performance of artificial intelligence computer-aided

Evaluation of deep learning detection and classification towards computer-aided diagnosis of breast lesions in digital X-ray mammograms

MA Al-Antari, SM Han, TS Kim - Computer methods and programs in …, 2020 - Elsevier
detect breast lesions in the full-field digital mammograms (… mammograms were accurately
acquired as full-field digital … YOLO detector (ie, YOLO 9000) is adopted and used to detect