161 related articles for article (PubMed ID: 36856841)
1. Diagnostic accuracy of automated ACR BI-RADS breast density classification using deep convolutional neural networks.
Sexauer R; Hejduk P; Borkowski K; Ruppert C; Weikert T; Dellas S; Schmidt N
Eur Radiol; 2023 Jul; 33(7):4589-4596. PubMed ID: 36856841
[TBL] [Abstract][Full Text] [Related]
2. Determination of mammographic breast density using a deep convolutional neural network.
Ciritsis A; Rossi C; Vittoria De Martini I; Eberhard M; Marcon M; Becker AS; Berger N; Boss A
Br J Radiol; 2019 Jan; 92(1093):20180691. PubMed ID: 30209957
[TBL] [Abstract][Full Text] [Related]
3. Automatic classification of ultrasound breast lesions using a deep convolutional neural network mimicking human decision-making.
Ciritsis A; Rossi C; Eberhard M; Marcon M; Becker AS; Boss A
Eur Radiol; 2019 Oct; 29(10):5458-5468. PubMed ID: 30927100
[TBL] [Abstract][Full Text] [Related]
4. Automated pectoral muscle identification on MLO-view mammograms: Comparison of deep neural network to conventional computer vision.
Ma X; Wei J; Zhou C; Helvie MA; Chan HP; Hadjiiski LM; Lu Y
Med Phys; 2019 May; 46(5):2103-2114. PubMed ID: 30771257
[TBL] [Abstract][Full Text] [Related]
5. Understanding Clinical Mammographic Breast Density Assessment: a Deep Learning Perspective.
Mohamed AA; Luo Y; Peng H; Jankowitz RC; Wu S
J Digit Imaging; 2018 Aug; 31(4):387-392. PubMed ID: 28932980
[TBL] [Abstract][Full Text] [Related]
6. Fully automatic classification of automated breast ultrasound (ABUS) imaging according to BI-RADS using a deep convolutional neural network.
Hejduk P; Marcon M; Unkelbach J; Ciritsis A; Rossi C; Borkowski K; Boss A
Eur Radiol; 2022 Jul; 32(7):4868-4878. PubMed ID: 35147776
[TBL] [Abstract][Full Text] [Related]
7. BI-RADS-Based Classification of Mammographic Soft Tissue Opacities Using a Deep Convolutional Neural Network.
Sabani A; Landsmann A; Hejduk P; Schmidt C; Marcon M; Borkowski K; Rossi C; Ciritsis A; Boss A
Diagnostics (Basel); 2022 Jun; 12(7):. PubMed ID: 35885470
[TBL] [Abstract][Full Text] [Related]
8. A new automated method to evaluate 2D mammographic breast density according to BI-RADS® Atlas Fifth Edition recommendations.
Balleyguier C; Arfi-Rouche J; Boyer B; Gauthier E; Helin V; Loshkajian A; Ragusa S; Delaloge S
Eur Radiol; 2019 Jul; 29(7):3830-3838. PubMed ID: 30770972
[TBL] [Abstract][Full Text] [Related]
9. Inter- and intraradiologist variability in the BI-RADS assessment and breast density categories for screening mammograms.
Redondo A; Comas M; Macià F; Ferrer F; Murta-Nascimento C; Maristany MT; Molins E; Sala M; Castells X
Br J Radiol; 2012 Nov; 85(1019):1465-70. PubMed ID: 22993385
[TBL] [Abstract][Full Text] [Related]
10. Measuring mammographic density: comparing a fully automated volumetric assessment versus European radiologists' qualitative classification.
Sartor H; Lång K; Rosso A; Borgquist S; Zackrisson S; Timberg P
Eur Radiol; 2016 Dec; 26(12):4354-4360. PubMed ID: 27011371
[TBL] [Abstract][Full Text] [Related]
11. Digital breast tomosynthesis versus digital mammography: integration of image modalities enhances deep learning-based breast mass classification.
Li X; Qin G; He Q; Sun L; Zeng H; He Z; Chen W; Zhen X; Zhou L
Eur Radiol; 2020 Feb; 30(2):778-788. PubMed ID: 31691121
[TBL] [Abstract][Full Text] [Related]
12. Comparison Between Digital and Synthetic 2D Mammograms in Breast Density Interpretation.
Alshafeiy TI; Wadih A; Nicholson BT; Rochman CM; Peppard HR; Patrie JT; Harvey JA
AJR Am J Roentgenol; 2017 Jul; 209(1):W36-W41. PubMed ID: 28504593
[TBL] [Abstract][Full Text] [Related]
13. Classification of Mammographic Breast Microcalcifications Using a Deep Convolutional Neural Network: A BI-RADS-Based Approach.
Schönenberger C; Hejduk P; Ciritsis A; Marcon M; Rossi C; Boss A
Invest Radiol; 2021 Apr; 56(4):224-231. PubMed ID: 33038095
[TBL] [Abstract][Full Text] [Related]
14. Automated mammographic breast density estimation using a fully convolutional network.
Lee J; Nishikawa RM
Med Phys; 2018 Mar; 45(3):1178-1190. PubMed ID: 29363774
[TBL] [Abstract][Full Text] [Related]
15. Persistent inter-observer variability of breast density assessment using BI-RADS® 5th edition guidelines.
Portnow LH; Georgian-Smith D; Haider I; Barrios M; Bay CP; Nelson KP; Raza S
Clin Imaging; 2022 Mar; 83():21-27. PubMed ID: 34952487
[TBL] [Abstract][Full Text] [Related]
16. Mammographic density: Comparison of visual assessment with fully automatic calculation on a multivendor dataset.
Sacchetto D; Morra L; Agliozzo S; Bernardi D; Björklund T; Brancato B; Bravetti P; Carbonaro LA; Correale L; Fantò C; Favettini E; Martincich L; Milanesio L; Mombelloni S; Monetti F; Morrone D; Pellegrini M; Pesce B; Petrillo A; Saguatti G; Stevanin C; Trimboli RM; Tuttobene P; Valentini M; Marra V; Frigerio A; Bert A; Sardanelli F
Eur Radiol; 2016 Jan; 26(1):175-83. PubMed ID: 25929945
[TBL] [Abstract][Full Text] [Related]
17. A comparison of full-field digital mammograms versus 2D synthesized mammograms for detection of microcalcifications on screening.
Wahab RA; Lee SJ; Zhang B; Sobel L; Mahoney MC
Eur J Radiol; 2018 Oct; 107():14-19. PubMed ID: 30292258
[TBL] [Abstract][Full Text] [Related]
18. Inter-observer agreement according to three methods of evaluating mammographic density and parenchymal pattern in a case control study: impact on relative risk of breast cancer.
Winkel RR; von Euler-Chelpin M; Nielsen M; Diao P; Nielsen MB; Uldall WY; Vejborg I
BMC Cancer; 2015 Apr; 15():274. PubMed ID: 25884160
[TBL] [Abstract][Full Text] [Related]
19. Automated Breast Density Assessment in MRI Using Deep Learning and Radiomics: Strategies for Reducing Inter-Observer Variability.
Jing X; Wielema M; Monroy-Gonzalez AG; Stams TRG; Mahesh SVK; Oudkerk M; Sijens PE; Dorrius MD; van Ooijen PMA
J Magn Reson Imaging; 2024 Jul; 60(1):80-91. PubMed ID: 37846440
[TBL] [Abstract][Full Text] [Related]
20. Breast lesion shape and margin evaluation: BI-RADS based metrics understate radiologists' actual levels of agreement.
Rawashdeh M; Lewis S; Zaitoun M; Brennan P
Comput Biol Med; 2018 May; 96():294-298. PubMed ID: 29673997
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
