183 related articles for article (PubMed ID: 22271831)
1. Computer-aided lesion diagnosis in automated 3-D breast ultrasound using coronal spiculation.
Tan T; Platel B; Huisman H; Sánchez CI; Mus R; Karssemeijer N
IEEE Trans Med Imaging; 2012 May; 31(5):1034-42. PubMed ID: 22271831
[TBL] [Abstract][Full Text] [Related]
2. Evaluation of the effect of computer-aided classification of benign and malignant lesions on reader performance in automated three-dimensional breast ultrasound.
Tan T; Platel B; Twellmann T; van Schie G; Mus R; Grivegnée A; Mann RM; Karssemeijer N
Acad Radiol; 2013 Nov; 20(11):1381-8. PubMed ID: 24119350
[TBL] [Abstract][Full Text] [Related]
3. Computer-aided detection of cancer in automated 3-D breast ultrasound.
Tan T; Platel B; Mus R; Tabar L; Mann RM; Karssemeijer N
IEEE Trans Med Imaging; 2013 Sep; 32(9):1698-706. PubMed ID: 23693128
[TBL] [Abstract][Full Text] [Related]
4. Computer-aided diagnosis for the classification of breast masses in automated whole breast ultrasound images.
Moon WK; Shen YW; Huang CS; Chiang LR; Chang RF
Ultrasound Med Biol; 2011 Apr; 37(4):539-48. PubMed ID: 21420580
[TBL] [Abstract][Full Text] [Related]
5. Quantitative analysis of breast echotexture patterns in automated breast ultrasound images.
Chang RF; Hou YL; Lo CM; Huang CS; Chen JH; Kim WH; Chang JM; Bae MS; Moon WK
Med Phys; 2015 Aug; 42(8):4566-78. PubMed ID: 26233185
[TBL] [Abstract][Full Text] [Related]
6. Multiplanar Reconstructions of 3D Automated Breast Ultrasound Improve Lesion Differentiation by Radiologists.
Van Zelst JC; Platel B; Karssemeijer N; Mann RM
Acad Radiol; 2015 Dec; 22(12):1489-96. PubMed ID: 26345538
[TBL] [Abstract][Full Text] [Related]
7. Malignant and benign breast masses on 3D US volumetric images: effect of computer-aided diagnosis on radiologist accuracy.
Sahiner B; Chan HP; Roubidoux MA; Hadjiiski LM; Helvie MA; Paramagul C; Bailey J; Nees AV; Blane C
Radiology; 2007 Mar; 242(3):716-24. PubMed ID: 17244717
[TBL] [Abstract][Full Text] [Related]
8. Computer-aided diagnosis with textural features for breast lesions in sonograms.
Chen DR; Huang YL; Lin SH
Comput Med Imaging Graph; 2011 Apr; 35(3):220-6. PubMed ID: 21131178
[TBL] [Abstract][Full Text] [Related]
9. Computer-Aided Diagnosis for Breast Ultrasound Using Computerized BI-RADS Features and Machine Learning Methods.
Shan J; Alam SK; Garra B; Zhang Y; Ahmed T
Ultrasound Med Biol; 2016 Apr; 42(4):980-8. PubMed ID: 26806441
[TBL] [Abstract][Full Text] [Related]
10. Characterization of spiculation on ultrasound lesions.
Huang SF; Chang RF; Chen DR; Moon WK
IEEE Trans Med Imaging; 2004 Jan; 23(1):111-21. PubMed ID: 14719692
[TBL] [Abstract][Full Text] [Related]
11. Computer-aided diagnosis based on quantitative elastographic features with supersonic shear wave imaging.
Xiao Y; Zeng J; Niu L; Zeng Q; Wu T; Wang C; Zheng R; Zheng H
Ultrasound Med Biol; 2014 Feb; 40(2):275-86. PubMed ID: 24268454
[TBL] [Abstract][Full Text] [Related]
12. Computerized characterization of breast masses on three-dimensional ultrasound volumes.
Sahiner B; Chan HP; Roubidoux MA; Helvie MA; Hadjiiski LM; Ramachandran A; Paramagul C; LeCarpentier GL; Nees A; Blane C
Med Phys; 2004 Apr; 31(4):744-54. PubMed ID: 15124991
[TBL] [Abstract][Full Text] [Related]
13. Dedicated computer-aided detection software for automated 3D breast ultrasound; an efficient tool for the radiologist in supplemental screening of women with dense breasts.
van Zelst JCM; Tan T; Clauser P; Domingo A; Dorrius MD; Drieling D; Golatta M; Gras F; de Jong M; Pijnappel R; Rutten MJCM; Karssemeijer N; Mann RM
Eur Radiol; 2018 Jul; 28(7):2996-3006. PubMed ID: 29417251
[TBL] [Abstract][Full Text] [Related]
14. Computer-aided diagnosis using morphological features for classifying breast lesions on ultrasound.
Huang YL; Chen DR; Jiang YR; Kuo SJ; Wu HK; Moon WK
Ultrasound Obstet Gynecol; 2008 Sep; 32(4):565-72. PubMed ID: 18383556
[TBL] [Abstract][Full Text] [Related]
15. Multimodality computerized diagnosis of breast lesions using mammography and sonography.
Drukker K; Horsch K; Giger ML
Acad Radiol; 2005 Aug; 12(8):970-9. PubMed ID: 16087091
[TBL] [Abstract][Full Text] [Related]
16. Computer-aided diagnosis of solid breast nodules: use of an artificial neural network based on multiple sonographic features.
Joo S; Yang YS; Moon WK; Kim HC
IEEE Trans Med Imaging; 2004 Oct; 23(10):1292-300. PubMed ID: 15493696
[TBL] [Abstract][Full Text] [Related]
17. Segmentation of malignant lesions in 3D breast ultrasound using a depth-dependent model.
Tan T; Gubern-Mérida A; Borelli C; Manniesing R; van Zelst J; Wang L; Zhang W; Platel B; Mann RM; Karssemeijer N
Med Phys; 2016 Jul; 43(7):4074. PubMed ID: 27370126
[TBL] [Abstract][Full Text] [Related]
18. Ultrasonic multi-feature analysis procedure for computer-aided diagnosis of solid breast lesions.
Alam SK; Feleppa EJ; Rondeau M; Kalisz A; Garra BS
Ultrason Imaging; 2011 Jan; 33(1):17-38. PubMed ID: 21608446
[TBL] [Abstract][Full Text] [Related]
19. Computer-aided diagnosis based on speckle patterns in ultrasound images.
Moon WK; Lo CM; Huang CS; Chen JH; Chang RF
Ultrasound Med Biol; 2012 Jul; 38(7):1251-61. PubMed ID: 22579548
[TBL] [Abstract][Full Text] [Related]
20. Combining low-, high-level and empirical domain knowledge for automated segmentation of ultrasonic breast lesions.
Madabhushi A; Metaxas DN
IEEE Trans Med Imaging; 2003 Feb; 22(2):155-69. PubMed ID: 12715992
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
