270 related articles for article (PubMed ID: 22104530)
1. Effect of a novel segmentation algorithm on radiologists' diagnosis of breast masses using ultrasound imaging.
Tian JW; Ning CP; Guo YH; Cheng HD; Tang XL
Ultrasound Med Biol; 2012 Jan; 38(1):119-27. PubMed ID: 22104530
[TBL] [Abstract][Full Text] [Related]
2. 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]
3. CAD algorithms for solid breast masses discrimination: evaluation of the accuracy and interobserver variability.
Wang Y; Jiang S; Wang H; Guo YH; Liu B; Hou Y; Cheng H; Tian J
Ultrasound Med Biol; 2010 Aug; 36(8):1273-81. PubMed ID: 20691917
[TBL] [Abstract][Full Text] [Related]
4. 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]
5. Speckle reduction approach for breast ultrasound image and its application to breast cancer diagnosis.
Su Y; Wang H; Wang Y; Guo Y; Cheng H; Zhang Y; Tian J
Eur J Radiol; 2010 Jul; 75(1):e136-41. PubMed ID: 19913380
[TBL] [Abstract][Full Text] [Related]
6. 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]
7. A new automated method for the segmentation and characterization of breast masses on ultrasound images.
Cui J; Sahiner B; Chan HP; Nees A; Paramagul C; Hadjiiski LM; Zhou C; Shi J
Med Phys; 2009 May; 36(5):1553-65. PubMed ID: 19544771
[TBL] [Abstract][Full Text] [Related]
8. Computer-assisted assessment of ultrasound real-time elastography: initial experience in 145 breast lesions.
Zhang X; Xiao Y; Zeng J; Qiu W; Qian M; Wang C; Zheng R; Zheng H
Eur J Radiol; 2014 Jan; 83(1):e1-7. PubMed ID: 24148563
[TBL] [Abstract][Full Text] [Related]
9. Whole Breast Ultrasound: Comparison of the Visibility of Suspicious Lesions with Automated Breast Volumetric Scanning Versus Hand-Held Breast Ultrasound.
Kuzmiak CM; Ko EY; Tuttle LA; Steed D; Zeng D; Yoon SC
Acad Radiol; 2015 Jul; 22(7):870-9. PubMed ID: 25872862
[TBL] [Abstract][Full Text] [Related]
10. Intensity-Invariant Texture Analysis for Classification of BI-RADS Category 3 Breast Masses.
Lo CM; Moon WK; Huang CS; Chen JH; Yang MC; Chang RF
Ultrasound Med Biol; 2015 Jul; 41(7):2039-48. PubMed ID: 25843514
[TBL] [Abstract][Full Text] [Related]
11. 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]
12. Computerized lesion segmentation of breast ultrasound based on marker-controlled watershed transformation.
Gómez W; Leija L; Alvarenga AV; Infantosi AF; Pereira WC
Med Phys; 2010 Jan; 37(1):82-95. PubMed ID: 20175469
[TBL] [Abstract][Full Text] [Related]
13. 1000-Case Reader Study of Radiologists' Performance in Interpretation of Automated Breast Volume Scanner Images with a Computer-Aided Detection System.
Xu X; Bao L; Tan Y; Zhu L; Kong F; Wang W
Ultrasound Med Biol; 2018 Aug; 44(8):1694-1702. PubMed ID: 29853222
[TBL] [Abstract][Full Text] [Related]
14. 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]
15. 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]
16. Differentiation of benign and malignant breast lesions: a comparison between automatically generated breast volume scans and handheld ultrasound examinations.
Wang HY; Jiang YX; Zhu QL; Zhang J; Dai Q; Liu H; Lai XJ; Sun Q
Eur J Radiol; 2012 Nov; 81(11):3190-200. PubMed ID: 22386134
[TBL] [Abstract][Full Text] [Related]
17. Computerized-aid diagnosis of breast mass using ultrasound image.
Tian JW; Sun LT; Guo YH; Cheng HD; Zhang YT
Med Phys; 2007 Aug; 34(8):3158-64. PubMed ID: 17879777
[TBL] [Abstract][Full Text] [Related]
18. Bimodal Multiparameter-Based Approach for Benign-Malignant Classification of Breast Tumors.
Ara SR; Alam F; Rahman MH; Akhter S; Awwal R; Hasan K
Ultrasound Med Biol; 2015 Jul; 41(7):2022-38. PubMed ID: 25913281
[TBL] [Abstract][Full Text] [Related]
19. Comparative study of automated breast 3-D ultrasound and handheld B-mode ultrasound for differentiation of benign and malignant breast masses.
Chen L; Chen Y; Diao XH; Fang L; Pang Y; Cheng AQ; Li WP; Wang Y
Ultrasound Med Biol; 2013 Oct; 39(10):1735-42. PubMed ID: 23849390
[TBL] [Abstract][Full Text] [Related]
20. Qualitative pattern classification of shear wave elastography for breast masses: how it correlates to quantitative measurements.
Yoon JH; Ko KH; Jung HK; Lee JT
Eur J Radiol; 2013 Dec; 82(12):2199-204. PubMed ID: 24041435
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
