472 related articles for article (PubMed ID: 29157459)
1. A computer-aided diagnosis system for breast ultrasound based on weighted BI-RADS classes.
Rodríguez-Cristerna A; Gómez-Flores W; de Albuquerque Pereira WC
Comput Methods Programs Biomed; 2018 Jan; 153():33-40. PubMed ID: 29157459
[TBL] [Abstract][Full Text] [Related]
2. Computer aided classification system for breast ultrasound based on Breast Imaging Reporting and Data System (BI-RADS).
Shen WC; Chang RF; Moon WK
Ultrasound Med Biol; 2007 Nov; 33(11):1688-98. PubMed ID: 17681678
[TBL] [Abstract][Full Text] [Related]
3. Computer-aided classification of BI-RADS category 3 breast lesions.
Buchbinder SS; Leichter IS; Lederman RB; Novak B; Bamberger PN; Sklair-Levy M; Yarmish G; Fields SI
Radiology; 2004 Mar; 230(3):820-3. PubMed ID: 14739315
[TBL] [Abstract][Full Text] [Related]
4. Development and validation of a transformer-based CAD model for improving the consistency of BI-RADS category 3-5 nodule classification among radiologists: a multiple center study.
Ji H; Zhu Q; Ma T; Cheng Y; Zhou S; Ren W; Huang H; He W; Ran H; Ruan L; Guo Y; Tian J; Chen W; Chen L; Wang Z; Zhou Q; Niu L; Zhang W; Yang R; Chen Q; Zhang R; Wang H; Li L; Liu M; Nie F; Zhou A
Quant Imaging Med Surg; 2023 Jun; 13(6):3671-3687. PubMed ID: 37284087
[TBL] [Abstract][Full Text] [Related]
5. Deep Learning-Based Computer-Aided Diagnosis for Breast Lesion Classification on Ultrasound: A Prospective Multicenter Study of Radiologists Without Breast Ultrasound Expertise.
He P; Chen W; Bai MY; Li J; Wang QQ; Fan LH; Zheng J; Liu CT; Zhang XR; Yuan XR; Song PJ; Cui LG
AJR Am J Roentgenol; 2023 Oct; 221(4):450-459. PubMed ID: 37222275
[No Abstract] [Full Text] [Related]
6. What Help Could Ultrasound Elastography Give to the Diagnosis of Breast Papillary Lesions?
Li LJ; Yao JY; Zhou XC; Zhao XB; Zhong WJ; Ou B; Luo BM; Hao SY; Zhi H
Ultrasound Med Biol; 2017 May; 43(5):903-910. PubMed ID: 28256344
[TBL] [Abstract][Full Text] [Related]
7. EMD-DWT based transform domain feature reduction approach for quantitative multi-class classification of breast lesions.
Ara SR; Bashar SK; Alam F; Hasan MK
Ultrasonics; 2017 Sep; 80():22-33. PubMed ID: 28499122
[TBL] [Abstract][Full Text] [Related]
8. Usefulness of combined BI-RADS analysis and Nakagami statistics of ultrasound echoes in the diagnosis of breast lesions.
Dobruch-Sobczak K; Piotrzkowska-Wróblewska H; Roszkowska-Purska K; Nowicki A; Jakubowski W
Clin Radiol; 2017 Apr; 72(4):339.e7-339.e15. PubMed ID: 28038779
[TBL] [Abstract][Full Text] [Related]
9. Scoring system based on BI-RADS lexicon to predict probability of malignancy in suspicious microcalcifications.
Youk JH; Son EJ; Kim JA; Moon HJ; Kim MJ; Choi CH; Kim EK
Ann Surg Oncol; 2012 May; 19(5):1491-8. PubMed ID: 22173328
[TBL] [Abstract][Full Text] [Related]
10. Can a Computer-Aided Mass Diagnosis Model Based on Perceptive Features Learned From Quantitative Mammography Radiology Reports Improve Junior Radiologists' Diagnosis Performance? An Observer Study.
He Z; Li Y; Zeng W; Xu W; Liu J; Ma X; Wei J; Zeng H; Xu Z; Wang S; Wen C; Wu J; Feng C; Ma M; Qin G; Lu Y; Chen W
Front Oncol; 2021; 11():773389. PubMed ID: 34976817
[TBL] [Abstract][Full Text] [Related]
11. A Machine Learning Ensemble Based on Radiomics to Predict BI-RADS Category and Reduce the Biopsy Rate of Ultrasound-Detected Suspicious Breast Masses.
Interlenghi M; Salvatore C; Magni V; Caldara G; Schiavon E; Cozzi A; Schiaffino S; Carbonaro LA; Castiglioni I; Sardanelli F
Diagnostics (Basel); 2022 Jan; 12(1):. PubMed ID: 35054354
[TBL] [Abstract][Full Text] [Related]
12. Breast masses: computer-aided diagnosis with serial mammograms.
Hadjiiski L; Sahiner B; Helvie MA; Chan HP; Roubidoux MA; Paramagul C; Blane C; Petrick N; Bailey J; Klein K; Foster M; Patterson SK; Adler D; Nees AV; Shen J
Radiology; 2006 Aug; 240(2):343-56. PubMed ID: 16801362
[TBL] [Abstract][Full Text] [Related]
13. BUS-BRA: A breast ultrasound dataset for assessing computer-aided diagnosis systems.
Gómez-Flores W; Gregorio-Calas MJ; Coelho de Albuquerque Pereira W
Med Phys; 2024 Apr; 51(4):3110-3123. PubMed ID: 37937827
[TBL] [Abstract][Full Text] [Related]
14. Computer-aided diagnosis of breast masses using quantified BI-RADS findings.
Moon WK; Lo CM; Cho N; Chang JM; Huang CS; Chen JH; Chang RF
Comput Methods Programs Biomed; 2013 Jul; 111(1):84-92. PubMed ID: 23639752
[TBL] [Abstract][Full Text] [Related]
15. Computer-Aided Diagnosis in Multiparametric Magnetic Resonance Imaging Screening of Women With Extremely Dense Breasts to Reduce False-Positive Diagnoses.
Verburg E; van Gils CH; Bakker MF; Viergever MA; Pijnappel RM; Veldhuis WB; Gilhuijs KGA
Invest Radiol; 2020 Jul; 55(7):438-444. PubMed ID: 32149858
[TBL] [Abstract][Full Text] [Related]
16. The diagnostic performance of ultrasound computer-aided diagnosis system for distinguishing breast masses: a prospective multicenter study.
Wei Q; Yan YJ; Wu GG; Ye XR; Jiang F; Liu J; Wang G; Wang Y; Song J; Pan ZP; Hu JH; Jin CY; Wang X; Dietrich CF; Cui XW
Eur Radiol; 2022 Jun; 32(6):4046-4055. PubMed ID: 35066633
[TBL] [Abstract][Full Text] [Related]
17. Diagnostic value of acoustic radiation force impulse for BI-RADS category 4 breast lesions of different sizes.
You QQ; Xu M; Yao MH; Xu G; Liu H; Pu H; Xiang LH; Wu R
Clin Hemorheol Microcirc; 2018; 70(2):143-154. PubMed ID: 29710678
[TBL] [Abstract][Full Text] [Related]
18. Quantitative ultrasound analysis for classification of BI-RADS category 3 breast masses.
Moon WK; Lo CM; Chang JM; Huang CS; Chen JH; Chang RF
J Digit Imaging; 2013 Dec; 26(6):1091-8. PubMed ID: 23494603
[TBL] [Abstract][Full Text] [Related]
19. Improving the Accuracy of Computer-aided Diagnosis for Breast MR Imaging by Differentiating between Mass and Nonmass Lesions.
Gallego-Ortiz C; Martel AL
Radiology; 2016 Mar; 278(3):679-88. PubMed ID: 26383229
[TBL] [Abstract][Full Text] [Related]
20. [Stereotactic Mammotome breast biopsy: routine clinical experience and correlation with BI-RADS--classification and histopathology].
Michel SC; Löw R; Singer G; Otto R; Hohl M; Kubik RA
Praxis (Bern 1994); 2007 Sep; 96(39):1459-74. PubMed ID: 17966279
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
