355 related articles for article (PubMed ID: 29748869)
41. Contamination artifact that mimics in-situ carcinoma on contrast-enhanced digital mammography.
Gluskin J; Click M; Fleischman R; Dromain C; Morris EA; Jochelson MS
Eur J Radiol; 2017 Oct; 95():147-154. PubMed ID: 28987661
[TBL] [Abstract][Full Text] [Related]
42. Contrast-enhanced digital mammography.
Dromain C; Balleyguier C; Adler G; Garbay JR; Delaloge S
Eur J Radiol; 2009 Jan; 69(1):34-42. PubMed ID: 18790584
[TBL] [Abstract][Full Text] [Related]
43. Evaluation of a New Ensemble Learning Framework for Mass Classification in Mammograms.
Rahmani Seryasat O; Haddadnia J
Clin Breast Cancer; 2018 Jun; 18(3):e407-e420. PubMed ID: 29141776
[TBL] [Abstract][Full Text] [Related]
44. Breast mass detection and diagnosis using fused features with density.
Wang Z; Huang Y; Li M; Zhang H; Li C; Xin J; Qian W
J Xray Sci Technol; 2019; 27(2):321-342. PubMed ID: 30856154
[TBL] [Abstract][Full Text] [Related]
45. Computerized detection of masses in digitized mammograms using single-image segmentation and a multilayer topographic feature analysis.
Zheng B; Chang YH; Gur D
Acad Radiol; 1995 Nov; 2(11):959-66. PubMed ID: 9419667
[TBL] [Abstract][Full Text] [Related]
46. Contrast-enhanced dual-energy mammography: a promising new imaging tool in breast cancer detection.
Lalji U; Lobbes M
Womens Health (Lond); 2014 May; 10(3):289-98. PubMed ID: 24956295
[TBL] [Abstract][Full Text] [Related]
47. A New Computer-Aided Diagnosis System with Modified Genetic Feature Selection for BI-RADS Classification of Breast Masses in Mammograms.
Boumaraf S; Liu X; Ferkous C; Ma X
Biomed Res Int; 2020; 2020():7695207. PubMed ID: 32462017
[TBL] [Abstract][Full Text] [Related]
48. Applying a new computer-aided detection scheme generated imaging marker to predict short-term breast cancer risk.
Mirniaharikandehei S; Hollingsworth AB; Patel B; Heidari M; Liu H; Zheng B
Phys Med Biol; 2018 May; 63(10):105005. PubMed ID: 29667606
[TBL] [Abstract][Full Text] [Related]
49. A new near-term breast cancer risk prediction scheme based on the quantitative analysis of ipsilateral view mammograms.
Sun W; Tseng TB; Qian W; Saltzstein EC; Zheng B; Yu H; Zhou S
Comput Methods Programs Biomed; 2018 Mar; 155():29-38. PubMed ID: 29512502
[TBL] [Abstract][Full Text] [Related]
50. Computer-aided detection of masses in digital tomosynthesis mammography: comparison of three approaches.
Chan HP; Wei J; Zhang Y; Helvie MA; Moore RH; Sahiner B; Hadjiiski L; Kopans DB
Med Phys; 2008 Sep; 35(9):4087-95. PubMed ID: 18841861
[TBL] [Abstract][Full Text] [Related]
51. Computer-aided detection in mammography: an assessment of performance on current and prior images.
Zheng B; Shah R; Wallace L; Hakim C; Ganott MA; Gur D
Acad Radiol; 2002 Nov; 9(11):1245-50. PubMed ID: 12449356
[TBL] [Abstract][Full Text] [Related]
52. Computer-aided characterization of mammographic masses: accuracy of mass segmentation and its effects on characterization.
Sahiner B; Petrick N; Chan HP; Hadjiiski LM; Paramagul C; Helvie MA; Gurcan MN
IEEE Trans Med Imaging; 2001 Dec; 20(12):1275-84. PubMed ID: 11811827
[TBL] [Abstract][Full Text] [Related]
53. Preoperative loco-regional staging of invasive lobular carcinoma with contrast-enhanced digital mammography (CEDM).
Amato F; Bicchierai G; Cirone D; Depretto C; Di Naro F; Vanzi E; Scaperrotta G; Bartolotta TV; Miele V; Nori J
Radiol Med; 2019 Dec; 124(12):1229-1237. PubMed ID: 31773458
[TBL] [Abstract][Full Text] [Related]
54. Assessment of global and local region-based bilateral mammographic feature asymmetry to predict short-term breast cancer risk.
Li Y; Fan M; Cheng H; Zhang P; Zheng B; Li L
Phys Med Biol; 2018 Jan; 63(2):025004. PubMed ID: 29226849
[TBL] [Abstract][Full Text] [Related]
55. Parameter optimization of a computer-aided diagnosis system for detection of masses on digitized mammograms.
Radovic M; Milosevic M; Ninkovic S; Filipovic N; Peulic A
Technol Health Care; 2015; 23(6):757-74. PubMed ID: 26409521
[TBL] [Abstract][Full Text] [Related]
56. YOLO Based Breast Masses Detection and Classification in Full-Field Digital Mammograms.
Aly GH; Marey M; El-Sayed SA; Tolba MF
Comput Methods Programs Biomed; 2021 Mar; 200():105823. PubMed ID: 33190942
[TBL] [Abstract][Full Text] [Related]
57. A deep learning approach for the analysis of masses in mammograms with minimal user intervention.
Dhungel N; Carneiro G; Bradley AP
Med Image Anal; 2017 Apr; 37():114-128. PubMed ID: 28171807
[TBL] [Abstract][Full Text] [Related]
58. Computer-aided detection systems for breast masses: comparison of performances on full-field digital mammograms and digitized screen-film mammograms.
Wei J; Hadjiiski LM; Sahiner B; Chan HP; Ge J; Roubidoux MA; Helvie MA; Zhou C; Wu YT; Paramagul C; Zhang Y
Acad Radiol; 2007 Jun; 14(6):659-69. PubMed ID: 17502255
[TBL] [Abstract][Full Text] [Related]
59. A new approach to develop computer-aided detection schemes of digital mammograms.
Tan M; Qian W; Pu J; Liu H; Zheng B
Phys Med Biol; 2015 Jun; 60(11):4413-27. PubMed ID: 25984710
[TBL] [Abstract][Full Text] [Related]
60. Computer-aided breast cancer detection and diagnosis of masses using difference of Gaussians and derivative-based feature saliency.
Polakowski WE; Cournoyer DA; Rogers SK; DeSimio MP; Ruck DW; Hoffmeister JW; Raines RA
IEEE Trans Med Imaging; 1997 Dec; 16(6):811-9. PubMed ID: 9533581
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]