These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
454 related articles for article (PubMed ID: 19928066)
1. Malignant lesion segmentation in contrast-enhanced breast MR images based on the marker-controlled watershed. Cui Y; Tan Y; Zhao B; Liberman L; Parbhu R; Kaplan J; Theodoulou M; Hudis C; Schwartz LH Med Phys; 2009 Oct; 36(10):4359-69. PubMed ID: 19928066 [TBL] [Abstract][Full Text] [Related]
2. 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]
3. Computerized interpretation of breast MRI: investigation of enhancement-variance dynamics. Chen W; Giger ML; Lan L; Bick U Med Phys; 2004 May; 31(5):1076-82. PubMed ID: 15191295 [TBL] [Abstract][Full Text] [Related]
4. Automatic identification and classification of characteristic kinetic curves of breast lesions on DCE-MRI. Chen W; Giger ML; Bick U; Newstead GM Med Phys; 2006 Aug; 33(8):2878-87. PubMed ID: 16964864 [TBL] [Abstract][Full Text] [Related]
5. A fuzzy c-means (FCM)-based approach for computerized segmentation of breast lesions in dynamic contrast-enhanced MR images. Chen W; Giger ML; Bick U Acad Radiol; 2006 Jan; 13(1):63-72. PubMed ID: 16399033 [TBL] [Abstract][Full Text] [Related]
6. 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]
7. Treatment response assessment of breast masses on dynamic contrast-enhanced magnetic resonance scans using fuzzy c-means clustering and level set segmentation. Shi J; Sahiner B; Chan HP; Paramagul C; Hadjiiski LM; Helvie M; Chenevert T Med Phys; 2009 Nov; 36(11):5052-63. PubMed ID: 19994516 [TBL] [Abstract][Full Text] [Related]
8. Automated chest wall line detection for whole-breast segmentation in sagittal breast MR images. Wu S; Weinstein SP; Conant EF; Schnall MD; Kontos D Med Phys; 2013 Apr; 40(4):042301. PubMed ID: 23556914 [TBL] [Abstract][Full Text] [Related]
9. Robust segmentation of mass-lesions in contrast-enhanced dynamic breast MR images. Meinel LA; Buelow T; Huo D; Shimauchi A; Kose U; Buurman J; Newstead G J Magn Reson Imaging; 2010 Jul; 32(1):110-9. PubMed ID: 20578017 [TBL] [Abstract][Full Text] [Related]
10. Semiautomatic segmentation of liver metastases on volumetric CT images. Yan J; Schwartz LH; Zhao B Med Phys; 2015 Nov; 42(11):6283-93. PubMed ID: 26520721 [TBL] [Abstract][Full Text] [Related]
11. Improved discrimination of breast lesions using selective sampling of segmented MR images. Issa B MAGMA; 2006 Feb; 19(1):34-40. PubMed ID: 16465550 [TBL] [Abstract][Full Text] [Related]
12. A new background distribution-based active contour model for three-dimensional lesion segmentation in breast DCE-MRI. Liu H; Liu Y; Zhao Z; Zhang L; Qiu T Med Phys; 2014 Aug; 41(8):082303. PubMed ID: 25086552 [TBL] [Abstract][Full Text] [Related]
13. A computerized global MR image feature analysis scheme to assist diagnosis of breast cancer: a preliminary assessment. Yang Q; Li L; Zhang J; Shao G; Zheng B Eur J Radiol; 2014 Jul; 83(7):1086-1091. PubMed ID: 24743001 [TBL] [Abstract][Full Text] [Related]
14. Multilevel analysis of spatiotemporal association features for differentiation of tumor enhancement patterns in breast DCE-MRI. Lee SH; Kim JH; Cho N; Park JS; Yang Z; Jung YS; Moon WK Med Phys; 2010 Aug; 37(8):3940-56. PubMed ID: 20879557 [TBL] [Abstract][Full Text] [Related]
15. Marker-controlled watershed for lymphoma segmentation in sequential CT images. Yan J; Zhao B; Wang L; Zelenetz A; Schwartz LH Med Phys; 2006 Jul; 33(7):2452-60. PubMed ID: 16898448 [TBL] [Abstract][Full Text] [Related]
16. Segmentation of lung lesions on CT scans using watershed, active contours, and Markov random field. Tan Y; Schwartz LH; Zhao B Med Phys; 2013 Apr; 40(4):043502. PubMed ID: 23556926 [TBL] [Abstract][Full Text] [Related]
17. Automatic segmentation of invasive breast carcinomas from dynamic contrast-enhanced MRI using time series analysis. Jayender J; Chikarmane S; Jolesz FA; Gombos E J Magn Reson Imaging; 2014 Aug; 40(2):467-75. PubMed ID: 24115175 [TBL] [Abstract][Full Text] [Related]
18. A fully automatic algorithm for segmentation of the breasts in DCE-MR images. Giannini V; Vignati A; Morra L; Persano D; Brizzi D; Carbonaro L; Bert A; Sardanelli F; Regge D Annu Int Conf IEEE Eng Med Biol Soc; 2010; 2010():3146-9. PubMed ID: 21096592 [TBL] [Abstract][Full Text] [Related]
19. Simultaneous segmentation and registration of contrast-enhanced breast MRI. Xiaohua C; Brady M; Lo JL; Moore N Inf Process Med Imaging; 2005; 19():126-37. PubMed ID: 17354690 [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]