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Co-Authors

This is a "connection" page, showing publications co-authored by Karen Drukker and Maryellen L. Giger.

 
Connection Strength
 
 
 
8.175
 
  1. Drukker K, Edwards A, Doyle C, Papaioannou J, Kulkarni K, Giger ML. Breast MRI radiomics for the pretreatment prediction of response to neoadjuvant chemotherapy in node-positive breast cancer patients. J Med Imaging (Bellingham). 2019 Jul; 6(3):034502.
    View in: PubMed
    Score: 0.827
  2. Drukker K, Li H, Antropova N, Edwards A, Papaioannou J, Giger ML. Most-enhancing tumor volume by MRI radiomics predicts recurrence-free survival "early on" in neoadjuvant treatment of breast cancer. Cancer Imaging. 2018 Apr 13; 18(1):12.
    View in: PubMed
    Score: 0.747
  3. Drukker K, Sennett CA, Giger ML. Computerized detection of breast cancer on automated breast ultrasound imaging of women with dense breasts. Med Phys. 2014 Jan; 41(1):012901.
    View in: PubMed
    Score: 0.555
  4. Drukker K, Horsch KJ, Pesce LL, Giger ML. Interreader scoring variability in an observer study using dual-modality imaging for breast cancer detection in women with dense breasts. Acad Radiol. 2013 Jul; 20(7):847-53.
    View in: PubMed
    Score: 0.528
  5. Drukker K, Pesce L, Giger M. Repeatability in computer-aided diagnosis: application to breast cancer diagnosis on sonography. Med Phys. 2010 Jun; 37(6):2659-69.
    View in: PubMed
    Score: 0.433
  6. Drukker K, Pesce L, Giger M. Repeatability in computer-aided diagnosis: Application to breast cancer diagnosis on sonography. Med Phys. 2010 Jun; 37(6Part1):2659-2669.
    View in: PubMed
    Score: 0.433
  7. Drukker K, Sennett CA, Giger ML. Automated method for improving system performance of computer-aided diagnosis in breast ultrasound. IEEE Trans Med Imaging. 2009 Jan; 28(1):122-8.
    View in: PubMed
    Score: 0.393
  8. Drukker K, Gruszauskas NP, Sennett CA, Giger ML. Breast US computer-aided diagnosis workstation: performance with a large clinical diagnostic population. Radiology. 2008 Aug; 248(2):392-7.
    View in: PubMed
    Score: 0.378
  9. Drukker K, Horsch K, Giger ML. Multimodality computerized diagnosis of breast lesions using mammography and sonography. Acad Radiol. 2005 Aug; 12(8):970-9.
    View in: PubMed
    Score: 0.310
  10. Whitney HM, Drukker K, Giger ML. Performance metric curve analysis framework to assess impact of the decision variable threshold, disease prevalence, and dataset variability in two-class classification. J Med Imaging (Bellingham). 2022 May; 9(3):035502.
    View in: PubMed
    Score: 0.249
  11. Hu Q, Drukker K, Giger ML. Role of standard and soft tissue chest radiography images in deep-learning-based early diagnosis of COVID-19. J Med Imaging (Bellingham). 2021 Jan; 8(Suppl 1):014503.
    View in: PubMed
    Score: 0.237
  12. Whitney HM, Drukker K, Edwards A, Papaioannou J, Medved M, Karczmar G, Giger ML. Robustness of radiomic features of benign breast lesions and hormone receptor positive/HER2-negative cancers across DCE-MR magnet strengths. Magn Reson Imaging. 2021 10; 82:111-121.
    View in: PubMed
    Score: 0.233
  13. Drukker K, Giger ML, Joe BN, Kerlikowske K, Greenwood H, Drukteinis JS, Niell B, Fan B, Malkov S, Avila J, Kazemi L, Shepherd J. Combined Benefit of Quantitative Three-Compartment Breast Image Analysis and Mammography Radiomics in the Classification of Breast Masses in a Clinical Data Set. Radiology. 2019 03; 290(3):621-628.
    View in: PubMed
    Score: 0.195
  14. Sahiner B, Pezeshk A, Hadjiiski LM, Wang X, Drukker K, Cha KH, Summers RM, Giger ML. Deep learning in medical imaging and radiation therapy. Med Phys. 2019 Jan; 46(1):e1-e36.
    View in: PubMed
    Score: 0.195
  15. Whitney HM, Taylor NS, Drukker K, Edwards AV, Papaioannou J, Schacht D, Giger ML. Additive Benefit of Radiomics Over Size Alone in the Distinction Between Benign Lesions and Luminal A Cancers on a Large Clinical Breast MRI Dataset. Acad Radiol. 2019 02; 26(2):202-209.
    View in: PubMed
    Score: 0.188
  16. Haddad CW, Drukker K, Gullett R, Carroll TJ, Christoforidis GA, Giger ML. Fuzzy c-means segmentation of major vessels in angiographic images of stroke. J Med Imaging (Bellingham). 2018 Jan; 5(1):014501.
    View in: PubMed
    Score: 0.183
  17. Li H, Zhu Y, Burnside ES, Huang E, Drukker K, Hoadley KA, Fan C, Conzen SD, Zuley M, Net JM, Sutton E, Whitman GJ, Morris E, Perou CM, Ji Y, Giger ML. Quantitative MRI radiomics in the prediction of molecular classifications of breast cancer subtypes in the TCGA/TCIA data set. NPJ Breast Cancer. 2016; 2.
    View in: PubMed
    Score: 0.163
  18. Li H, Zhu Y, Burnside ES, Drukker K, Hoadley KA, Fan C, Conzen SD, Whitman GJ, Sutton EJ, Net JM, Ganott M, Huang E, Morris EA, Perou CM, Ji Y, Giger ML. MR Imaging Radiomics Signatures for Predicting the Risk of Breast Cancer Recurrence as Given by Research Versions of MammaPrint, Oncotype DX, and PAM50 Gene Assays. Radiology. 2016 Nov; 281(2):382-391.
    View in: PubMed
    Score: 0.163
  19. Giger ML, Inciardi MF, Edwards A, Papaioannou J, Drukker K, Jiang Y, Brem R, Brown JB. Automated Breast Ultrasound in Breast Cancer Screening of Women With Dense Breasts: Reader Study of Mammography-Negative and Mammography-Positive Cancers. AJR Am J Roentgenol. 2016 Jun; 206(6):1341-50.
    View in: PubMed
    Score: 0.162
  20. Burnside ES, Drukker K, Li H, Bonaccio E, Zuley M, Ganott M, Net JM, Sutton EJ, Brandt KR, Whitman GJ, Conzen SD, Lan L, Ji Y, Zhu Y, Jaffe CC, Huang EP, Freymann JB, Kirby JS, Morris EA, Giger ML. Using computer-extracted image phenotypes from tumors on breast magnetic resonance imaging to predict breast cancer pathologic stage. Cancer. 2016 Mar 01; 122(5):748-57.
    View in: PubMed
    Score: 0.158
  21. Schacht DV, Drukker K, Pak I, Abe H, Giger ML. Using quantitative image analysis to classify axillary lymph nodes on breast MRI: a new application for the Z 0011 Era. Eur J Radiol. 2015 Mar; 84(3):392-397.
    View in: PubMed
    Score: 0.148
  22. Drukker K, Duewer F, Giger ML, Malkov S, Flowers CI, Joe B, Kerlikowske K, Drukteinis JS, Li H, Shepherd JA. Mammographic quantitative image analysis and biologic image composition for breast lesion characterization and classification. Med Phys. 2014 Mar; 41(3):031915.
    View in: PubMed
    Score: 0.140
  23. Drukker K, Giger M, Meinel LA, Starkey A, Janardanan J, Abe H. Quantitative ultrasound image analysis of axillary lymph node status in breast cancer patients. Int J Comput Assist Radiol Surg. 2013 Nov; 8(6):895-903.
    View in: PubMed
    Score: 0.132
  24. Chen W, Metz CE, Giger ML, Drukker K. A novel hybrid linear/nonlinear classifier for two-class classification: theory, algorithm, and applications. IEEE Trans Med Imaging. 2010 Feb; 29(2):428-41.
    View in: PubMed
    Score: 0.104
  25. Drukker K, Giger ML, Metz CE. Robustness of computerized lesion detection and classification scheme across different breast US platforms. Radiology. 2005 Dec; 237(3):834-40.
    View in: PubMed
    Score: 0.079
  26. Drukker K, Giger ML, Vyborny CJ, Mendelson EB. Computerized detection and classification of cancer on breast ultrasound. Acad Radiol. 2004 May; 11(5):526-35.
    View in: PubMed
    Score: 0.071
  27. Drukker K, Giger ML, Mendelson EB. Computerized analysis of shadowing on breast ultrasound for improved lesion detection. Med Phys. 2003 Jul; 30(7):1833-42.
    View in: PubMed
    Score: 0.067
  28. Drukker K, Giger ML, Horsch K, Kupinski MA, Vyborny CJ, Mendelson EB. Computerized lesion detection on breast ultrasound. Med Phys. 2002 Jul; 29(7):1438-46.
    View in: PubMed
    Score: 0.063
  29. Leong LT, Malkov S, Drukker K, Niell BL, Sadowski P, Wolfgruber T, Greenwood HI, Joe BN, Kerlikowske K, Giger ML, Shepherd JA. Dual-energy three-compartment breast imaging for compositional biomarkers to improve detection of malignant lesions. Commun Med (Lond). 2021; 1:29.
    View in: PubMed
    Score: 0.059
  30. Yeh AC, Li H, Zhu Y, Zhang J, Khramtsova G, Drukker K, Edwards A, McGregor S, Yoshimatsu T, Zheng Y, Niu Q, Abe H, Mueller J, Conzen S, Ji Y, Giger ML, Olopade OI. Radiogenomics of breast cancer using dynamic contrast enhanced MRI and gene expression profiling. Cancer Imaging. 2019 Jul 15; 19(1):48.
    View in: PubMed
    Score: 0.051
  31. Armato SG, Huisman H, Drukker K, Hadjiiski L, Kirby JS, Petrick N, Redmond G, Giger ML, Cha K, Mamonov A, Kalpathy-Cramer J, Farahani K. PROSTATEx Challenges for computerized classification of prostate lesions from multiparametric magnetic resonance images. J Med Imaging (Bellingham). 2018 Oct; 5(4):044501.
    View in: PubMed
    Score: 0.049
  32. Sutton EJ, Huang EP, Drukker K, Burnside ES, Li H, Net JM, Rao A, Whitman GJ, Zuley M, Ganott M, Bonaccio E, Giger ML, Morris EA. Breast MRI radiomics: comparison of computer- and human-extracted imaging phenotypes. Eur Radiol Exp. 2017; 1(1):22.
    View in: PubMed
    Score: 0.045
  33. Armato SG, Drukker K, Li F, Hadjiiski L, Tourassi GD, Engelmann RM, Giger ML, Redmond G, Farahani K, Kirby JS, Petrick NA. Letter to the Editor: Use of Publicly Available Image Resources. Acad Radiol. 2017 07; 24(7):916-917.
    View in: PubMed
    Score: 0.044
  34. Armato SG, Drukker K, Li F, Hadjiiski L, Tourassi GD, Engelmann RM, Giger ML, Redmond G, Farahani K, Kirby JS, Clarke LP. LUNGx Challenge for computerized lung nodule classification. J Med Imaging (Bellingham). 2016 Oct; 3(4):044506.
    View in: PubMed
    Score: 0.043
  35. Zhu Y, Li H, Guo W, Drukker K, Lan L, Giger ML, Ji Y. Deciphering Genomic Underpinnings of Quantitative MRI-based Radiomic Phenotypes of Invasive Breast Carcinoma. Sci Rep. 2015 Dec 07; 5:17787.
    View in: PubMed
    Score: 0.040
  36. Guo W, Li H, Zhu Y, Lan L, Yang S, Drukker K, Morris E, Burnside E, Whitman G, Giger ML, Ji Y. Prediction of clinical phenotypes in invasive breast carcinomas from the integration of radiomics and genomics data. J Med Imaging (Bellingham). 2015 10; 2(4):041007.
    View in: PubMed
    Score: 0.039
  37. Armato SG, Hadjiiski L, Tourassi GD, Drukker K, Giger ML, Li F, Redmond G, Farahani K, Kirby JS, Clarke LP. LUNGx Challenge for computerized lung nodule classification: reflections and lessons learned. J Med Imaging (Bellingham). 2015 Apr; 2(2):020103.
    View in: PubMed
    Score: 0.038
  38. Kuo HC, Giger ML, Reiser I, Drukker K, Boone JM, Lindfors KK, Yang K, Edwards A. Impact of lesion segmentation metrics on computer-aided diagnosis/detection in breast computed tomography. J Med Imaging (Bellingham). 2014 Oct; 1(3):031012.
    View in: PubMed
    Score: 0.037
  39. Kuo HC, Giger ML, Reiser I, Drukker K, Boone JM, Lindfors KK, Yang K, Edwards A, Sennett CA. Segmentation of breast masses on dedicated breast computed tomography and three-dimensional breast ultrasound images. J Med Imaging (Bellingham). 2014 Apr; 1(1):014501.
    View in: PubMed
    Score: 0.035
  40. Sadinski M, Giger M, Drukker K, Yamaguchi K, Lan L, Li H. TU-E-217BCD-07: Pilot Study on Consistency in Size Metrics for a Multimodality PEM/MR Breast Imaging Approach. Med Phys. 2012 Jun; 39(6Part24):3915.
    View in: PubMed
    Score: 0.031
  41. Jamieson AR, Giger ML, Drukker K, Pesce LL. Enhancement of breast CADx with unlabeled dataa). Med Phys. 2010 Aug; 37(8):4155-4172.
    View in: PubMed
    Score: 0.027
  42. Jamieson AR, Giger ML, Drukker K, Pesce LL. Enhancement of breast CADx with unlabeled data. Med Phys. 2010 Aug; 37(8):4155-72.
    View in: PubMed
    Score: 0.027
  43. Jamieson AR, Giger ML, Drukker K, Li H, Yuan Y, Bhooshan N. Exploring nonlinear feature space dimension reduction and data representation in breast Cadx with Laplacian eigenmaps and t-SNE. Med Phys. 2010 Jan; 37(1):339-51.
    View in: PubMed
    Score: 0.026
  44. Gruszauskas NP, Drukker K, Giger ML, Chang RF, Sennett CA, Moon WK, Pesce LL. Breast US computer-aided diagnosis system: robustness across urban populations in South Korea and the United States. Radiology. 2009 Dec; 253(3):661-71.
    View in: PubMed
    Score: 0.026
  45. Gruszauskas NP, Drukker K, Giger ML, Sennett CA, Pesce LL. Performance of breast ultrasound computer-aided diagnosis: dependence on image selection. Acad Radiol. 2008 Oct; 15(10):1234-45.
    View in: PubMed
    Score: 0.024
Connection Strength

The connection strength for concepts is the sum of the scores for each matching publication.

Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.