Studies that have used our ROC software

Some Papers appear more than once because they belong to multiple classifications



  • Metz CE, Herman BA, Roe CA. Statistical comparison of two ROC curve estimates obtained from partially-paired datasets. Med Decis Making 1998; 18:110-121.
    Comments:Uses ROCKIT to compare partially paired datasets.
  • Worling JR, Curwen T. Adolescent sexual offender recidivism: success of specialized treatment and implications for risk prediction. Child Abuse Negl 2000; 24:965-982.
    Comments:Uses ROCKIT to compare partially paired datasets.
  • Worling JR. The Estimate of Risk of Adolescent Sexual Offense Recidivism (ERASOR): preliminary psychometric data. Sex Abuse 2004; 16:235-254.
    Comments:Uses ROCKIT to compare partially paired datasets.
  • Drukker K, Giger ML, Metz CE, ‘Robustness of a computerized breast lesion detection and classification system across different ultrasound acquisition platforms’, Radiology, 237: 834-840 (2005)
  • Weijie Chen, Maryellen L. Giger, Ulrich Bick, and Gillian M. Newstead, “Automatic identification and classification of characteristic kinetic curves of breast lesions on DCE-MRI” Medical Physics 33:2878-2887 (2006)


  • Jiang Y, Nishikawa RM, Schmidt RA, Metz CE, Giger ML, Doi K. Improving breast cancer diagnosis with computer-aided diagnosis. Academic Radiology 6:22-33, 1999.
    Comments:Makes use of both LABMRMC and LABROC4
  • Shiraishi J, Abe H, Englemann R, Aoyama M, MacMahon H, Doi K: Computer-aided diagnosis for distinction between benign and malignant solitary pulmonary nodules in chest radiographs: ROC analysis of radiologists’ performance. Radiology (in press) 2003.
  • Shiraishi J, Abe H, Engelmann R, Doi K. Effect of high sensitivity in a computerized scheme for detecting extremely subtle solitary pulmonary nodules. in chest radiographs: Observer performance study. Academic Radiology 2003;10:1302-1311.
  • Li F, Aoyama M, Shiraishi J, Abe H, Li Q, Suzuki K, Engelmann R, Sone S, MacMahon H, Doi K. Radiologists’ performance for differentiating benign from malignant lung nodules on high-resolution CT using computer-estimated likelihood of malignancy. American Journal of Roentgenology 2004;183:1209-1215.
  • Li F, Arimura H, Suzuki K, Shiraishi J, Li Q, Abe H, Engelmann R, Sone S, MacMahon H, Doi K. Computer-aided detection of peripheral lung cancers missed at CT: ROC analyses without and with localization. Radiology 2005;237:684-690.


  • Jiang Y, Nishikawa RM, Wolverton DE, Metz CE, Giger ML, Schmidt RA, Vyborny CJ, Doi K.: Malignant and benign clustered microcalcifications: automated feature analysis and classification. Radiology 198:671-678, 1996
    Comments:Uses partial areas (currently not available in ROCKIT)
  • Armato SG III, Giger ML, MacMahon H: Computerized delineation and analysis of costophrenic angles in digital chest radiographs. Academic Radiology 5: 329-335, 1998.
  • Gilhuijs KGA, Giger ML, Bick U: Automated analysis of breast lesions in three dimensions using dynamic magnetic resonance imaging. Medical Physics 25:1647-1654, 1998.
  • Shiraishi J, Katsuragawa S, Ikezoe J, Matsumoto T, Kobayashi T, Komatsu K, Matsui M, Fujita H, Kodera Y, Doi K: Development of a digital image database for chest radiographs with and without a lung nodule: receiver operating characteristic analysis of radiologists’ detection of pulmonary nodules. AJR 174:71-74, 2000.
  • Huo Z, Giger ML, Vyborny CJ: Computerized analysis of multiple-mammographic views: potential usefulness of special view mammograms in computer-aided diagnosis. IEEE Transactions on Medical Imaging 20: 1285-1292, 2001.
    Comments:Uses also CLABROC (now fully included in ROCKIT)
  • Armato SG III, Li F, Giger ML, MacMahon H, Sone S, Doi K: Lung cancer: Performance of automated lung nodule detection applied to cancers missed in a CT screening program. Radiology 225: 685-692, 2002
  • Drukker K, Giger ML, Horsch K, Kupinski MA, Vyborny CJ and Mendelson EB: Computerized lesion detection on breast ultrasound. MedPhys 29 (7), 1438, (2002)
    Comments:LABROC4 is currently easier to interface to Matlab than ROCKIT
  • Huo Z, Giger ML, Vyborny CJ, Metz CE: Effectiveness of CAD in the diagnosis of breast cancer: An observer study on an independent database of mammograms Radiology 224:560-568, 2002.
    Comments:Uses also CLABROC (now fully included in ROCKIT)
  • Armato SG III, Altman MB, La Rivière PJ: Automated detection of lung nodules in CT scans: effect of image reconstruction algorithm. MedPhys 30 (3): 461-472 MAR 2003
  • Drukker K, Horsch K, Giger ML, ‘Multi-modality computerized diagnosis of breast lesions using mammography and sonography’, Academic Radiology 12, 970-979, (2005)


  • Edwards DC, Kupinski MA, Metz CE, and Nishikawa RM:
    Maximum likelihood fitting of FROC curves under an initial-detection-and-candidate-analysis model, Med. Phys. 29, 2861-2870 (2002).
    Comments:Uses both PROPROC and LABROC4
  • Abe H, MacMahon H, Engelmann R, Li Q, Shiraishi J, Katsuragawa S, Aoyama M, Ishida T, Ashizawa K, Metz C, Doi K: Computer-aided diagnosis in chest radiology: results of large-scale observer tests performed at the 1996-2001 RSNA Scientific Assemblies. RadioGraphics, 23:255-265, 2003.
  • Edwards DC, Lan L, Metz CE, Giger ML, and Nishikawa RM, Estimating three-class ideal observer decision variables for computerized detection and classification of mammographic mass lesions. Med. Phys. 31, pp. 81-90, 2004
  • Snoeijs MGJ, Schaefer S, Christiaans MH, et al.
    Kidney transplantation using elderly non-heart-beating donors: A single-center experience AMERICAN JOURNAL OF TRANSPLANTATION 6 (5): 1066-1071 Part 1 MAY 2006