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John Papaioannou
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2020 – today
- 2020
- [c14]Karen Drukker, Alexandra Edwards, John Papaioannou, Maryellen L. Giger:
Deep learning predicts breast cancer recurrence in analysis of consecutive MRIs acquired during the course of neoadjuvant chemotherapy. Computer-Aided Diagnosis 2020
2010 – 2019
- 2019
- [c13]Heather M. Whitney, Yu Ji, Hui Li, Alexandra Edwards, John Papaioannou, Peifang Liu, Maryellen L. Giger:
Effect of diversity of patient population and acquisition systems on the use of radiomics and machine learning for classification of 2, 397 breast lesions. Computer-Aided Diagnosis 2019: 109501A - [c12]Karen Drukker, Iman El-Bawab, Alexandra Edwards, Christopher Doyle, John Papaioannou, Kirti Kulkarni, Maryellen L. Giger:
Breast MRI radiomics for the pre-treatment prediction of response to neoadjuvant chemotherapy in node-positive breast cancer patients. Computer-Aided Diagnosis 2019: 109502N - [c11]Qiyuan Hu, Heather M. Whitney, Alexandra Edwards, John Papaioannou, Maryellen L. Giger:
Radiomics and deep learning of diffusion-weighted MRI in the diagnosis of breast cancer. Computer-Aided Diagnosis 2019: 109504A - 2018
- [c10]Heather M. Whitney, Karen Drukker, Alexandra Edwards, John Papaioannou, Maryellen L. Giger:
Effect of biopsy on the MRI radiomics classification of benign lesions and luminal A cancers. IWBI 2018: 107180H - [c9]Heather M. Whitney, Karen Drukker, Alexandra Edwards, John Papaioannou, Maryellen L. Giger:
Robustness of radiomic breast features of benign lesions and luminal A cancers across MR magnet strengths. Computer-Aided Diagnosis 2018: 105750A - [c8]Karen Drukker, Rachel Anderson, Alexandra Edwards, John Papaioannou, Fred Pineda, Hiroyuki Abe, Gregory Karzcmar, Maryellen L. Giger:
Radiomics for ultrafast dynamic contrast-enhanced breast MRI in the diagnosis of breast cancer: a pilot study. Computer-Aided Diagnosis 2018: 105753U - 2012
- [j1]Alexandros Karakos, John Papaioannou, Anastasia Georgiadou:
Learning the Greek Language via Greeklish. IxD&A 15: 31-39 (2012)
2000 – 2009
- 2004
- [c7]Sophie Paquerault, Laura M. Yarusso, John Papaioannou:
Potential improvement of computerized classification for malignant versus benign mammographic microcalcification clusters with the use of special views. Image Processing 2004 - 2002
- [c6]Robert M. Nishikawa, Maria Fernanda Salfity, Yulei Jiang, John Papaioannou:
Improving the automated classification of clustered calcifications on mammograms through the improved detection of individual calcifications. Image Processing 2002 - 2001
- [c5]Darrin C. Edwards, John Papaioannou, Yulei Jiang, Matthew A. Kupinski, Robert M. Nishikawa:
Eliminating false-positive microcalcification clusters in a mammography CAD scheme using a Bayesian neural network. Image Processing 2001
1990 – 1999
- 1998
- [c4]Robert M. Nishikawa, Maryellen L. Giger, Dulcy E. Wolverton, Robert A. Schmidt, Christopher E. Comstock, John Papaioannou, Stephen A. Collins, Kunio Doi:
Prospective Testing of a Clinical Mammography Workstation for CAD: Analysis of the First 10, 000 Cases. Digital Mammography / IWDM 1998: 401-406 - [c3]Yulei Jiang, Robert M. Nishikawa, John Papaioannou:
Requirement of microcalcification detection for computerized classification of malignant and benign clustered microcalcifications. Image Processing 1998 - 1996
- [c2]Robert M. Nishikawa, John Papaioannou, Stephen A. Collins:
Reproducibility of an automated scheme for the detection of clustered microcalcifications on digital mammograms. Image Processing 1996 - 1993
- [c1]Chi-haur Wu, S. David Stulberg, John Papaioannou, Hsiang-Yun Huang, Kao-Shing Hwang, Tom Kienzle:
An Integrated CT-Imaging, CAD-Based System for Orthopedic Surgery. ICRA (1) 1993: 895-900
Coauthor Index
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