| 3-D Active Contour Segmentation Based on Sparse Linear Combination of Training Shapes (SCoTS) MM Farhangi, H Frigui, A Seow, AA Amini IEEE transactions on medical imaging 36 (11), 2239-2249, 2017 | 52 | 2017 |
| Lung nodule malignancy prediction in sequential ct scans: Summary of isbi 2018 challenge Y Balagurunathan, A Beers, M Mcnitt-Gray, L Hadjiiski, S Napel, ... IEEE transactions on medical imaging 40 (12), 3748-3761, 2021 | 43 | 2021 |
| Segmentation and tracking of lung nodules via graph‐cuts incorporating shape prior and motion from 4D CT J Cha, MM Farhangi, N Dunlap, AA Amini Medical physics 45 (1), 297-306, 2018 | 33 | 2018 |
| Deep neural networks-based denoising models for CT imaging and their efficacy KC Prabhat, R Zeng, MM Farhangi, KJ Myers Medical Imaging 2021: Physics of Medical Imaging 11595, 105-117, 2021 | 32 | 2021 |
| Recurrent attention network for false positive reduction in the detection of pulmonary nodules in thoracic CT scans MM Farhangi, N Petrick, B Sahiner, H Frigui, AA Amini, A Pezeshk Medical physics 47 (5), 2150-2160, 2020 | 25 | 2020 |
| Multiple instance learning for malignant vs. benign classification of lung nodules in thoracic screening ct data W Safta, MM Farhangi, B Veasey, A Amini, H Frigui 2019 IEEE 16Th international symposium on biomedical imaging (ISBI 2019 …, 2019 | 22 | 2019 |
| Lung nodule malignancy classification based on NLSTx Data B Veasey, MM Farhangi, H Frigui, J Broadhead, M Dahle, A Pezeshk, ... 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI), 1870-1874, 2020 | 19 | 2020 |
| Improvement the bag of words image representation using spatial information MM Farhangi, M Soryani, M Fathy Advances in Computing and Information Technology: Proceedings of the Second …, 2013 | 19 | 2013 |
| Automatic lung nodule detection in thoracic CT scans using dilated slice‐wise convolutions MM Farhangi, B Sahiner, N Petrick, A Pezeshk Medical Physics 48 (7), 3741-3751, 2021 | 17 | 2021 |
| Informative visual words construction to improve bag of words image representation MM Farhangi, M Soryani, M Fathy IET Image Processing 8 (5), 310-318, 2014 | 15 | 2014 |
| Volumetric analysis of respiratory gated whole lung and liver CT data with motion-constrained graph cuts segmentation J won Cha, MM Farhangi, N Dunlap, A Amini 2017 39th Annual International Conference of the IEEE Engineering in …, 2017 | 10 | 2017 |
| 4D lung tumor segmentation via shape prior and motion cues J won Cha, MM Farhangi, N Dunlap, A Amini Engineering in Medicine and Biology Society (EMBC), 2016 IEEE 38th Annual …, 2016 | 8 | 2016 |
| Incorporating shape prior into active contours with a sparse linear combination of training shapes: Application to corpus callosum segmentation MM Farhangi, H Frigui, R Bert, AA Amini 2016 38th Annual International Conference of the IEEE Engineering in …, 2016 | 8 | 2016 |
| Semi‐supervised training using cooperative labeling of weakly annotated data for nodule detection in chest CT M Maynord, MM Farhangi, C Fermüller, Y Aloimonos, G Levine, N Petrick, ... Medical Physics 50 (7), 4255-4268, 2023 | 7 | 2023 |
| Detecting dataset bias in medical ai: A generalized and modality-agnostic auditing framework N Drenkow, M Pavlak, K Harrigian, A Zirikly, A Subbaswamy, ... arXiv preprint arXiv:2503.09969, 2025 | 5 | 2025 |
| Data AUDIT: Identifying Attribute Utility- and Detectability-Induced Bias in Task Models M Pavlak, N Drenkow, N Petrick, MM Farhangi, M Unberath International Conference on Medical Image Computing and Computer-Assisted …, 2023 | 5 | 2023 |
| Finding and tracking local communities by approximating derivatives in networks MA Rigi, I Moser, MM Farhangi, C Lui World Wide Web 23 (3), 1519-1551, 2020 | 5 | 2020 |
| Mammographic image conversion between source and target acquisition systems using cGAN Z Ghanian, A Badal, K Cha, MM Farhangi, N Petrick, B Sahiner International Workshop on Machine Learning in Medical Imaging, 523-531, 2020 | 3 | 2020 |
| Deciphering deep ensembles for lung nodule analysis RK Samala, B Sahiner, G Pennello, KH Cha, MM Farhangi, N Petrick Medical Imaging 2022: Computer-Aided Diagnosis 12033, 157-165, 2022 | 1 | 2022 |
| Segmentation and classification of lung nodules from Thoracic CT scans: methods based on dictionary learning and deep convolutional neural networks. MM Farhangi | 1 | 2019 |
Jungwon ChaUniversity of ArizonaVerified email at arizona.edu
Jungwon ChaUniversity of ArizonaVerified email at arizona.edu