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| COVID-19 neuropathology at columbia university irving medical center/New York presbyterian hospital KT Thakur, EH Miller, MD Glendinning, O Al-Dalahmah, MA Banu, ... Brain 144 (9), 2696-2708, 2021 | 343 | 2021 |
| Quantitative imaging biomarkers alliance (QIBA) recommendations for improved precision of DWI and DCE‐MRI derived biomarkers in multicenter oncology trials A Shukla‐Dave, NA Obuchowski, TL Chenevert, S Jambawalikar, ... Journal of Magnetic Resonance Imaging 49 (7), e101-e121, 2019 | 336 | 2019 |
| Hand recognition using geometric classifiers Y Bulatov, S Jambawalikar, P Kumar, S Sethia International Conference on Biometric Authentication, 753-759, 2004 | 151 | 2004 |
| Cardiac-specific conversion factors to estimate radiation effective dose from dose-length product in computed tomography S Trattner, S Halliburton, CM Thompson, Y Xu, A Chelliah, ... JACC: Cardiovascular Imaging 11 (1), 64-74, 2018 | 148 | 2018 |
| Prior to initiation of chemotherapy, can we predict breast tumor response? Deep learning convolutional neural networks approach using a breast MRI tumor dataset R Ha, C Chin, J Karcich, MZ Liu, P Chang, S Mutasa, E Pascual Van Sant, ... Journal of digital imaging 32, 693-701, 2019 | 130 | 2019 |
| Predicting breast cancer molecular subtype with MRI dataset utilizing convolutional neural network algorithm R Ha, S Mutasa, J Karcich, N Gupta, E Pascual Van Sant, J Nemer, M Sun, ... Journal of digital imaging 32, 276-282, 2019 | 112 | 2019 |
| Investigating the mechanical function of the cervix during pregnancy using finite element models derived from high-resolution 3D MRI M Fernandez, M House, S Jambawalikar, N Zork, J Vink, R Wapner, ... Computer methods in biomechanics and biomedical engineering 19 (4), 404-417, 2016 | 104 | 2016 |
| Convolutional neural networks for the detection and measurement of cerebral aneurysms on magnetic resonance angiography JN Stember, P Chang, DM Stember, M Liu, J Grinband, CG Filippi, ... Journal of digital imaging 32, 808-815, 2019 | 97 | 2019 |
| Radiomics of MRI for pretreatment prediction of pathologic complete response, tumor regression grade, and neoadjuvant rectal score in patients with locally advanced rectal … H Shaish, A Aukerman, R Vanguri, A Spinelli, P Armenta, S Jambawalikar, ... European radiology 30, 6263-6273, 2020 | 95 | 2020 |
| Diffusion tensor imaging of peripheral nerves S Jambawalikar, J Baum, T Button, H Li, V Geronimo, ES Gould Skeletal radiology 39, 1073-1079, 2010 | 89 | 2010 |
| The role of initial chest X-ray in triaging patients with suspected COVID-19 during the pandemic HW Kim, KM Capaccione, G Li, L Luk, RS Widemon, O Rahman, ... Emergency radiology 27, 617-621, 2020 | 78 | 2020 |
| Axillary lymph node evaluation utilizing convolutional neural networks using MRI dataset R Ha, P Chang, J Karcich, S Mutasa, R Fardanesh, RT Wynn, MZ Liu, ... Journal of digital imaging 31, 851-856, 2018 | 72 | 2018 |
| Eye tracking for deep learning segmentation using convolutional neural networks JN Stember, H Celik, E Krupinski, PD Chang, S Mutasa, BJ Wood, ... Journal of digital imaging 32, 597-604, 2019 | 65 | 2019 |
| Convolutional neural network using a breast MRI tumor dataset can predict oncotype Dx recurrence score R Ha, P Chang, S Mutasa, J Karcich, S Goodman, E Blum, K Kalinsky, ... Journal of Magnetic Resonance Imaging 49 (2), 518-524, 2019 | 65 | 2019 |
| Segmentation of brain tumors using DeepLabv3+ A Roy Choudhury, R Vanguri, SR Jambawalikar, P Kumar Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries …, 2019 | 65 | 2019 |
| Dynamic infrared imaging for the detection of malignancy TM Button, H Li, P Fisher, R Rosenblatt, K Dulaimy, S Li, B O'Hea, ... Physics in Medicine & Biology 49 (14), 3105, 2004 | 61 | 2004 |
| The international workshop on osteoarthritis imaging knee MRI segmentation challenge: a multi-institute evaluation and analysis framework on a standardized dataset AD Desai, F Caliva, C Iriondo, A Mortazi, S Jambawalikar, U Bagci, ... Radiology: Artificial Intelligence 3 (3), e200078, 2021 | 60 | 2021 |
| Convolutional neural network based breast cancer risk stratification using a mammographic dataset R Ha, P Chang, J Karcich, S Mutasa, EP Van Sant, MZ Liu, ... Academic radiology 26 (4), 544-549, 2019 | 56 | 2019 |
| Convolutional neural network detection of axillary lymph node metastasis using standard clinical breast MRI T Ren, R Cattell, H Duanmu, P Huang, H Li, R Vanguri, MZ Liu, ... Clinical breast cancer 20 (3), e301-e308, 2020 | 46 | 2020 |
