|Current applications and future impact of machine learning in radiology|
G Choy, O Khalilzadeh, M Michalski, S Do, AE Samir, OS Pianykh, ...
Radiology 288 (2), 318-328, 2018
|Artificial intelligence and machine learning in radiology: opportunities, challenges, pitfalls, and criteria for success|
JH Thrall, X Li, Q Li, C Cruz, S Do, K Dreyer, J Brink
Journal of the American College of Radiology 15 (3), 504-508, 2018
|Abdominal CT: comparison of adaptive statistical iterative and filtered back projection reconstruction techniques|
S Singh, MK Kalra, J Hsieh, PE Licato, S Do, HH Pien, MA Blake
Radiology 257 (2), 373-383, 2010
|Fully automated deep learning system for bone age assessment|
H Lee, S Tajmir, J Lee, M Zissen, BA Yeshiwas, TK Alkasab, G Choy, ...
Journal of digital imaging 30, 427-441, 2017
|How much data is needed to train a medical image deep learning system to achieve necessary high accuracy?|
J Cho, K Lee, E Shin, G Choy, S Do
arXiv preprint arXiv:1511.06348, 2015
|An explainable deep-learning algorithm for the detection of acute intracranial haemorrhage from small datasets|
H Lee, S Yune, M Mansouri, M Kim, SH Tajmir, CE Guerrier, SA Ebert, ...
Nature biomedical engineering 3 (3), 173-182, 2019
|Diffuse lung disease: CT of the chest with adaptive statistical iterative reconstruction technique|
P Prakash, MK Kalra, JB Ackman, SR Digumarthy, J Hsieh, S Do, ...
Radiology 256 (1), 261-269, 2010
|Deep convolutional neural network–based software improves radiologist detection of malignant lung nodules on chest radiographs|
Y Sim, MJ Chung, E Kotter, S Yune, M Kim, S Do, K Han, H Kim, S Yang, ...
Radiology 294 (1), 199-209, 2020
|Comparison of hybrid and pure iterative reconstruction techniques with conventional filtered back projection: dose reduction potential in the abdomen|
S Singh, MK Kalra, S Do, JB Thibault, H Pien, OOJ Connor, MA Blake
Journal of computer assisted tomography 36 (3), 347-353, 2012
|Pixel-level deep segmentation: artificial intelligence quantifies muscle on computed tomography for body morphometric analysis|
H Lee, FM Troschel, S Tajmir, G Fuchs, J Mario, FJ Fintelmann, S Do
Journal of digital imaging 30, 487-498, 2017
|Coronary artery plaques: cardiac CT with model-based and adaptive-statistical iterative reconstruction technique|
H Scheffel, P Stolzmann, CL Schlett, LC Engel, GP Major, M Károlyi, S Do, ...
European journal of radiology 81 (3), e363-e369, 2012
|Artificial intelligence-assisted interpretation of bone age radiographs improves accuracy and decreases variability|
SH Tajmir, H Lee, R Shailam, HI Gale, JC Nguyen, SJ Westra, R Lim, ...
Skeletal radiology 48, 275-283, 2019
|Sinogram-affirmed iterative reconstruction of low-dose chest CT: effect on image quality and radiation dose|
MK Kalra, M Woisetschläger, N Dahlström, S Singh, S Digumarthy, S Do, ...
American Journal of Roentgenology 201 (2), W235-W244, 2013
|Histogram analysis of lipid-core plaques in coronary computed tomographic angiography: ex vivo validation against histology|
CL Schlett, P Maurovich-Horvat, M Ferencik, H Alkadhi, P Stolzmann, ...
Investigative Radiology 48 (9), 646-653, 2013
|Multi GPU implementation of iterative tomographic reconstruction algorithms|
B Jang, D Kaeli, S Do, H Pien
2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro …, 2009
|Basics of deep learning: a radiologist's guide to understanding published radiology articles on deep learning|
S Do, KD Song, JW Chung
Korean journal of radiology 21 (1), 33-41, 2020
|Computed Tomography (CT) of the Chest at Less Than 1 mSv: An Ongoing Prospective Clinical Trial of Chest CT at Submillisievert Radiation Doses with Iterative Model Image …|
RDA Khawaja, S Singh, M Gilman, A Sharma, S Do, S Pourjabbar, ...
Journal of computer assisted tomography 38 (4), 613-619, 2014
|Urinary stone detection on CT images using deep convolutional neural networks: evaluation of model performance and generalization|
A Parakh, H Lee, JH Lee, BH Eisner, DV Sahani, S Do
Radiology: Artificial Intelligence 1 (4), e180066, 2019
|Submillisievert chest CT with filtered back projection and iterative reconstruction techniques|
A Padole, S Singh, JB Ackman, C Wu, S Do, S Pourjabbar, RDA Khawaja, ...
American Journal of Roentgenology 203 (4), 772-781, 2014
|Ultra-low dose abdominal MDCT: using a knowledge-based Iterative Model Reconstruction technique for substantial dose reduction in a prospective clinical study|
RDA Khawaja, S Singh, M Blake, M Harisinghani, G Choy, ...
European journal of radiology 84 (1), 2-10, 2015