Timeline Slider Archive - Page 2 of 3 - Lab of Medical Imaging and Computation

2013

Lee S, Shima A, Singh S, Kalra MK, Kim H-J, Do S. Co-registered image quality comparison in hybrid iterative reconstruction techniques: SAFIRE and SafeCT, in SPIE Medical Imaging. ; 2013 :86683G–86683G. Näppi JJ, Do S, Yoshida H. Computer-Aided Detection of Colorectal Lesions with Super-Resolution CT Colonography: Pilot Evaluation. In: Abdominal Imaging. Computation and Clinical Applications. Springer Berlin Heidelberg…

2014

Do S, Pourjabbar S, Khawaja R, Padole A, Singh S, Kalra M. Texturization: A Generalized Image Quality Comparison Method, in The Third International Conference on Image Formation in X-ray Computed Tomography. Vol 3. Salt Lake City, UT: University of Utah ; 2014. Do S, Karl WC, Singh S, Kalra M, Brady T, Shin E, Pien H. High Fidelity…

2015

Padole AMD, Singh SMD, Lira DMD, Blake MAMD, Pourjabbar SMD, Khawaja RDAMD, Choy, Garry MD MBA, Saini SMD, Do SPD, Kalra MKMD. Assessment of Filtered Back Projection, Adaptive Statistical, and Model-Based Iterative Reconstruction for Reduced Dose Abdominal Computed Tomography. Journal of Computer Assisted Tomography. 2015;39 (4) :462-467. Cho J, Lee K, Shin E, Choy G,…

2016

Do S. The future of artificial intelligence for physicians (인공지능과 의사의 미래). J Korean Med Assoc [Internet]. 2016;59 (6) :410-412.

2017

Lee, H., Troschel, F.M., Tajmir, S. et al. Pixel-Level Deep Segmentation: Artificial Intelligence Quantifies Muscle on Computed Tomography for Body Morphometric Analysis. J Digit Imaging (2017). doi:10.1007/s10278-017-9988-z. Cho J, Lee E, Lee H, Liu B, Li X, Tajmir S, Sahani D, Do S. Machine Learning Powered Automatic Organ Classification for Patient Specific Organ Dose Estimation….

2018

Lee, H., Yune, S., Mansouri, M., Kim, M., Tajmir, S., Guerrier, C., Ebert, S., Pomerantz, S., Romero, J., Kamalian, S., Gonzalez, R., Lev, M., Do, S. An explainable deep-learning algorithm for the detection of acute intracranial haemorrhage from small datasets. Nature Biomedical Engineering, Pp. 1-10. 12/17/2018. Lee, H., Kim, M., Do, S. Practical Window Setting Optimization for…

2019

Tajmir, Shahein H., Hyunkwang Lee, Randheer Shailam, Heather I. Gale, Jie C. Nguyen, Sjirk J. Westra, Ruth Lim, Sehyo Yune, Michael S. Gee, and Synho Do. “Artificial intelligence-assisted interpretation of bone age radiographs improves accuracy and decreases variability.” Skeletal Radiology 48, no. 2 (2019): 275-283. Parakh, Anushri, Hyunkwang Lee, Jeong Hyun Lee, Brian H. Eisner, Dushyant V….

2020

Sim, Yongsik, Myung Jin, Chung, Elmar, Kotter, Sehyo, Yune, Myeongchan, Kim, Synho, Do, Kyunghwa, Han, Hanmyoung, Kim, Seungwook, Yang, Dong-Jae, Lee, and Byoung Wook, Choi. “Deep Convolutional Neural Network–based Software Improves Radiologist Detection of Malignant Lung Nodules on Chest Radiographs”.Radiology 294, no.1 (2020): 199-209. Synho, Do, Song, Kyoung Doo, Chung, Joo Won . “Basics of…

2021

Witowski, Jan, Jongmun, Choi, Soomin, Jeon, Doyun, Kim, Joowon, Chung, John, Conklin, Maria Gabriela Figueiro, Longo, Marc D, Succi, and Synho, Do. “MarkIt: A Collaborative Artificial Intelligence Annotation Platform Leveraging Blockchain For Medical Imaging Research”.Blockchain Healthc Today 4 (2021). Doyun, Kim, Joowon, Chun, Jongnum, Choi, Marc, Succi, John, Conklin, Maria, Figueiro, Jeanne, Ackman, Brent, Little,…

2022

Kim, Doyun, Joowon Chung, Jongmun Choi, Marc D. Succi, John Conklin, Maria Gabriela Figueiro Longo, Jeanne B. Ackman, Brent P. Little, Milena Petranovic, Mannudeep K. Kalra, Michael H. Lev, and Synho Do. “Accurate auto-labeling of chest X-ray images based on quantitative similarity to an explainable AI model.” Nature Communications 13, no. 1 (2022): 1867. Jongmun…