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Publication search results
found 41 matches
- 2020
- Craig K. Abbey, Frank W. Samuelson, Rongping Zeng, John M. Boone, Miguel P. Eckstein, Kyle J. Myers:
Human observer templates for lesion discrimination tasks. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2020: 113160U - Craig K. Abbey, Michael A. Webster, Tanya D. Geertse, Danielle van der Waal, Eric Tetteroo, Ruud Pijnappel, Mireille J. M. Broeders, Ioannis Sechopoulos:
Sequential reading effects in Dutch screening mammography. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2020: 113160G - Ramy Mohammed Abdlaty, Lillian Doerwald, Joseph Hayward, Qiyin Fang:
Spectral assessment of radiation therapy-induced skin erythema. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2020: 1131619 - Areej S. Aloufi, Abdulrahman AlNaeem, Abeer Almousa, Khaled Alzimami, Abdulrahman Alfuraih, Bader Alshahrani, Mohammed Zayed, Taghrid AlMashouq, Saud Alnasser, Khera Aldossari, Mona Alomrani, Iman Alzahrani, Elaine F. Harkness, Susan M. Astley:
Breast density in Saudi Arabia: intra and inter reader variability in screening mammograms assessed visually using BI-RADS and visual analogue scales. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2020: 113160H - Abdulaziz S. Alshabibi, Moayyad E. Suleiman, Kriscia A. Tapia, Robert Heard, Patrick C. Brennan:
Effect of time of day on radiology image interpretations. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2020: 1131608 - Alireza Nasiri Avanaki, Kathryn S. Espig, Albert Xthona, D. Brooks, J. Young, Tom Kimpe:
Perceptual image quality in digital dermoscopy. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2020: 1131614 - Kenny H. Cha, Alexej Gossmann, Nicholas Petrick, Berkman Sahiner:
Supplementing training with data from a shifted distribution for machine learning classifiers: adding more cases may not always help. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2020: 113160S - Jennie Crosby, Sophia Chen, Feng Li, Heber MacMahon, Maryellen L. Giger:
Network output visualization to uncover limitations of deep learning detection of pneumothorax. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2020: 113160O - Alexander Dabrowiecki, Alexander Villalobos, Elizabeth A. Krupinski:
Blue light filtering glasses and computer vision syndrome: a pilot study. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2020: 1131609 - Amy Van Dusen, Michael Vieceli, Karen Drukker, Hiroyuki Abe, Maryellen L. Giger, Heather M. Whitney:
Repeatability profiles towards consistent sensitivity and specificity levels for machine learning on breast DCE-MRI. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2020: 113160I - Fenglei Fan, Sangtae Ahn, Bruno De Man, Kristen A. Wangerin, Scott D. Wollenweber, Craig K. Abbey, Paul E. Kinahan:
Deep learning-based model observers that replicate human observers for PET imaging. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2020: 113160E - Jordan D. Fuhrman, Peter Halloran, Rowena Yip, Artit C. Jirapatnakul, Claudia I. Henschke, David F. Yankelevitz, Maryellen L. Giger:
Effect of observer variability and training cases on U-Net segmentation performance. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2020: 113160T - Ziba Gandomkar, Ernest U. Ekpo, Sarah J. Lewis, Moayyad E. Suleiman, Kriscia Tapia, Tong Li, Seyedamir Tavakoli Taba, Phuong Dung Trieu, Patrick C. Brennan:
Investigating the potential of a gist-sensitive computer-aided detection tool. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2020: 113160J - Qi Gao, Sui Li, Manman Zhu, Danyang Li, Zhaoying Bian, Qingwen Lv, Dong Zeng, Jianhua Ma:
Combined global and local information for blind CT image quality assessment via deep learning. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2020: 1131615 - Maryellen L. Giger:
Towards understanding perception in the latest era of AI in medical imaging (Conference Presentation). Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2020: 1131602 - Jason L. Granstedt, Weimin Zhou, Mark A. Anastasio:
Learning efficient channels with a dual loss autoencoder. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2020: 113160C - Julia Guillou, Romain Bourcier, Florent Autrusseau:
Brain vasculature segmentation based on human perception criteria. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2020: 113160Z - Minah Han, Byeongjoon Kim, Jongduk Baek:
A performance comparison of convolutional neural network based anthropomorphic model observer and linear model observer for signal-known statistically detection tasks. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2020: 1131612 - Shenghua He, Weimin Zhou, Hua Li, Mark A. Anastasio:
Learning numerical observers using unsupervised domain adaptation. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2020: 113160W - Stephen L. Hillis:
Determining Roe and Metz model parameters for simulating multireader multicase confidence-of-disease rating data based on read-data or conjectured Obuchowski-Rockette parameter estimates. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2020: 113160N - Aditya Jonnalagadda, Miguel A. Lago, Bruno Barufaldi, Predrag R. Bakic, Craig K. Abbey, Andrew D. A. Maidment, Miguel P. Eckstein:
Evaluation of convolutional neural networks for search in 1/f 2.8 filtered noise and digital breast tomosynthesis phantoms. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2020: 1131617 - Zohaib Amjad Khan, Azeddine Beghdadi, Faouzi Alaya Cheikh, Mounir Kaaniche, Egidijus Pelanis, Rafael Palomar, Åsmund Avdem Fretland, Bjørn Edwin, Ole Jakob Elle:
Towards a video quality assessment based framework for enhancement of laparoscopic videos. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2020: 113160P - Byeongjoon Kim, Minah Han, Jongduk Baek:
Convolutional neural network-based anthropomorphic model observer for breast cone-beam CT images. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2020: 113160Y - Amanda Koh, Dorina Roy, Alastair G. Gale, Raluca Mihai, Guprit Atwal, Ian O. Ellis, David R. J. Snead, Yan Chen:
Understanding digital pathology performance: an eye tracking study. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2020: 1131607 - Elizabeth A. Krupinski, Henry Zhan, Sadaf Sahraian, Elham Beheshtian, Robert E. Morales, David M. Yousem:
Where's WALDO: a potential tool for training radiology residents? Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2020: 1131605 - Matthew A. Kupinski, Zachary Garrett, Jiahua Fan:
Observer-driven texture analysis in CT imaging. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2020: 1131610 - Miguel A. Lago, Bruno Barufaldi, Predrag R. Bakic, Craig K. Abbey, Andrew D. A. Maidment, Miguel P. Eckstein:
Foveated model observer to predict human search performance on virtual digital breast tomosynthesis phantoms. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2020: 113160V - Changwoo Lee, Jongduk Baek:
Implementation of an anthropomorphic model observer using convolutional neural network for breast tomosynthesis images. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2020: 1131611 - Iris Lorente, Craig K. Abbey, Jovan G. Brankov:
Deep learning based model observer by U-Net. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2020: 113160F - Gregory Ongie, Emil Y. Sidky, Ingrid S. Reiser, Xiaochuan Pan:
Supervised learning of model observers for assessment of CT image reconstruction algorithms. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2020: 113160B
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