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ORCIDMedical Imaging: Image Perception, Observer Performance, and Technology Assessment 2022: San Diego, CA, USA
- Claudia R. Mello-Thoms, Sian Taylor-Phillips:
Medical Imaging 2022: Image Perception, Observer Performance, and Technology Assessment, San Diego, CA, USA, February 20-24, 2022 / Online, March 21-27, 2022. SPIE Proceedings 12035, SPIE 2022, ISBN 9781510649453
Artificial Intelligence
- Gopichandh Danala, Seyedehnafiseh Mirniaharikandehei, Meredith A. Jones, Tiancheng Gai, Sai Kiran Reddy Maryada, Dee Wu, Yuchen Qiu, Bin Zheng:
Developing interactive computer-aided detection tools to support translational clinical research. - Iris N. Vos, Maud E. H. Ophelders, Ynte M. Ruigrok, Birgitta K. Velthuis, Hugo J. Kuijf:
Assessment of manual and automated intracranial artery diameter measurements. - Craig K. Abbey, Sourya Sengupta, Weimin Zhou, Andreu Badal, Rongping Zeng, Frank W. Samuelson, Miguel P. Eckstein, Kyle J. Myers, Mark A. Anastasio, Jovan G. Brankov:
Analyzing neural networks applied to an anatomical simulation of the breast. - Darrin W. Byrd, Dennis Bontempi, Hao Yang, Hugo J. W. L. Aerts, Binzhang Zhao, Andrey Fedorov, Lawrence H. Schwartz, Tavis Allison, Chaya Moscowitz, Paul E. Kinahan:
Using virtual clinical trials to determine the accuracy of AI-based quantitative imaging biomarkers in oncology trials using standard-of-care CT. - Alina Jade Barnett, Vaibhav Sharma, Neel Gajjar, Jerry Fang, Fides Regina Schwartz
, Chaofan Chen, Joseph Y. Lo, Cynthia Rudin:
Interpretable deep learning models for better clinician-AI communication in clinical mammography.
Image perception I
- George J. W. Partridge, Peter Phillips, Iain T. Darker, Yan Chen:
Investigating reading strategies and eye behaviours associated with high diagnostic performance when reading digital breast tomosynthesis (DBT) images. - Manish Sharma, Sree Sudha Kota, Madhuri Madasu, Surabhi Bajpai, Yibin Shao, Srinivas Pasupuleti, Michael O'Connor:
Satisfaction of search (SOS) error and new lesions identification on imaging in central review for clinical trials.
Model observers
- Gregory Ongie, Emil Y. Sidky, Ingrid S. Reiser, Xiaochuan Pan:
Optimizing model observer performance in learning-based CT reconstruction. - Weimin Zhou, Miguel P. Eckstein:
A deep Q-learning method for optimizing visual search strategies in backgrounds of dynamic noise. - Parvathy Sudhir Pillai, Scott S. Hsieh, David R. Holmes III, Rickey E. Carter, Joel G. Fletcher, Cynthia H. McCollough:
Individualized and generalized learner models for predicting missed hepatic metastases. - Zitong Yu, Md. Ashequr Rahman, Abhinav K. Jha:
Investigating the limited performance of a deep-learning-based SPECT denoising approach: an observer-study-based characterization.
Observer Performance and ROC Methods
- Stephen L. Hillis:
Identical-test Roe and Metz simulation model for validating multi-reader methods of analysis for comparing different radiologic imaging modalities. - Natalie M. Baughan, Heather M. Whitney, Karen Drukker, Berkman Sahiner, Tingting Hu, Hyun J. Grace Kim, Michael F. McNitt-Gray, Kyle J. Myers, Maryellen L. Giger:
Sequestration of imaging studies in MIDRC: a multi-institutional data commons. - Brian J. Smith, Stephen L. Hillis:
MATLAB toolbox for ROC analysis of multi-reader multi-case diagnostic imaging studies. - Phuong Dung (Yun) Trieu, Jennifer Noakes, Natacha Borecky, Tong Li, Patrick C. Brennan, Melissa L. Barron, Sarah J. Lewis:
Diagnostic performances of radiology trainees in reading digital breast tomosynthesis and the synthesized view. - Don J. Nocum, John W. Robinson, Mark Halaki, Magnus Båth, Nejc Mekis, Eisen Liang, Nadine Thompson, Michelle Moscova, Warren M. Reed:
Visual grading characteristic (VGC) analysis of uterine artery embolisation (UAE) image quality assessment by interventional radiologists and interventional radiographers. - Manish Sharma, Madhuri Madasu, Sree Sudha Kota, Surabhi Bajpai, Yibin Shao, Srinivas Pasupuleti, Michael O'Connor:
Using reader disagreement index as a tool for monitoring impact on read quality due to reader fatigue in central reviewers.
Monday morning Keynotes
- Elizabeth A. Krupinski:
In between are the doors of perception.
Technology Assessment
- Areej S. Aloufi, Abdulrahman AlNaeem, Abeer Almousa, Mehreen Malik, Amani Hashem, Fatina Altahan, Mahmoud Elsharkawi, Manal ElMahdy, Reham Altokhais, Sara Alsultan, Rasha Sahloul, Khaled Alzimami, Steven Squires, Elaine F. Harkness, Susan M. Astley:
Breast density distribution among the Saudi screening population and correlation between radiologist visual assessment and two automated methods. - Ziping Liu, Zekun Li, Joyce C. Mhlanga, Barry A. Siegel, Abhinav K. Jha:
No-gold-standard evaluation of quantitative imaging methods in the presence of correlated noise. - Craig K. Abbey, Junyuan Li, Grace J. Gang, J. Webster Stayman:
Assessment of boundary discrimination performance in a printed phantom. - Varun A. Kelkar, Dimitrios S. Gotsis, Frank J. Brooks, Kyle J. Myers, Prabhat K. C., Rongping Zeng, Mark A. Anastasio:
Evaluating procedures for establishing generative adversarial network-based stochastic image models in medical imaging.
Translation of CAD-AI Methods to Clinical Practice: are we there yet? Joint Session with Conferences 12033 and 12035
- Katharina Hoebel, Christopher P. Bridge, Sara Ahmed, Oluwatosin Akintola, Caroline Chung, Raymond Y. Huang, Jason Johnson, Albert Kim, K. Ina Ly, Ken Chang, Jay B. Patel, Marco Pinho, Tracy Batchelor, Bruce R. Rosen, Elizabeth R. Gerstner, Jayashree Kalpathy-Cramer:
Is this good enough? On expert perception of brain tumor segmentation quality. - Yee Lam Elim Thompson, Gary Levine, Weijie Chen, Berkman Sahiner, Qin Li, Nicholas Petrick, Frank W. Samuelson:
Wait-time-saving analysis and clinical effectiveness of computer-aided triage and notification (CADt) devices based on queueing theory.
Image perception II
- Ziba Gandomkar, Somphone Siviengphanom, Moayyad E. Suleiman, Dennis Wong, Warren M. Reed, Ernest U. Ekpo, Dong Xu, Sarah J. Lewis, Patrick C. Brennan:
The reliability of radiologists' first impression interpreting a screening mammogram. - Basel A. Qenam, Tong Li, Patrick C. Brennan:
Test-set training is linked to increased breast screening cancer detection rates. - Lauren H. Williams, Megan Mills, Ann J. Carrigan, Anina N. Rich, Trafton Drew:
Experience does not protect against missed incidental-findings in radiology.
Poster Session
- Gopichandh Danala, Sai Kiran Reddy Maryada, Huong Pham, Warid Islam, Meredith A. Jones, Bin Zheng:
Comparison of performance in breast lesions classification using radiomics and deep transfer learning: an assessment study. - Heather M. Whitney, Karen Drukker, Hiroyuki Abe, Maryellen L. Giger:
Case-based repeatability and operating point variability of AI: breast lesion classification based on deep transfer learning. - Seyedehnafiseh Mirniaharikandehei, Alan B. Hollingsworth, Meredith A. Jones, Hong Liu, Yuchen Qiu, Bin Zheng:
Assessment of a new CAD-generated imaging marker to predict risk of having mammography-occult tumors. - Minah Han, Jongduk Baek:
Low-dose CT denoising via CNN trained using images with activation map. - Ilya Pershin, Maksim Kholiavchenko, Bulat Maksudov, Tamerlan Mustafaev, Bulat Ibragimov:
AI-based analysis of radiologist's eye movements for fatigue estimation: a pilot study on chest X-rays. - Denilson Sampén, Roberto J. Lavarello:
Comparison of deep learning architectures for COVID-19 diagnosis using chest X-ray images. - Kaiyan Li, Hua Li, Mark A. Anastasio:
A task-informed model training method for deep neural network-based image denoising. - Alexandra G. O'Neill, Sajan Goud Lingala, Angel R. Pineda:
Predicting human detection performance in magnetic resonance imaging (MRI) with total variation and wavelet sparsity regularizers. - Jason L. Granstedt, Fu Li, Umberto Villa, Mark A. Anastasio:
Learned Hotelling observers for use with multi-modal data. - Dan Li, Eric Clarkson:
Performance of list mode Hotelling observer and comparison to a neural network observer. - Sourya Sengupta, Craig K. Abbey, Kaiyan Li, Mark A. Anastasio:
Investigation of adversarial robust training for establishing interpretable CNN-based numerical observers. - Wonkyeong Lee, Eunbyeol Cho, Wonjin Kim, Jang-Hwan Choi:
Performance evaluation of image quality metrics for perceptual assessment of low-dose computed tomography images. - Satvika Bharadwaj, Komal N. Shah, Yifan Zhao, Aparna Harindranath, Arun George, Kajoli Banerjee Krishnan, Manish Arora:
Semi-blinded freehand 3D ultrasound with novice users. - Xuetong Tao, Ziba Gandomkar, Tong Li, Warren M. Reed, Patrick C. Brennan:
Varying performance levels for diagnosing mammographic images depending on reader nationality have AI and educational implications. - Wing Lam Chiu, Tong Li, Sarah J. Lewis:
Diagnostic efficacy in screening mammograms does not improve with peer reading strategy: a Sino-Australian study. - Irene Hernández-Girón, Touko Kaasalainen, Teemu Mäkelä, Juha I. Peltonen, Mika Kortesniemi:
Influence of deep learning reconstruction on task-based model observer performance in CT: an anthropomorphic head phantom study. - Emily L. Marshall, Daniela Olivera Velarde, Natalie M. Baughan, Nikolaj Reiser, Chao Guo, Juan-Pablo Cruz-Bastida, Kate A. Feinstein, Ingrid S. Reiser:
Task-specific evaluation of clinical pediatric fluoroscopy systems. - Luuk J. Oostveen, Kirsten L. Boedeker, Daniel W. Shin, Craig K. Abbey, Ioannis Sechopoulos:
Visibility of noise texture changes in CT images. - Ayaan Haque, Adam S. Wang, Abdullah-Al-Zubaer Imran:
Noise2Quality: non-reference, pixel-wise assessment of low dose CT image quality. - Ming Li, Nicole Varble, Baris Turkbey, Sheng Xu, Bradford J. Wood:
Camera-based distance detection and contact tracing to monitor potential spread of COVID-19. - Theresa X. Pham, Grace G. Zhu, Soham Banerjee, William F. Auffermann:
High volume chest radiography to facilitate pulmonary nodule identification on chest radiographs.
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