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Image Perception, Observer Performance, and Technology Assessment 2023: San Diego, CA, USA
- Claudia R. Mello-Thoms, Yan Chen:
Medical Imaging 2023: Image Perception, Observer Performance, and Technology Assessment, San Diego, CA, USA, February 21-23, 2023. SPIE Proceedings 12467, SPIE 2023, ISBN 9781510660397
Tuesday morning Keynotes
- Mark Steyvers:
Human-AI collaboration (Conference Presentation).
Visual Search
- Stephen H. Adamo, Bruno Barufaldi, Miguel A. Lago:
Comparing experts to novices: reduced satisfaction of search when searching with virtual breast tomosynthesis. - Scott S. Hsieh, Akitoshi Inoue, Mariana Yalon, David A. Cook, Jeff L. Fidler, Hao Gong, Parvathy Sudhir Pillai, Andrew J. Vercnocke, Matthew P. Johnson, Shuai Leng, Lifeng Yu, David R. Holmes III, Rickey E. Carter, Cynthia H. McCollough, Joel G. Fletcher:
A training program to reduce reader search errors for liver metastasis detection in CT. - Weimin Zhou, Miguel P. Eckstein:
Optimal visual search strategy with inter-saccade response correlations. - George J. W. Partridge, Peter Phillips
, Adnan Taib
Challenges and solutions to processing and visualising eye tracking data from digital pathology studies.
Breast
- Adnan Taib
Identifying and preventing fatigue in digital breast tomosynthesis. - Somphone Siviengphanom, Ziba Gandomkar, Sarah J. Lewis, Patrick C. Brennan:
Global mammographic radiomic signature can predict radiologists' difficult-to-interpret normal cases. - Elly K. Gallagher, Phuong Dung Trieu, Ziba Gandomkar, Tong Li, Masoumeh Gity, Patrick C. Brennan, Sarah Lewis, Seyedamir Tavakoli Taba:
A comparative study of diagnostic performance and work experience of radiologists in three countries interpreting digital breast tomosynthesis. - Ziba Gandomkar, Sarah J. Lewis, Somphone Siviengphanom, Dennis Wong, Ernest U. Ekpo, Moayyad E. Suleiman
False-negative diagnosis might occur due to absence of the global radiomic signature of malignancy on screening mammograms. - Xuetong Tao, Somphone Siviengphanom, Ziba Gandomkar, Tong Li, Warren M. Reed
Investigating the error-making patterns in reading high-density screening mammograms between radiologists from two countries.
AI: Joint Session with Conferences 12465 and 12467
- Karen Drukker
Longitudinal robustness of a thoracic radiographic AI model for COVID-19 severity prediction. - Lin Guo
Developing and assessing an AI-based multi-task prediction system to assist radiologists detecting lung diseases in reading chest x-ray images. - Karen Drukker
Assistance tools for the evaluation of machine learning algorithm performance: the decision tree-based tools developed by the Medical Imaging and Data Resource Center (MIDRC) Technology Development Project (TDP) 3c effort.
Model observers and Statistical analyses
- Stephen L. Hillis
Obuchowski-Rockette analysis for Multi-Reader Multi-Case (MRMC) readers-nested-in-test study design with unequal numbers of readers. - Dan Li, Eric Clarkson:
Approximating the idea observer on list mode data with comparison to CNN methods. - Craig K. Abbey, Frank W. Samuelson, Rongping Zeng, John M. Boone, Miguel P. Eckstein, Kyle J. Myers:
Predictive accuracy of model observers in lesion discrimination tasks. - Kaiyan Li, Weimin Zhou, Hua Li, Mark A. Anastasio:
Estimating task-based performance bounds for image reconstruction methods by use of learned-ideal observers.
Artificial Intelligence I
- Madeleine S. Durkee, Nevaeh Petrie, Kyle Lleras, Junting Ai, Rebecca Abraham, J. Cy Chittenden, Chasity Kasir, Fiona Clark, Gabriel Casella, Marcus R. Clark, Maryellen L. Giger:
Convolutional neural networks detect cells in densely packed images at performance levels similar to human readers. - Luyan Yao, Jiefei Wei
Full-field digital mammogram retrieval using Fourier feature-based auto-encoder: application in breast cancer screening training. - Heather M. Whitney, Hui Li, Karen Drukker
Investigation of demographic implicit discrimination and disparate impact in chest radiography image-based AI for COVID-19 severity prediction. - Zhengqiang Jiang, Phuong Dung Trieu, Ziba Gandomkar, Seyedamir Tavakoli Taba, Melissa L. Barron, Sarah J. Lewis:
How do you solve a problem like concordance? a study of radiologists' clinical annotations for mammographic AI training. - Chumin Zhao, Ryan Beams, Aldo Badano:
Spatiotemporal image quality in medical extended reality.
Artificial Intelligence II
- Alireza Abdihamzehkolaei, Seyedehnafiseh Mirniaharikandehei, Angel Choquehuanca, Marco Aedo Lopez
An observer comparison study to evaluate a machine learning model to quantify the infected pneumonia on lung CT images. - Yanchen Jessie Ou, Alina Jade Barnett
A user interface to communicate interpretable AI decisions to radiologists. - Katherine Elfer, Victor Garcia, Brandon D. Gallas:
Analysis of a pilot study collecting pathologist annotations for validating machine learning algorithms. - Ziping Liu, Joyce C. Mhlanga, Barry A. Siegel, Abhinav K. Jha:
Need for objective task-based evaluation of AI-based segmentation methods for quantitative PET. - Roberto Fedrigo, Fereshteh Yousefirizi
Observer study-based evaluation of TGAN architecture used to generate oncological PET images. - Asli Kumcu, Ljiljana Platisa, Bart Goossens, Amber J. Gislason-Lee, Andrew G. Davies, Gerard Schouten, Dimitri Buytaert, Klaus Bacher, Wilfried Philips:
A visibility overshoot index for interventional x-ray image quality assessment.
Technology Assessment
- Tavianne M. Kemp, Tetsuya A. Kawakita, Rehan Mehta, Angel R. Pineda:
Optimizing data acquisition in undersampled magnetic resonance imaging (MRI) using two alternative forced choice (2-AFC) and search tasks. - Miguel A. Lago, Aldo Badano:
Adaptive Laguerre-Gauss channels for detection and search of irregularly shaped lesions. - Kirsten L. Boedeker, Daniel W. Shin, Luuk J. Oostveen, Ioannis Sechopoulos, Craig K. Abbey:
Discriminability of non-Gaussian noise properties in CT. - Lindsay Douglas, Trisha Mondal
Influence of magnet strength on background parenchymal enhancement evaluation.
Poster Session
- Patrik Sund:
Configuring medical displays for high- and stable-image contrast in bright rooms. - Mostafa Abozeed, Tom Kimpe, Seth T. Lirette, Srini Tridandapani:
Comparison of radiologists' interpretation efficiency with radiographs: standard 6 MP versus 12 MP high-resolution display monitors. - Fernanda J. F. Cardoso, Homero Schiabel
Comparative tests between actual and simulated digital mammography images for new computer schemes evaluation database. - Hilary Cintia Djuikoua Wouafo, Julie Joncas, Marjolaine Roy-Beaudry, Soraya Barchi, Stefan Parent, Hubert Labelle, Luc Duong:
Automatic assessment of skeletal maturity in adolescent idiopathic scoliosis patients using support vector regression on deep features. - Myrthe A. D. Buser, Marc H. W. A. Wijnen, Alida F. W. van der Steeg, Bas H. M. van der Velden:
Evaluation of multiparametric MRI for deep learning-based segmentation of Wilms tumor. - Giulia de Donno, Kimberley M. Timmins, Hugo J. Kuijf:
Assessment of cerebral vascular abnormality quantification technique to aid aneurysm localization. - Lucas Exposto Soares
Assessing the impact of correlated noise in digital mammography: a virtual clinical trial. - Jia Lin Chua, Qin Xiao, Tong Li, Yajia Gu, Melissa L. Robinson, Kriscia Tapia, Sarah Lewis, Phuong Dung Trieu:
Diagnostic performance characteristics of Chinese radiologists in breast cancer detection with FFDM versus DBT images. - Weimin Zhou:
Task-aware denoising autoencoders for establishing efficient channels. - Varun A. Kelkar, Dimitrios S. Gotsis, Rucha Deshpande, Frank J. Brooks, Prabhat K. C., Kyle J. Myers, Rongping Zeng, Mark A. Anastasio:
Evaluating generative stochastic image models using task-based image quality measures. - Iman Bint Talha, Oanh T. M. Tran, Due T. Ong, Thuy T. Hoang, Tuan A. Khuong, Dennis Wong, Karen Ho, Natacha Borecky, Mary Rickard, Sarah Lewis, Patrick C. Brennan, Phuong Dung Trieu:
A progress in diagnostic performances of Vietnamese doctors in reading mammograms with different Level of breast density via the VIETRAD program. - Md. Ashequr Rahman, Zitong Yu, Barry A. Siegel, Abhinav K. Jha:
A task-specific deep-learning-based denoising approach for myocardial perfusion SPECT. - Steven A. Lewis, Scott Doyle:
Attention-guided single-voxel attacks for 3-dimensional neural networks: experiments with post-mortem CT segmentation.
Digital poster Session
- Christiane Posselt
Novel concept for systematic testing of AI models for MRI acquisition shifts with simulated data. - Manish Sharma, Sree Sudha Kota, Surabhi Bajpai, Kimberly Fernandes-Thomas, Madhuri Madasu, Yibin Shao, Rajesh Kaja, Rajesh Selvaraj, Kira Cheng, Joy Luo:
Utilizing network analysis in blinded independent central review for clinical trials as adjudication agreement dashboard. - Tianrun Chen, Ying Zang, Jia Zhang, Delong Zhang:
High-quality label-free prediction of fluorescence images through stimulated Raman scattering imaging and recurrent deep neural network. - Manish Sharma, Madhuri Madasu, Surabhi Bajpai, Kimberly Fernandes-Thomas, Sree Sudha Kota, Yibin Shao, Rajesh Selvaraj, Rajesh Kaja, Kira Cheng, Joy Luo:
Predictive adjudication rate modeling for prioritizing case distribution in BICR for oncology clinical trials.
Erratum
- Yanchen Ou, Alina Jade Barnett, Anika Mitra, Fides Regina Schwartz, Chaofan Chen, Lars J. Grimm, Joseph Y. Lo, Cynthia Rudin:
A user interface to communicate interpretable AI decisions to radiologists (Erratum).
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