Table of Contents

• Predictive accuracy of model observers in lesion discrimination tasksCraig K. Abbey, Frank W. Samuelson, Rongping Zeng, John M. Boone, Miguel P. Eckstein, Kyle J. Myers. [doi]
• Human-AI collaboration (Conference Presentation)Mark Steyvers. [doi]
• Assessment of cerebral vascular abnormality quantification technique to aid aneurysm localizationGiulia de Donno, Kimberley M. Timmins, Hugo J. Kuijf. [doi]
• Full-field digital mammogram retrieval using Fourier feature-based auto-encoder: application in breast cancer screening trainingLuyan Yao, Jiefei Wei, Xin Chen, Yan Chen 0012. [doi]
• Estimating task-based performance bounds for image reconstruction methods by use of learned-ideal observersKaiyan Li 0002, Weimin Zhou, Hua Li 0003, Mark A. Anastasio. [doi]
• A progress in diagnostic performances of Vietnamese doctors in reading mammograms with different Level of breast density via the VIETRAD programIman 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 0001, Patrick C. Brennan, Phuong Dung Trieu. [doi]
• Convolutional neural networks detect cells in densely packed images at performance levels similar to human readersMadeleine 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. [doi]
• How do you solve a problem like concordance? a study of radiologists' clinical annotations for mammographic AI trainingZhengqiang Jiang, Phuong Dung Trieu, Ziba Gandomkar, Seyedamir Tavakoli Taba, Melissa L. Barron, Sarah J. Lewis 0001. [doi]
• Challenges and solutions to processing and visualising eye tracking data from digital pathology studiesGeorge J. W. Partridge, Peter Phillips, Adnan Taib, Yan Chen 0012. [doi]
• Investigation of demographic implicit discrimination and disparate impact in chest radiography image-based AI for COVID-19 severity predictionHeather M. Whitney, Hui Li 0024, Karen Drukker, Michael Reeve, Maryellen L. Giger. [doi]
• A user interface to communicate interpretable AI decisions to radiologistsYanchen Jessie Ou, Alina Jade Barnett, Anika Mitra, Fides Regina Schwartz, Chaofan Chen, Lars J. Grimm, Joseph Y. Lo, Cynthia Rudin. [doi]
• A training program to reduce reader search errors for liver metastasis detection in CTScott 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. [doi]
• Influence of magnet strength on background parenchymal enhancement evaluationLindsay Douglas, Trisha Mondal, Alexandra Edwards, Maryellen L. Giger. [doi]
• Attention-guided single-voxel attacks for 3-dimensional neural networks: experiments with post-mortem CT segmentationSteven A. Lewis, Scott Doyle. [doi]
• Utilizing network analysis in blinded independent central review for clinical trials as adjudication agreement dashboardManish Sharma, Sree Sudha Kota, Surabhi Bajpai, Kimberly Fernandes-Thomas, Madhuri Madasu, Yibin Shao, Rajesh Kaja, Rajesh Selvaraj, Kira Cheng, Joy Luo. [doi]
• Obuchowski-Rockette analysis for Multi-Reader Multi-Case (MRMC) readers-nested-in-test study design with unequal numbers of readersStephen L. Hillis, BaoLin Pauline Soh. [doi]
• Predictive adjudication rate modeling for prioritizing case distribution in BICR for oncology clinical trialsManish Sharma, Madhuri Madasu, Surabhi Bajpai, Kimberly Fernandes-Thomas, Sree Sudha Kota, Yibin Shao, Rajesh Selvaraj, Rajesh Kaja, Kira Cheng, Joy Luo. [doi]
• Novel concept for systematic testing of AI models for MRI acquisition shifts with simulated dataChristiane Posselt, Edith Gramotke, Abhijeet Parida, Mehmet Yigitsoy, Stefanie Remmele. [doi]
• Developing and assessing an AI-based multi-task prediction system to assist radiologists detecting lung diseases in reading chest x-ray imagesLin Guo, Kunlei Hong, Qian Xiao, Lingjun Qian, Stefan Jaeger 0001, Bin Zheng 0001, Shenwen Quan, Li Xia, Guanxun Cheng, Y. M. Fleming Lure. [doi]
• High-quality label-free prediction of fluorescence images through stimulated Raman scattering imaging and recurrent deep neural networkTianrun Chen, Ying Zang, Jia Zhang, Delong Zhang. [doi]
• Spatiotemporal image quality in medical extended realityChumin Zhao, Ryan Beams, Aldo Badano. [doi]
• An observer comparison study to evaluate a machine learning model to quantify the infected pneumonia on lung CT imagesAlireza Abdihamzehkolaei, Seyedehnafiseh Mirniaharikandehei, Angel Choquehuanca, Marco Aedo, Wilmer Pacheco, Laura Estacio, Victor Cahui, Luis Huallpa, Kevin Quiñonez, Valeria Calderón, Ana Maria Gutiérrez, Ana Vargas, Dery Gamero, Eveling Castro Gutierrez, Yuchen Qiu, Bin Zheng 0001, Javier A. Jo. [doi]
• False-negative diagnosis might occur due to absence of the global radiomic signature of malignancy on screening mammogramsZiba Gandomkar, Sarah J. Lewis 0001, Somphone Siviengphanom, Dennis Wong, Ernest U. Ekpo, Moayyad E. Suleiman, Xuetong Tao, Warren M. Reed, Patrick C. Brennan. [doi]
• Investigating the error-making patterns in reading high-density screening mammograms between radiologists from two countriesXuetong Tao, Somphone Siviengphanom, Ziba Gandomkar, Tong Li, Warren M. Reed, Patrick C. Brennan. [doi]
• A user interface to communicate interpretable AI decisions to radiologists (Erratum)Yanchen Ou, Alina Jade Barnett, Anika Mitra, Fides Regina Schwartz, Chaofan Chen, Lars J. Grimm, Joseph Y. Lo, Cynthia Rudin. [doi]
• Approximating the idea observer on list mode data with comparison to CNN methodsDan Li, Eric Clarkson. [doi]
• Observer study-based evaluation of TGAN architecture used to generate oncological PET imagesRoberto Fedrigo, Fereshteh Yousefirizi, Ziping Liu, Abhinav K. Jha, Robert V. Bergen, Jean-François Rajotte, Raymond T. Ng, Ingrid Bloise, Sara Harsini, Dan J. Kadrmas, Carlos F. Uribe, Arman Rahmim. [doi]
• Optimal visual search strategy with inter-saccade response correlationsWeimin Zhou, Miguel P. Eckstein. [doi]
• Discriminability of non-Gaussian noise properties in CTKirsten L. Boedeker, Daniel W. Shin, Luuk J. Oostveen, Ioannis Sechopoulos, Craig K. Abbey. [doi]
• 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 effortKaren Drukker, Berkman Sahiner, Tingting Hu, Hyun J. Grace Kim, Heather M. Whitney, Natalie M. Baughan, Kyle J. Myers, Maryellen L. Giger, Michael F. McNitt-Gray. [doi]
• Analysis of a pilot study collecting pathologist annotations for validating machine learning algorithmsKatherine Elfer, Victor Garcia, Brandon D. Gallas. [doi]
• Longitudinal robustness of a thoracic radiographic AI model for COVID-19 severity predictionKaren Drukker, Hui Li 0024, Maryellen L. Giger. [doi]
• Configuring medical displays for high- and stable-image contrast in bright roomsPatrik Sund. [doi]
• Comparing experts to novices: reduced satisfaction of search when searching with virtual breast tomosynthesisStephen H. Adamo, Bruno Barufaldi, Miguel A. Lago. [doi]
• Evaluation of multiparametric MRI for deep learning-based segmentation of Wilms tumorMyrthe A. D. Buser, Marc H. W. A. Wijnen, Alida F. W. van der Steeg, Bas H. M. van der Velden. [doi]
• Task-aware denoising autoencoders for establishing efficient channelsWeimin Zhou. [doi]
• Comparative tests between actual and simulated digital mammography images for new computer schemes evaluation databaseFernanda J. F. Cardoso, Homero Schiabel. [doi]
• Global mammographic radiomic signature can predict radiologists' difficult-to-interpret normal casesSomphone Siviengphanom, Ziba Gandomkar, Sarah J. Lewis 0001, Patrick C. Brennan. [doi]
• A visibility overshoot index for interventional x-ray image quality assessmentAsli Kumcu, Ljiljana Platisa, Bart Goossens, Amber J. Gislason-Lee, Andrew G. Davies, Gerard Schouten, Dimitri Buytaert, Klaus Bacher, Wilfried Philips. [doi]
• Comparison of radiologists' interpretation efficiency with radiographs: standard 6 MP versus 12 MP high-resolution display monitorsMostafa Abozeed, Tom Kimpe, Seth T. Lirette, Srini Tridandapani. [doi]
• Need for objective task-based evaluation of AI-based segmentation methods for quantitative PETZiping Liu, Joyce C. Mhlanga, Barry A. Siegel, Abhinav K. Jha. [doi]
• Diagnostic performance characteristics of Chinese radiologists in breast cancer detection with FFDM versus DBT imagesJia Lin Chua, Qin Xiao, Tong Li, Yajia Gu, Melissa L. Robinson, Kriscia Tapia, Sarah Lewis 0001, Phuong Dung Trieu. [doi]
• A task-specific deep-learning-based denoising approach for myocardial perfusion SPECTMd. Ashequr Rahman, Zitong Yu, Barry A. Siegel, Abhinav K. Jha. [doi]
• Adaptive Laguerre-Gauss channels for detection and search of irregularly shaped lesionsMiguel A. Lago, Aldo Badano. [doi]
• Identifying and preventing fatigue in digital breast tomosynthesisAdnan Taib, George Partridge, Iain T. Darker, Peter Phillips, Yan Chen 0012. [doi]
• Optimizing data acquisition in undersampled magnetic resonance imaging (MRI) using two alternative forced choice (2-AFC) and search tasksTavianne M. Kemp, Tetsuya A. Kawakita, Rehan Mehta, Angel R. Pineda. [doi]
• Automatic assessment of skeletal maturity in adolescent idiopathic scoliosis patients using support vector regression on deep featuresHilary Cintia Djuikoua Wouafo, Julie Joncas, Marjolaine Roy-Beaudry, Soraya Barchi, Stefan Parent, Hubert Labelle, Luc Duong. [doi]
• A comparative study of diagnostic performance and work experience of radiologists in three countries interpreting digital breast tomosynthesisElly K. Gallagher, Phuong Dung Trieu, Ziba Gandomkar, Tong Li, Masoumeh Gity, Patrick C. Brennan, Sarah Lewis 0001, Seyedamir Tavakoli Taba. [doi]
• Assessing the impact of correlated noise in digital mammography: a virtual clinical trialLucas Exposto Soares, Renann F. Brandao, Lucas R. Borges, Renato F. Caron, Bruno Barufaldi, Andrew D. A. Maidment, Marcelo A. C. Vieira. [doi]
• Evaluating generative stochastic image models using task-based image quality measuresVarun A. Kelkar, Dimitrios S. Gotsis, Rucha Deshpande, Frank J. Brooks, Prabhat K. C., Kyle J. Myers, Rongping Zeng, Mark A. Anastasio. [doi]