Table of Contents

• Parameter selection with the Hotelling observer in linear iterative image reconstruction for breast tomosynthesisSean D. Rose, Jacob Roth, Cole Zimmerman, Ingrid S. Reiser, Emil Y. Sidky, Xiaochuan Pan. [doi]
• A Deep Learning Model Observer for use in Alterative Forced Choice Virtual Clinical TrialsMajdi R. Alnowami, G. Mills, M. Awis, Premkumar Elangovan, Mishal N. Patel, Mark D. Halling-Brown, Kenneth Y. Young, David R. Dance, Kevin Wells. [doi]
• Resampling techniques comparison for CHO's performance and uncertainty estimationFrancesc Massanes, Alexandre Ba, François O. Bochud, Jovan G. Brankov. [doi]
• Lesion detection performance of cone beam CT images with anatomical background noise: single-slice vs multi-slice human and model observer studyMinah Han, Hanjoo Jang, Jongduk Baek. [doi]
• Towards a surround-aware numerical observerAli R. N. Avanaki, Kathryn S. Espig, Albert Xthona, Tom R. L. Kimpe. [doi]
• Reader performance in visual assessment of breast density using visual analogue scales: are some readers more predictive of breast cancer?Millicent Rayner, Elaine F. Harkness, Philip Foden, Mary Wilson, Soujanya Gadde, Ursula M. Beetles, Yit Yoong Lim, Anil Jain 0001, Sally Bundred, Nicky B. Barr, D. Gareth Evans, Anthony Howell, Anthony Maxwell, Susan M. Astley. [doi]
• Interaction of anatomic and quantum noise in DBT power spectrumAmar Kavuri, Nathaniel R. Fredette, Mini Das. [doi]
• Interactions of lesion detectability and size across single-slice DBT and 3D DBTMiguel A. Lago, Craig K. Abbey, Bruno Barufaldi, Predrag R. Bakic, Susan P. Weinstein, Andrew D. A. Maidment, Miguel P. Eckstein. [doi]
• Feasibility study of deep convolutional generative adversarial networks to generate mammography imagesGihun Kim, Hyunjung Shim, Jongduk Baek. [doi]
• Comparison of microcalcification detectability in FFDM and DBT using a virtual clinical trialZhijin Li, Agnès Desolneux, Serge Muller, Pablo Milioni de Carvalho, Ann-Katherine Carton. [doi]
• Assessment of DBT acquisition parameters for 2D and 3D search tasksHoward C. Gifford, Mini Das. [doi]
• Test data reuse for evaluation of adaptive machine learning algorithms: over-fitting to a fixed 'test' dataset and a potential solutionAlexej Gossmann, Aria Pezeshk, Berkman Sahiner. [doi]
• Model and human observer reproducibility for detecting microcalcifications in digital breast tomosynthesis imagesDimitar Petrov, Nicholas Marshall, Kenneth C. Young, Hilde Bosmans. [doi]
• Simulating magnetic resonance images based on a model of tumor growth incorporating microenvironmentPamela R. Jackson, Andrea Hawkins-Daarud, Savannah C. Partridge, Paul E. Kinahan, Kristin R. Swanson. [doi]
• Breast elastography: Identification of benign and malignant cancer based on absolute elastic modulus measurement using vibro-elastographyJunior Arroyo, Ana Cecilia Saavedra, Jorge Guerrero, Pilar Montenegro, Jorge Aguilar, Joseph A. Pinto, Julio Lobo, Tim Salcudean, Roberto J. Lavarello, Benjamín Castañeda. [doi]
• A citizen science approach to optimising computer aided detection (CAD) in mammographyGeorgia V. Ionescu, Elaine F. Harkness, Johan Hulleman, Susan M. Astley. [doi]
• Towards the use of computationally inserted lesions for mammographic CAD assessmentZahra Ghanian, Aria Pezeshk, Nicholas Petrick, Berkman Sahiner. [doi]
• Quantifying predictive capability of electronic health records for the most harmful breast cancerYirong Wu, Jun Fan, Peggy L. Peissig, Richard L. Berg, Ahmad Pahlavan Tafti, Jie Yin, Ming Yuan, David Page, Jennifer Cox, Elizabeth S. Burnside. [doi]
• Local-search based prediction of medical image registration errorGörkem Saygili. [doi]
• Satisfaction at last: evidence for the 'satisfaction' account for multiple-target search errorsStephen H. Adamo, Matthew S. Cain, Stephen R. Mitroff. [doi]
• Correlation between model observers in uniform background and human observer in patient liver background for a low-contrast detection task in CTHao Gong, Lifeng Yu, Shuai Leng, Samantha Dilger, Wei Zhou, Liqiang Ren, Cynthia H. McCollough. [doi]
• Comparison of synthetic 2D images with planar and tomosynthesis imaging of the breast using a virtual clinical trialAlistair Mackenzie, Sukmanjit Kaur, Premkumar Elangovan, David R. Dance, Kenneth C. Young. [doi]
• A practical method to evaluate personalized injected patient dose for cardiac perfusion SPECT imaging: the polar map as a numerical observerP. Hendrik Pretorius, Michael A. King, Karen L. Johnson. [doi]
• Efficiency gain of paired split-plot designs in MRMC ROC studiesWeijie Chen, Qi Gong, Brandon D. Gallas. [doi]
• Evaluation of a machine learning based model observer for x-ray CTFelix K. Kopp, Marco Catalano, Daniela Pfeiffer, Ernst J. Rummeny, Peter B. Noël. [doi]
• Analyzing ROC curves using the effective set-size modelFrank W. Samuelson, Craig K. Abbey, Xin He. [doi]
• Blind CT image quality assessment via deep learning strategy: initial studySui Li, Ji He, Yongbo Wang, Yuting Liao, Dong Zeng, Zhaoying Bian, Jianhua Ma. [doi]
• Reducing the number of reconstructions needed for estimating channelized observer performanceAngel R. Pineda, Hope Miedema, Melissa Brenner, Sana Altaf. [doi]
• Lesion classification with a visual-search model observerKheya Banerjee, Howard C. Gifford. [doi]
• Evaluation of search strategies for microcalcifications and masses in 3D imagesMiguel P. Eckstein, Miguel A. Lago, Craig K. Abbey. [doi]
• Observer templates in 2D and 3D localization tasksCraig K. Abbey, Miguel A. Lago, Miguel P. Eckstein. [doi]
• Can a totally different approach to soft tissue computer aided detection CADE result in affecting radiologists' decisions?David Gur. [doi]
• Do radiographers base the diagnostic acceptability of a radiograph on anatomical structures?Robin Decoster, Rachel Toomey, Marie-Louise Butler. 1057703 [doi]
• A cognitive approach to determine the benefits of pairing radiologists in mammogram readingZiba Gandomkar, Patrick C. Brennan, Claudia Mello-Thoms. 1057704 [doi]
• Restored low-dose digital breast tomosynthesis: a perception studyLucas R. Borges, Predrag R. Bakic, Andrew D. A. Maidment, Marcelo A. C. Vieira. 1057705 [doi]
• A database for assessment of effect of lossy compression on digital mammogramsJiheng Wang, Berkman Sahiner, Nicholas Petrick, Aria Pezeshk. 1057706 [doi]
• A deep (learning) dive into visual search behaviour of breast radiologistsSuneeta Mall, Patrick C. Brennan, Claudia Mello-Thoms. 1057708 [doi]
• Can a limited double reading/second opinion of initially recalled breast ultrasound screening examinations improve radiologists' performances?David Gur, Kimberly Harnist, Terri-Ann Gizienski, Margarita L. Zuley, Christiane M. Hakim, Amy Lu, Jules H. Sumkin, Gordon Abrams, Marie A. Ganott, Amy E. Kelly, Cathy S. Tyma, Thomas S. Chang, Marcella Bhm-Vélez, Robin Sobolewski. 1057710 [doi]
• Study of CT image texture using deep learning techniquesSandeep Dutta, Jiahua Fan, David Chevalier. 1057712 [doi]
• Assessment of computerized algorithms by comparing with human observers in binary classification tasks: a simulation studyYang Yang, Berkman Sahiner, Zhipeng Huang, Nicholas Petrick, Weijie Chen. 1057713 [doi]
• Development of a validation instrument in myocardial perfusion imaging: results of first flow experimentsMarije E. Kamphuis, Gert Jan Pelgrim, Marcel J. W. Greuter, Riemer H. J. A. Slart, Cornelis H. Slump. 1057714 [doi]
• Ischemic stroke enhancement in computed tomography scans using a computational approachAllan F. F. Alves, Ana Luiza Menegatti Pavan, Rachid Jennane, José R. A. Miranda, Carlos C. M. Freitas, Nitamar Abdala, Diana Rodrigues de Pina. 1057716 [doi]
• Projection space model observers based on marginalized linear discriminantsZohreh Karbaschi, Howard C. Gifford. 1057717 [doi]
• Characteristics of the group of radiologists that benefits the most using Breast Screen Reader Assessment Strategy (BREAST)A. Ganesan, Maram Alakhras, Patrick C. Brennan, Warwick B. Lee, Kriscia Tapia, Claudia Mello-Thoms. 1057718 [doi]
• Learning the ideal observer for SKE detection tasks by use of convolutional neural networksWeimin Zhou, Mark A. Anastasio. 1057719 [doi]