Ziba Gandomkar

27 papers Journal 8Unranked 18

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	A Machine Learning Model Based on Global Mammographic Radiomic Features Can Predict Which Normal Mammographic Cases Radiology Trainees Find Most Difficult. J. Imaging Inform. Medicine Somphone Siviengphanom, Patrick C. Brennan, Sarah J. Lewis, Phuong Dung Trieu, Ziba Gandomkar
2024	J	`jnl`	MuscleMap: An Open-Source, Community-Supported Consortium for Whole-Body Quantitative MRI of Muscle. J. Imaging Marnee J. McKay, Kenneth Arnold Weber II, Evert O. Wesselink, Zachary A. Smith, Rebecca Abbott, David B. Anderson, Claire E. Ashton-James, John Atyeo, Aaron J. Beach, Joshua Burns, Stephen Clarke, Natalie J. Collins, Michel W. Coppieters, Jon Cornwall, Rebecca J. Crawford, Enrico De Martino, Adam G. Dunn, Jillian P. Eyles, Henry J. Feng, Maryse Fortin, Melinda M. Franettovich Smith, Graham J. Galloway, Ziba Gandomkar, Sarah Glastras, Luke A. Henderson, Julie A. Hides, Claire E. Hiller, Sarah N. Hilmer, Mark A. Hoggarth, Brian Kim, Navneet Lal, Laura Laporta, John S. Magnussen, Sarah Maloney, Lyn March, Andrea G. Nackley, Shaun P. O'leary, Anneli Peolsson, Zuzana Perraton, Annelies L. Pool-Goudzwaard, Margaret Schnitzler, Amee L. Seitz, Adam I. Semciw, Philip W. Sheard, Andrew C. Smith, Suzanne J. Snodgrass, Justin Sullivan, Vienna Tran, Stephanie Valentin, David M. Walton, Laurelie R. Wishart, James M. Elliott
2023	—	`conf`	A comparative study of diagnostic performance and work experience of radiologists in three countries interpreting digital breast tomosynthesis. Image Perception, Observer Performance, and Technology Assessment Elly K. Gallagher, Phuong Dung Trieu, Ziba Gandomkar, Tong Li, Masoumeh Gity, Patrick C. Brennan, Sarah Lewis, Seyedamir Tavakoli Taba
2023	—	`conf`	False-negative diagnosis might occur due to absence of the global radiomic signature of malignancy on screening mammograms. Image Perception, Observer Performance, and Technology Assessment Ziba Gandomkar, Sarah J. Lewis, Somphone Siviengphanom, Dennis Wong, Ernest U. Ekpo, Moayyad E. Suleiman, Xuetong Tao, Warren M. Reed, Patrick C. Brennan
2023	J	`jnl`	Global Radiomic Features from Mammography for Predicting Difficult-To-Interpret Normal Cases. J. Digit. Imaging Somphone Siviengphanom, Ziba Gandomkar, Sarah J. Lewis, Patrick C. Brennan
2023	—	`conf`	Global mammographic radiomic signature can predict radiologists' difficult-to-interpret normal cases. Image Perception, Observer Performance, and Technology Assessment Somphone Siviengphanom, Ziba Gandomkar, Sarah J. Lewis, Patrick C. Brennan
2023	—	`conf`	How do you solve a problem like concordance? a study of radiologists' clinical annotations for mammographic AI training. Image Perception, Observer Performance, and Technology Assessment Zhengqiang Jiang, Phuong Dung Trieu, Ziba Gandomkar, Seyedamir Tavakoli Taba, Melissa L. Barron, Sarah J. Lewis
2023	—	`conf`	Investigating the error-making patterns in reading high-density screening mammograms between radiologists from two countries. Image Perception, Observer Performance, and Technology Assessment Xuetong Tao, Somphone Siviengphanom, Ziba Gandomkar, Tong Li, Warren M. Reed, Patrick C. Brennan
2022	—	`conf`	The reliability of radiologists' first impression interpreting a screening mammogram. Image Perception, Observer Performance, and Technology Assessment Ziba Gandomkar, Somphone Siviengphanom, Moayyad E. Suleiman, Dennis Wong, Warren M. Reed, Ernest U. Ekpo, Dong Xu, Sarah J. Lewis, Patrick C. Brennan
2022	J	`jnl`	Using Occlusion-Based Saliency Maps to Explain an Artificial Intelligence Tool in Lung Cancer Screening: Agreement Between Radiologists, Labels, and Visual Prompts. J. Digit. Imaging Ziba Gandomkar, Pek-Lan Khong, Amanda Punch, Sarah Lewis
2022	—	`conf`	Varying performance levels for diagnosing mammographic images depending on reader nationality have AI and educational implications. Image Perception, Observer Performance, and Technology Assessment Xuetong Tao, Ziba Gandomkar, Tong Li, Warren M. Reed, Patrick C. Brennan
2021	—	`conf`	A retrospective comparative study of reading performances between radiologists from two countries in the assessment of 3D mammography. Image Perception, Observer Performance, and Technology Assessment Ziba Gandomkar, Tong Li, Phuong Dung Trieu, Sarah J. Lewis, Patrick C. Brennan
2021	—	`conf`	An end-to-end deep learning model can detect the gist of the abnormal in prior mammograms as perceived by experienced radiologists. Image Perception, Observer Performance, and Technology Assessment Ziba Gandomkar, Ernest U. Ekpo, Sarah J. Lewis, Moayyad E. Suleiman, Somphone Siviengphanom, Tong Li, Patrick C. Brennan
2020	—	`conf`	Investigating the potential of a gist-sensitive computer-aided detection tool. Image Perception, Observer Performance, and Technology Assessment Ziba Gandomkar, Ernest U. Ekpo, Sarah J. Lewis, Moayyad E. Suleiman, Kriscia Tapia, Tong Li, Seyedamir Tavakoli Taba, Phuong Dung Trieu, Patrick C. Brennan
2019	—	`conf`	BI-RADS density categorization using deep neural networks. Image Perception, Observer Performance, and Technology Assessment Ziba Gandomkar, Moayyad E. Suleiman, Delgermaa Demchig, Patrick C. Brennan, Mark F. McEntee
2019	J	`jnl`	Computer-Assisted Nuclear Atypia Scoring of Breast Cancer: a Preliminary Study. J. Digit. Imaging Ziba Gandomkar, Patrick C. Brennan, Claudia Mello-Thoms
2019	—	`conf`	Does the strength of the gist signal predict the difficulty of breast cancer detection in usual presentation and reporting mechanisms? Image Perception, Observer Performance, and Technology Assessment Ziba Gandomkar, Ernest U. Ekpo, Sarah J. Lewis, Karla K. Evans, Kriscia A. Tapia, Phuong Dung Trieu, Jeremy M. Wolfe, Patrick C. Brennan
2018	—	`conf`	A cognitive approach to determine the benefits of pairing radiologists in mammogram reading. Image Perception, Observer Performance, and Technology Assessment Ziba Gandomkar, Patrick C. Brennan, Claudia Mello-Thoms
2018	—	`conf`	A framework for distinguishing benign from malignant breast histopathological images using deep residual networks. IWBI Ziba Gandomkar, Patrick C. Brennan, Claudia Mello-Thoms
2018	—	`—`	Added benefits of computer-assisted analysis of Hematoxylin-Eosin stained breast histopathological digital slides. Ziba Gandomkar
2018	—	`conf`	Detection of the abnormal gist in the prior mammograms even with no overt sign of breast cancer. IWBI Ziba Gandomkar, Ernest U. Ekpo, Sarah J. Lewis, Karla K. Evans, Kriscia Tapia, Phuong Dung Trieu, Jeremy M. Wolfe, Patrick C. Brennan
2018	J	`jnl`	MuDeRN: Multi-category classification of breast histopathological image using deep residual networks. Artif. Intell. Medicine Ziba Gandomkar, Patrick C. Brennan, Claudia Mello-Thoms
2017	—	`conf`	Determining local and contextual features describing appearance of difficult to identify mitotic figures. Digital Pathology Ziba Gandomkar, Patrick C. Brennan, Claudia Mello-Thoms
2017	J	`jnl`	iCAP: An Individualized Model Combining Gaze Parameters and Image-Based Features to Predict Radiologists' Decisions While Reading Mammograms. IEEE Trans. Medical Imaging Ziba Gandomkar, Kevin Tay, Will Ryder, Patrick C. Brennan, Claudia Mello-Thoms
2016	—	`conf`	Predicting radiologists' true and false positive decisions in reading mammograms by using gaze parameters and image-based features. Image Perception, Observer Performance, and Technology Assessment Ziba Gandomkar, Kevin Tay, Will Ryder, Patrick C. Brennan, Claudia Mello-Thoms
2014	J	`jnl`	EEG-based sympathy recognition. Int. J. Medical Eng. Informatics Muhammad Ali Sadouni, Ziba Gandomkar, Ehsan Arbabi
2012	—	`conf`	Hippocampal shape analysis in the Laplace Beltrami feature space for temporal lobe epilepsy diagnosis and lateralization. ISBI Rosita Shishegar, Ziba Gandomkar, Hamid Soltanian-Zadeh, Seyed Reza Moghadasi