Mahnaz Maddah

1.2k total citations
40 papers, 754 citations indexed

About

Mahnaz Maddah is a scholar working on Radiology, Nuclear Medicine and Imaging, Biophysics and Computer Vision and Pattern Recognition. According to data from OpenAlex, Mahnaz Maddah has authored 40 papers receiving a total of 754 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Radiology, Nuclear Medicine and Imaging, 10 papers in Biophysics and 9 papers in Computer Vision and Pattern Recognition. Recurrent topics in Mahnaz Maddah's work include Cell Image Analysis Techniques (10 papers), Advanced Neuroimaging Techniques and Applications (10 papers) and Medical Image Segmentation Techniques (7 papers). Mahnaz Maddah is often cited by papers focused on Cell Image Analysis Techniques (10 papers), Advanced Neuroimaging Techniques and Applications (10 papers) and Medical Image Segmentation Techniques (7 papers). Mahnaz Maddah collaborates with scholars based in United States, Germany and Iran. Mahnaz Maddah's co-authors include Simon K. Warfield, W. Eric L. Grimson, Kevin Loewke, William M. Wells, Andrea U. J. Mewes, Mohammad A. Mandegar, Bruce R. Conklin, Daniel Goldberg‐Zimring, Steven Haker and Hamid Soltanian‐Zadeh and has published in prestigious journals such as Circulation, Journal of the American College of Cardiology and NeuroImage.

In The Last Decade

Mahnaz Maddah

35 papers receiving 742 citations

Peers

Mahnaz Maddah

RNMI

PPCH

CCM

Françoise Durand‐Dubief France

Peter Savadjiev United States

Lisa Jonasson Switzerland

Constantin Anastasopoulos Germany

Iman Aganj United States

Irvin Teh United Kingdom

Benoît Scherrer United States

Bistra Iordanova United States

Alexandre Guimond Canada

Sushmita Datta United States

Françoise Durand‐Dubief France

Mahnaz Maddah

240 ×0.7

RNMI

148 ×0.8

40 ×0.2

32 ×0.3

PPCH

45 ×0.5

CCM

Citations per year, relative to Mahnaz Maddah Mahnaz Maddah (= 1×) peers Françoise Durand‐Dubief

Countries citing papers authored by Mahnaz Maddah

Since Specialization

Citations

This map shows the geographic impact of Mahnaz Maddah's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Mahnaz Maddah with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mahnaz Maddah more than expected).

Fields of papers citing papers by Mahnaz Maddah

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mahnaz Maddah. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Mahnaz Maddah. The network helps show where Mahnaz Maddah may publish in the future.

Co-authorship network of co-authors of Mahnaz Maddah

This figure shows the co-authorship network connecting the top 25 collaborators of Mahnaz Maddah. A scholar is included among the top collaborators of Mahnaz Maddah based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Mahnaz Maddah. Mahnaz Maddah is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Friedman, Sam, Shaan Khurshid, Xin Wang, et al.. (2025). Unsupervised deep learning of electrocardiograms enables scalable human disease profiling. npj Digital Medicine. 8(1). 23–23. 4 indexed citations

Kany, Shinwan, Mostafa A. Al‐Alusi, Joel Rämö, et al.. (2025). “Weekend Warrior” Physical Activity and Adipose Tissue Deposition. JACC Advances. 4(3). 101603–101603.

Claggett, Brian, Mahnaz Maddah, Shaan Khurshid, et al.. (2025). Using Artificial Intelligence to Adjudicate Major Adverse Cardiovascular Events in Clinical Trials. Journal of the American College of Cardiology.

Al‐Alusi, Mostafa A., Emily S. Lau, Christopher Reeder, et al.. (2025). A Deep Learning Model to Identify Mitral Valve Prolapse From the Echocardiogram. JACC. Cardiovascular imaging. 19(1). 18–29.

Lau, Emily S., V. D’Souza, Yunong Zhao, et al.. (2025). Contemporary Burden of Cardiovascular Disease in Pregnancy: Insights From a Real-World Pregnancy Electronic Health Record Cohort. Circulation. 152(15). 1044–1055.

Kany, Shinwan, Sam Friedman, Mostafa A. Al‐Alusi, et al.. (2025). Electrocardiogram-Based Artificial Intelligence to Identify Coronary Artery Disease. JACC Advances. 4(9). 102041–102041. 1 indexed citations

Khurshid, Shaan, Sam Friedman, Mostafa A. Al‐Alusi, et al.. (2025). Artificial intelligence-enabled analysis of handheld single-lead electrocardiograms to predict incident atrial fibrillation: an analysis of the VITAL-AF randomized trial. npj Digital Medicine. 8(1). 776–776.

Gallego, Raquel Del, Lorena Bori, Kevin Loewke, et al.. (2020). Assessment of embryo implantation potential with a cloud-based automatic software. Reproductive BioMedicine Online. 42(1). 66–74. 14 indexed citations

Maddah, Mahnaz, et al.. (2015). A Non-invasive Platform for Functional Characterization of Stem-Cell-Derived Cardiomyocytes with Applications in Cardiotoxicity Testing. Stem Cell Reports. 4(4). 621–631. 106 indexed citations

10.

Maddah, Mahnaz, et al.. (2014). A System for Automated, Noninvasive, Morphology-Based Evaluation of Induced Pluripotent Stem Cell Cultures. SLAS TECHNOLOGY. 19(5). 454–460. 36 indexed citations

11.

Loewke, Kevin, Farshid Moussavi, Mahnaz Maddah, et al.. (2012). Development and validation of an automated computer vision algorithm for real-time embryo viability prediction. Fertility and Sterility. 98(3). S288–S289. 4 indexed citations

12.

Maddah, Mahnaz, Marek Kubicki, William M. Wells, et al.. (2008). Findings in Schizophrenia by Tract-Oriented DT-MRI Analysis. Lecture notes in computer science. 11(Pt 1). 917–924. 18 indexed citations

13.

Maddah, Mahnaz, Lilla Zöllei, W. Eric L. Grimson, & William M. Wells. (2008). Modeling of anatomical information in clustering of white matter fiber trajectories using Dirichlet distribution. PubMed. 2008. 1–7. 12 indexed citations

14.

Maddah, Mahnaz, Lilla Zöllei, W. Eric L. Grimson, Carl‐Fredrik Westin, & William M. Wells. (2008). A Mathematical Framework for incorporating anatomical knowledge in DT-MRI analysis. PubMed. 4543943. 105–108. 18 indexed citations

15.

Maddah, Mahnaz, W. Eric L. Grimson, Simon K. Warfield, & William M. Wells. (2007). A unified framework for clustering and quantitative analysis of white matter fiber tracts. Medical Image Analysis. 12(2). 191–202. 98 indexed citations

16.

Maddah, Mahnaz, Hamid Soltanian‐Zadeh, Ali Afzali‐Kusha, Ali Shahrokni, & Zheng G. Zhang. (2005). Three-dimensional analysis of complex branching vessels in confocal microscopy images. Computerized Medical Imaging and Graphics. 29(6). 487–498. 5 indexed citations

17.

Goldberg‐Zimring, Daniel, Andrea U. J. Mewes, Mahnaz Maddah, & Simon K. Warfield. (2005). Diffusion Tensor Magnetic Resonance Imaging in Multiple Sclerosis. Journal of Neuroimaging. 15(s4). 68S–81S. 57 indexed citations

18.

Soltanian‐Zadeh, Hamid, Ali Shahrokni, Zheng G. Zhang, et al.. (2004). 3-D quantification and visualization of vascular structures from confocal microscopic images using skeletonization and voxel-coding. Computers in Biology and Medicine. 35(9). 791–813. 15 indexed citations

19.

Maddah, Mahnaz, Ali Afzali‐Kusha, & Hamid Soltanian‐Zadeh. (2003). Efficient center-line extraction for quantification of vessels in confocal microscopy images. Medical Physics. 30(2). 204–211. 12 indexed citations

20.

Maddah, Mahnaz, Hamid Soltanian‐Zadeh, & Ali Afzali‐Kusha. (2003). Snake modeling and distance transform approach to vascular centerline extraction and quantification. Computerized Medical Imaging and Graphics. 27(6). 503–512. 13 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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