Mehdi Moradi

contact information

Scientist/Manager, AI for Healthcare
IBM Almaden Research Center, San Jose, CA, USA
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Professional Associations

Professional Associations: IEEE Signal Processing Society | The Medical Image Computing and Computer Assisted Intervention Society (MICCAI)

2020

A Deep Community Based Approach for Large Scale Content Based X-Ray Image Retrieval
Nandinee Fariah Haq, Mehdi Moradi, Z. Jane Wang
Medical Image Analysis, 2020
Abstract image retrieval, deep learning, data mining, clinical decision support system, computer science, artificial intelligence, community based, improved performance, large scale data, network generation, x ray image

Comparison of Chest Radiograph Interpretations by Artificial Intelligence Algorithm vs Radiology Residents
Joy T. Wu, Ken C. L. Wong, Yaniv Gur, Nadeem Ansari, Alexandros Karargyris, Arjun Sharma, Michael Morris, Babak Saboury, Hassan Ahmad, Orest Boyko, Ali Syed, Ashutosh Jadhav, Hongzhi Wang, Anup Pillai, Satyananda Kashyap, Mehdi Moradi, Tanveer Syeda-Mahmood
JAMA Network Open 3(10), 2020
Abstract receiver operating characteristic, chest radiograph, medical imaging, inter rater reliability, f1 score, statistic, ground truth, radiography, radiology, medicine, artificial intelligence, algorithm

Importance Chest radiography is the most common diagnostic imaging examination performed in emergency departments (EDs). Augmenting clinicians with automated preliminary read assistants could help expedite their workflows, improve accuracy, and reduce the cost of care. Objective To assess the performance of artificial intelligence (AI) algorithms in realistic radiology workflows by performing an objective comparative evaluation of the preliminary reads of anteroposterior (AP) frontal chest radiographs performed by an AI algorithm and radiology residents. Design, Setting, and Participants This diagnostic study included a set of 72 findings assembled by clinical experts to constitute a full-fledged preliminary read of AP frontal chest radiographs. A novel deep learning architecture was designed for an AI algorithm to estimate the findings per image. The AI algorithm was trained using a multihospital training data set of 342126 frontal chest radiographs captured in ED and urgent care settings. The training data were labeled from their associated reports. Image-based F1 score was chosen to optimize the operating point on the receiver operating characteristics (ROC) curve so as to minimize the number of missed findings and overcalls per image read. The performance of the model was compared with that of 5 radiology residents recruited from multiple institutions in the US in an objective study in which a separate data set of 1998 AP frontal chest radiographs was drawn from a hospital source representative of realistic preliminary reads in inpatient and ED settings. A triple consensus with adjudication process was used to derive the ground truth labels for the study data set. The performance of AI algorithm and radiology residents was assessed by comparing their reads with ground truth findings. All studies were conducted through a web-based clinical study application system. The triple consensus data set was collected between February and October 2018. The comparison study was preformed between January and October 2019. Data were analyzed from October to February 2020. After the first round of reviews, further analysis of the data was performed from March to July 2020. Main Outcomes and Measures The learning performance of the AI algorithm was judged using the conventional ROC curve and the area under the curve (AUC) during training and field testing on the study data set. For the AI algorithm and radiology residents, the individual finding label performance was measured using the conventional measures of label-based sensitivity, specificity, and positive predictive value (PPV). In addition, the agreement with the ground truth on the assignment of findings to images was measured using the pooled statistic. The preliminary read performance was recorded for AI algorithm and radiology residents using new measures of mean image-based sensitivity, specificity, and PPV designed for recording the fraction of misses and overcalls on a per image basis. The 1-sided analysis of variance test was used to compare the means of each group (AI algorithm vs radiology residents) using the F distribution, and the null hypothesis was that the groups would have similar means. Results The trained AI algorithm achieved a mean AUC across labels of 0.807 (weighted mean AUC, 0.841) after training. On the study data set, which had a different prevalence distribution, the mean AUC achieved was 0.772 (weighted mean AUC, 0.865). The interrater agreement with ground truth finding labels for AI algorithm predictions had pooled value of 0.544, and the pooled for radiology residents was 0.585. For the preliminary read performance, the analysis of variance test was used to compare the distributions of AI algorithm and radiology residents mean image-based sensitivity, PPV, and specificity. The mean image-based sensitivity for AI algorithm was 0.716 (95% CI, 0.704-0.729) and for radiology residents was 0.720 (95% CI, 0.709-0.732) (P=.66), while the PPV was 0.730 (95% CI, 0.718-0.742) for the AI algorithm and 0.682 (95% CI, 0.670-0.694) for the radiology residents (P<.001), and specificity was 0.980 (95% CI, 0.980-0.981) for the AI algorithm and 0.973 (95% CI, 0.971-0.974) for the radiology residents (P<.001). Conclusions and Relevance These findings suggest that it is possible to build AI algorithms that reach and exceed the mean level of performance of third-year radiology residents for full-fledged preliminary read of AP frontal chest radiographs. This diagnostic study also found that while the more complex findings would still benefit from expert overreads, the performance of AI algorithms was associated with the amount of data available for training rather than the level of difficulty of interpretation of the finding. Integrating such AI systems in radiology workflows for preliminary interpretations has the potential to expedite existing radiology workflows and address resource scarcity while improving overall accuracy and reducing the cost of care.

Chest X-ray Report Generation through fine-grained label learning
Tanveer Syeda-Mahmood, Ken C. L. Wong, Y. Gur, Joy T. Wu, Ashutosh Jadhav, Alexandros Karargyris, Anup Pillai, Arjun Sharma, Ali Syed, Orest Boyko, others
Medical Image Computing and Computer Assisted Intervention (MICCAI 2020)

Looking in the Right Place for Anomalies: Explainable Ai Through Automatic Location Learning
S. Kashyap, A. Karargyris, J. Wu, Y. Gur, A. Sharma, K. C. L. Wong, M. Moradi, T. Syeda-Mahmood
2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI), pp. 1125-1129

Automatic Bounding Box Annotation of Chest X-Ray Data for Localization of Abnormalities
J. Wu, Y. Gur, A. Karargyris, A. B. Syed, O. Boyko, M. Moradi, T. Syeda-Mahmood
2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI), pp. 799-803

A robust network architecture to detect normal chest X-ray radiographs
Ken CL Wong, Mehdi Moradi, Joy Wu, Anup Pillai, Arjun Sharma, Yaniv Gur, Hassan Ahmad, Minnekanti Sunil Chowdary, Kiran Kumar Reddy Polaka, Venkateswar Wunnava, DC Reddy, Tanveer Syeda-Mahmood
2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI), 2020, pp. 1851-1855
Abstract

Quality controlled segmentation to aid disease detection
Mehdi Moradi, Ken C. L. Wong, Alexandros Karargyris, Tanveer Syeda-Mahmood
Medical Imaging 2020: Computer-Aided Diagnosis11314
Abstract segmentation, pattern recognition, offset, limiting, disease detection, deep learning, computer science, classifier, artificial intelligence, area of interest, annotation

2019

Building a Benchmark Dataset and Classifiers for Sentence-Level Findings in AP Chest X-Rays
T. Syeda-Mahmood, H. Ahmad, N. Ansari, Y. Gur, S. Kashyap, A. Karargyris, M. Moradi, A. Pillai, K. Seshadhri, W. Wang, K. C. L. Wong, J. Wu
2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019), pp. 863-867

SegNAS3D: Network Architecture Search with Derivative-Free Global Optimization for 3D Image Segmentation
Ken C. L. Wong, Mehdi Moradi
MICCAI, pp. 393-401, 2019

Boosting the Rule-Out Accuracy of Deep Disease Detection Using Class Weight Modifiers
Alexandros Karargyris, Ken C. L. Wong, Joy T. Wu, Mehdi Moradi, Tanveer Syeda-Mahmood
2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019), pp. 877-881

Artificial intelligence for point of care radiograph quality assessment
Satyananda Kashyap, Mehdi Moradi, Alexandros Karargyris, Joy T. Wu, Michael Morris, Babak Saboury, Eliot Siegel, Tanveer Syeda-Mahmood
SPIE Medical Imaging 10950, 2019

Age prediction using a large chest x-ray dataset
A. Karargyris, S. Kashyap, J. T. Wu, A. Sharma, M. Moradi, T. Syeda-Mahmood
SPIE Medical Imaging 10950, 2019

Identifying disease-free chest x-ray images with deep transfer learning
Ken C. L. Wong, Mehdi Moradi, Joy Wu, Tanveer Syeda-Mahmood
SPIE Medical Imaging 10950, 2019

Body part and imaging modality classification for a general radiology cognitive assistant
Chinyere Agunwa, Mehdi Moradi, Ken C. L. Wong, Tanveer Syeda-Mahmood
SPIE Medical Imaging 10949, 2019

Community structure detection from networks with weighted modularity
Nandinee Fariah Haq, Mehdi Moradi, Z Jane Wang
Pattern Recognition Letters122, 14--22, Elsevier, 2019

2018

3d segmentation with exponential logarithmic loss for highly unbalanced object sizes
Ken CL Wong, Mehdi Moradi, Hui Tang, Tanveer Syeda-Mahmood
International Conference on Medical Image Computing and Computer-Assisted Intervention, pp. 612--619, 2018

Bimodal network architectures for automatic generation of image annotation from text
Mehdi Moradi, Ali Madani, Yaniv Gur, Yufan Guo, Tanveer Syeda-Mahmood
International Conference on Medical Image Computing and Computer-Assisted Intervention, pp. 449--456, 2018

Integrating Deformable Modeling with 3D Deep Neural Network Segmentation
Hui Tang, Mehdi Moradi, Ken CL Wong, Hongzhi Wang, Ahmed El Harouni, Tanveer Syeda-Mahmood
Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support, pp. 377--384, Springer, 2018

Detecting anomalies from echocardiography using multi-view regression of clinical measurements
Lu, Allen and Dehghan, Ehsan and Veni, Gopalkrishna and Moradi, Mehdi and Syeda-Mahmood, Tanveer
Biomedical Imaging (ISBI 2018), 2018 IEEE 15th International Symposium on, pp. 1504--1508

Echocardiography segmentation based on a shape-guided deformable model driven by a fully convolutional network prior
Veni, Gopalkrishna and Moradi, Mehdi and Bulu, Hakan and Narayan, Girish and Syeda-Mahmood, Tanveer
Biomedical Imaging (ISBI 2018), 2018 IEEE 15th International Symposium on, pp. 898--902

Semi-supervised learning with generative adversarial networks for chest X-ray classification with ability of data domain adaptation
Madani, Ali and Moradi, Mehdi and Karargyris, Alexandros and Syeda-Mahmood, Tanveer
Biomedical Imaging (ISBI 2018), 2018 IEEE 15th International Symposium on, pp. 1038--1042

Segmentation of anatomical structures in cardiac CTA using multi-label V-Net
Tang, Hui and Moradi, Mehdi and El Harouni, Ahmed and Wang, Hongzhi and Veni, Gopalkrishna and Prasanna, Prasanth and Syeda-Mahmood, Tanveer
Medical Imaging 2018: Image Processing, pp. 1057407

Chest x-ray generation and data augmentation for cardiovascular abnormality classification
Madani, Ali and Moradi, Mehdi and Karargyris, Alexandros and Syeda-Mahmood, Tanveer
Medical Imaging 2018: Image Processing, pp. 105741M

Building medical image classifiers with very limited data using segmentation networks
Ken CL Wong, Tanveer Syeda-Mahmood, Mehdi Moradi
Medical image analysis49, 105--116, Elsevier, 2018

2017

Building Disease Detection Algorithms with Very Small Numbers of Positive Samples
Wong, Ken CL and Karargyris, Alexandros and Syeda-Mahmood, Tanveer and Moradi, Mehdi
International Conference on Medical Image Computing and Computer-Assisted Intervention, pp. 471--479, 2017
Abstract

Automatic Labeling of Continuous Wave Doppler Images Based on Combined Image and Sentence Networks
Mehdi Moradi, Yufan Guo, Yaniv Gur, Tanveer Syeda-Mahmood
IEEE 13th International Symposium on Biomedical Imaging (ISBI), 2017

A Multi-atlas Approach to Region of Interest Detection for Medical Image Classification
Wang, Hongzhi and Moradi, Mehdi and Gur, Yaniv and Prasanna, Prasanth and Syeda-Mahmood, Tanveer
International Conference on Medical Image Computing and Computer-Assisted Intervention, pp. 168--176, 2017

An algorithm for fully automatic detection of calcium in chest CT imaging
Tang, Hui and Moradi, Mehdi and Prasanna, Prasanth and Wang, Hongzhi and Syeda-Mahmood, Tanveer
Biomedical Imaging (ISBI 2017), 2017 IEEE 14th International Symposium on, pp. 265--269
Abstract

Towards an Efficient Way of Building Annotated Medical Image Collections for Big Data Studies
Gur, Yaniv and Moradi, Mehdi and Bulu, Hakan and Guo, Yufan and Compas, Colin and Syeda-Mahmood, Tanveer
Intravascular Imaging and Computer Assisted Stenting, and Large-Scale Annotation of Biomedical Data and Expert Label Synthesis, pp. 87--95, Springer, 2017

Automatic Extraction of Disease-Specific Features from Doppler Images
Mohammadreza Negahdar, Mehdi Moradi, Nripesh Parajuli, and Tanveer Syeda-Mahmood.
SPIE Conference on Computer-Aided Diagnosis, 2017

Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support: Third International Workshop, DLMIA 2017, and 7th International Workshop, ML-CDS 2017, Held in Conjunction with MICCAI 2017, Qu{\'e}bec City, QC, Canada, Septem
Cardoso, M Jorge and Arbel, Tal and Carneiro, Gustavo and Syeda-Mahmood, Tanveer and Tavares, Jo{\~a}o Manuel RS and Moradi, Mehdi and Bradley, Andrew and Greenspan, Hayit and Papa, Jo{\~a}o Paulo and Madabhushi, Anant and others
Mahmood, JMRS Tavares, M Moradi… - 2017 - books.google.com, Springer
Abstract

2016

Tree-Based Transforms for Privileged Learning
Moradi, Mehdi and Syeda-Mahmood, Tanveer and Hor, Soheil
International Workshop on Machine Learning in Medical Imaging, pp. 188--195, 2016

A hybrid learning approach for semantic labeling of cardiac CT slices and recognition of body position
Mehdi Moradi, Yaniv Gur, Hongzhi Wang, Prasanth Prasanna, Tanveer Syeda-Mahmood
Biomedical Imaging (ISBI), 2016 IEEE 13th International Symposium on, pp. 1418-1421

Medical sieve: A cognitive assistant for radiologists and cardiologists
T Syeda-Mahmood, E Walach, D Beymer, F Gilboa-Solomon, M Moradi, P Kisilev, D Kakrania, C Compas, H Wang, R Negadhar, Y Cao, T Baldwin, Y Guo, Y Gur, D Rajan, A Zlotnick, S Rabinovici-Cohen, R Ben-Ari, Amit Guy, P Prasanna, J Morey, O Boyko, S Hashoul
SPIE Medical Imaging, pp. 97850A-97850A-6, 2016

Lymphoma diagnosis in histopathology using a multi-stage visual learning approach
N Codella, M Moradi, M Matasar, T Syeda-Mahmood, JR Smith
SPIE Medical Imaging, pp. 97910H-97910H-7, 2016

Learning in data-limited multimodal scenarios: Scandent decision forests and tree-based features
S Hor, M Moradi
Medical Image Analysis34, 30-41, Elsevier, 2016

Tree-based transforms for privileged learning
Mehdi Moradi, Tanveer Syeda-Mahmood, Soheil Hor
Machine Learning in Medical Imaging, 2016

Identifying Patients at Risk for Aortic Stenosis Through Learning from Multimodal Data
Tanveer Syeda-Mahmood, Yufan Guo, Mehdi Moradi, D. Beymer, D. Rajan, Yu Cao, Yaniv Gur, and Mohammadreza Negahdar
Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016, pp. 238-245

A Cross-Modality Neural Network Transform for Semi-automatic Medical Image Annotation
Mehdi Moradi, Yufan Guo, Yaniv Gur, Mohammadreza Negahdar, and Tanveer Syeda-Mahmood
Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016, pp. 300-307, Springer, LNCS Series

2015

Ultrasound RF time series for classification of breast lesions
Uniyal, Nishant and Eskandari, Hani and Abolmaesumi, Purang and Sojoudi, Samira and Gordon, Paula and Warren, Linda and Rohling, Robert N and Salcudean, Septimiu E and Moradi, Mehdi
IEEE transactions on medical imaging 34(2), 652--661, IEEE, 2015
Abstract

Fracture detection in x-ray images through stacked random forests feature fusion
Cao, Yu and Wang, Hongzhi and Moradi, Mehdi and Prasanna, Prasanth and Syeda-Mahmood, Tanveer F
Biomedical Imaging (ISBI), 2015 IEEE 12th International Symposium on, pp. 801--805
Abstract

Viewpoint Recognition in Cardiac CT Images
Mehdi Moradi, Noel C Codella, Tanveer Syeda-Mahmood
Functional Imaging and Modeling of the Heart (FIMH 2015), LNCS 9126, pp. 180-188, Springer

Ultrasound-Based Detection of Prostate Cancer Using Automatic Feature Selection with Deep Belief Networks
Shekoofeh Azizi, Farhad Imani, Bo Zhuang, Amir Tahmasebi, Jin Tae Kwak, Sheng Xu, Nishant Uniyal, Baris Turkbey, Peter Choyke, Peter Pinto, Bradford Wood, Mehdi Moradi, Parvin Mousavi, Purang Abolmaesumi
Medical Image Computing and Computer-Assisted Intervention, MICCAI 2015, pp. 70-77

Scandent Tree: A Random Forest Learning Method for Incomplete Multimodal Datasets
S Hor, M Moradi
Medical Image Computing and Computer-Assisted Intervention, MICCAI 2015, , pp. 694-701

Augmenting MRI--transrectal ultrasound-guided prostate biopsy with temporal ultrasound data: a clinical feasibility study
Farhad Imani, Bo Zhuang, Amir Tahmasebi, Jin Tae Kwak, Sheng Xu, Harsh Agarwal, Shyam Bharat, Nishant Uniyal, Ismail Baris Turkbey, Peter Choyke, others
International journal of computer assisted radiology and surgery, 1--9, Springer, 2015

Characterization of aggressive prostate cancer using ultrasound RF time series
Amir Khojaste, Farhad Imani, Mehdi Moradi, David Berman, D Robert Siemens, Eric E Sauerberi, Alexander H Boag, Purang Abolmaesumi, Parvin Mousavi
SPIE Medical Imaging, pp. 94141A--94141A, 2015

Ultrasound RF time series for classification of breast lesions.
Nishant Uniyal, Hani Eskandari, Purang Abolmaesumi, Samira Sojoudi, Paula Gordon, Linda Warren, R Rohling, S Salcudean, Mehdi Moradi
IEEE Transactions on Medical Imaging 34(2), 652-661, IEEE , 2015

Multimodal classification of prostate tissue: a feasibility study on combining multiparametric MRI and ultrasound
Hussam Al-Deen Ashab, Nandinee Fariah Haq, Guy Nir, Piotr Kozlowski, Peter Black, Edward C Jones, S Larry Goldenberg, Septimiu E Salcudean, Mehdi Moradi
SPIE Medical Imaging, pp. 94141B--94141B, 2015

Prostate cancer detection from model-free T1-weighted time series and diffusion imaging
Nandinee F Haq, Piotr Kozlowski, Edward C Jones, Silvia D Chang, S Larry Goldenberg, Mehdi Moradi
SPIE Medical Imaging, pp. 94142X--94142X, 2015

A data-driven approach to prostate cancer detection from dynamic contrast enhanced MRI
Nandinee Fariah Haq, Piotr Kozlowski, Edward C Jones, Silvia D Chang, S Larry Goldenberg, Mehdi Moradi
Computerized Medical Imaging and Graphics 41(April), 37-45, Elsevier, 2015

2014

Ultrasound-Based Predication of Prostate Cancer in MRI-guided Biopsy
Nishant Uniyal, Farhad Imani, Amir Tahmasebi, Harsh Agarwal, Shyam Bharat, Pingkun Yan, Jochen Kruecker, Jin Tae Kwak, Sheng Xu, Bradford Wood, others
Clinical Image-Based Procedures. Translational Research in Medical Imaging, pp. 142--150, Springer, 2014

Solutions for Missing Parameters in Computer-Aided Diagnosis with Multiparametric Imaging Data
Hussam Al-Deen Ashab, Piotr Kozlowski, S Larry Goldenberg, Mehdi Moradi
Machine Learning in Medical Imaging, pp. 289--296, Springer, 2014

Multi-parametric 3D Quantitative Ultrasound Vibro-Elastography Imaging for Detecting Palpable Prostate Tumors
Omid Mohareri, Angelica Ruszkowski, Julio Lobo, Joseph Ischia, Ali Baghani, Guy Nir, Hani Eskandari, Edward Jones, Ladan Fazli, Larry Goldenberg, others
Medical Image Computing and Computer-Assisted Intervention--MICCAI 2014, pp. 561--568, Springer

Towards enabling ultrasound guidance in cervical cancer high-dose-rate brachytherapy
Adrian Wong, Samira Sojoudia, Marc Gaudet, Wan Wan Yap, Silvia D Chang, Purang Abolmaesumi, Christina Aquino-Parsons, Mehdi Moradi
SPIE Medical Imaging, pp. 90361Q--90361Q, 2014

Improved parameter extraction and classification for dynamic contrast enhanced MRI of prostate
Nandinee Fariah Haq, Piotr Kozlowski, Edward C Jones, Silvia D Chang, S Larry Goldenberg, Mehdi Moradi
SPIE Medical Imaging, pp. 903511--903511, 2014

Multiparametric 3D in vivo ultrasound vibroelastography imaging of prostate cancer: Preliminary results
Mehdi Moradi, S Sara Mahdavi, Guy Nir, Omid Mohareri, Anthony Koupparis, Louis-Olivier Gagnon, Ladan Fazli, Rowan G Casey, Joseph Ischia, Edward C Jones, others
Medical physics 41(7), 073505, American Association of Physicists in Medicine, 2014

2013

Statistical unit root test for edge detection in ultrasound images of vessels and cysts
Mehdi Moradi, S Sara Mahdavi, Julian Guerrero, Robert Rohling, Septimiu E Salcudean
Journal of Electronic Imaging 22(3), 033013--033013, International Society for Optics and Photonics, 2013

Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, Canada
Nishant Uniyal, Hani Eskandari, Purang Abolmaesumi, Samira Sojoudi, Paula Gordon, Linda Warren, Robert N Rohling, Septimiu E Salcudean, Mehdi Moradi
Ultrasonics Symposium (IUS), 2013 IEEE International, pp. 96--99

Ultrasound RF time series for tissue typing: first in vivo clinical results
Mehdi Moradi, S Sara Mahdavi, Guy Nir, Edward C Jones, S Larry Goldenberg, Septimiu E Salcudean
SPIE Medical Imaging, pp. 86701I--86701I, 2013

2012

MRI Confirmed Prostate Tissue Classification with Laplacian Eigenmaps of Ultrasound RF Spectra
Mehdi Moradi, Christian Wachinger, Andriy Fedorov, William M Wells, Tina Kapur, Luciant D Wolfsberger, Paul Nguyen, Clare M Tempany
Machine Learning in Medical Imaging, pp. 19--26, Springer, 2012

Use of Needle Track Detection to Quantify the Displacement of Stranded Seeds Following Prostate Brachytherapy
Julio R Lobo, Mehdi Moradi, Nick Chng, Ehsan Dehghan, William J Morris, Gabor Fichtinger, Septimiu E Salcudean
Medical Imaging, IEEE Transactions on 31(3), 738--748, IEEE, 2012

New Image-Based Techniques for Prostate Biopsy and Treatment
Mehdi Moradi
Technical Report, DTIC Document, 2012

Two solutions for registration of ultrasound to MRI for image-guided prostate interventions
Mehdi Moradi, Firdaus Janoos, Andriy Fedorov, Petter Risholm, Tina Kapur, Luciant D Wolfsberger, Paul L Nguyen, Clare M Tempany, William M Wells
Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE, pp. 1129--1132

Seed localization in ultrasound and registration to C-arm fluoroscopy using matched needle tracks for prostate brachytherapy
Mehdi Moradi, Seyedeh Sara Mahdavi, Ehsan Dehghan, Julio R Lobo, Sanchit Deshmukh, William James Morris, Gabor Fichtinger, Septimiu E Salcudean
Biomedical Engineering, IEEE Transactions on 59(9), 2558--2567, IEEE, 2012

Fusion of ultrasound B-mode and vibro-elastography images for automatic 3-D segmentation of the prostate
Seyedeh Sara Mahdavi, Mehdi Moradi, William J Morris, S Larry Goldenberg, Septimiu E Salcudean
Medical Imaging, IEEE Transactions on 31(11), 2073--2082, IEEE, 2012

Multiparametric MRI maps for detection and grading of dominant prostate tumors
Mehdi Moradi, Septimiu E Salcudean, Silvia D Chang, Edward C Jones, Nicholas Buchan, Rowan G Casey, S Larry Goldenberg, Piotr Kozlowski
Journal of Magnetic Resonance Imaging 35(6), 1403--1413, Wiley Online Library, 2012

2011

Medical Image Computing and Computer-Assisted Intervention-MICCAI 2011: 14th International Conference, Toronto, Canada, September 18-22, 2011, Proceedings
Gabor Fichtinger, Anne Martel, Terry Peters
2011 - books.google.com, Springer

Quantifying stranded implant displacement following prostate brachytherapy
Julio Lobo, Mehdi Moradi, Nick Chng, Ehsan Dehghan, Gabor Fichtinger, William Morris, Septimiu Salcudean
Medical Image Computing and Computer-Assisted Intervention--MICCAI 2011, 307--314, Springer

Towards intra-operative prostate brachytherapy dosimetry based on partial seed localization in ultrasound and registration to C-arm fluoroscopy
Mehdi Moradi, S Sara Mahdavi, Sanchit Deshmukh, Julio Lobo, Ehsan Dehghan, Gabor Fichtinger, William J Morris, Septimiu E Salcudean
Medical Image Computing and Computer-Assisted Intervention--MICCAI 2011, pp. 291--298, Springer Berlin Heidelberg

Tissue classification using depth-dependent ultrasound time series analysis: in-vitro animal study
Farhad Imani, Mohammad Daoud, Mehdi Moradi, Purang Abolmaesumi, Parvin Mousavi
SPIE Medical Imaging, pp. 79680F--79680F, 2011

Prostate implant reconstruction from C-arm images with motion-compensated tomosynthesis
Ehsan Dehghan, Mehdi Moradi, Xu Wen, Danny French, Julio Lobo, W James Morris, Septimiu E Salcudean, Gabor Fichtinger
Medical physics 38(10), 5290--5302, American Association of Physicists in Medicine, 2011

Brachytherapy seed reconstruction with joint-encoded C-arm single-axis rotation and motion compensation
Ehsan Dehghan, Ameet K Jain, Mehdi Moradi, Xu Wen, W James Morris, Septimiu E Salcudean, Gabor Fichtinger
Medical image analysis 15(5), 760--771, Elsevier, 2011

A robotic system for intra-operative trans-rectal ultrasound and ultrasound elastography in radical prostatectomy
Troy Adebar, Septimiu Salcudean, Sara Mahdavi, Mehdi Moradi, Christopher Nguan, Larry Goldenberg
Information Processing in Computer-Assisted Interventions, pp. 79--89, Springer, 2011

Evaluating the investors’ overreaction to financial measures: some evidence of Tehran stock exchange
Mehdi Moradi, Mahdi Salehi
International Journal of Academic Research 3(2), 921--929, 2011

A study of the reasons for shortcomings in establishment of internet financial reporting in Iran
Moradi Mehdi, Salehi Mahdi, Arianpoor Arash
African Journal of Business Management 5(8), 3312--3321, Academic Journals, 2011

Evaluation of visualization of the prostate gland in vibro-elastography images
S Sara Mahdavi, Mehdi Moradi, Xu Wen, William J Morris, Septimiu E Salcudean
Medical image analysis 15(4), 589--600, Elsevier, 2011

2010

Brachytherapy strand visibility in reflected power ultrasound images: Comparison of EchoStrand vs. Regular Strands Using 3D Visibility Profiles
Mehdi Moradi, Jack Zheng, Septimiu E Salcudean
Ultrasonics Symposium (IUS), 2010 IEEE, pp. 2356--2359

Automatic prostate segmentation using fused ultrasound B-mode and elastography images
S Sara Mahdavi, Mehdi Moradi, William J Morris, Septimiu E Salcudean
Medical Image Computing and Computer-Assisted Intervention--MICCAI 2010, pp. 76--83, Springer

Prostate brachytherapy seed reconstruction using c-arm rotation measurement and motion compensation
Ehsan Dehghan, Junghoon Lee, Mehdi Moradi, Xu Wen, Gabor Fichtinger, Septimiu Salcudean
Medical Image Computing and Computer-Assisted Intervention--MICCAI 2010, 283--290, Springer

A study of the integrity of Internet financial reporting: Empirical evidence of emerging economy
Mahdi Salehi, Mehdi Moradi, Arash Ariyan Pour
Global Journal of Management and Business Research 10(1), 2010

Tissue typing using ultrasound RF time series: Experiments with animal tissue samples
Mehdi Moradi, Purang Abolmaesumi, Parvin Mousavi
Medical physics 37(8), 4401--4413, American Association of Physicists in Medicine, 2010

High-throughput detection of prostate cancer in histological sections using probabilistic pairwise Markov models
James P Monaco, John E Tomaszewski, Michael D Feldman, Ian Hagemann, Mehdi Moradi, Parvin Mousavi, Alexander Boag, Chris Davidson, Purang Abolmaesumi, Anant Madabhushi
Medical image analysis 14(4), 617--629, Elsevier, 2010

2009

Tissue typing with ultrasound RF time series: Phantom studies
Mehdi Moradi, Parvin Mousavi, Robert Rohling, Purang Abolmaesumi
SPIE Medical Imaging, pp. 726516--726516, 2009

Preliminary results of an ultrasound segmentation method based on statistical unit-root test of b-scan radial intensity profiles
Mehdi Moradi, Julian Guerrero, Robert Rohling, Septimiu E Salcudean
Ultrasonics Symposium (IUS), 2009 IEEE International, pp. 1--4

Ultrasound elastography--an image guidance tool for prostate brachytherapy
Septimiu E Salcudean, Xu Wen, Seyedeh Sara Mahdavi, Mehdi Moradi, J William Morris, Ingrid Spadinger
Brachytherapy 8(2), 125--126, Elsevier, 2009

Automated detection of prostate cancer using wavelet transform features of ultrasound RF time series
Mohammad Aboofazeli, Purang Abolmaesumi, Mehdi Moradi, Eric Sauerbrei, Robert Siemens, Alexander Boag, Parvin Mousavi
SPIE Medical Imaging, pp. 72603J--72603J, 2009

Vibro-elastography for visualization of the prostate region: Method evaluation
Seyedeh Sara Mahdavi, Mehdi Moradi, Xu Wen, William J Morris, Septimiu E Salcudean
Medical Image Computing and Computer-Assisted Intervention--MICCAI 2009, pp. 339--347, Springer

Probabilistic pairwise markov models: Application to prostate cancer detection
James Monaco, John E Tomaszewski, Michael D Feldman, Mehdi Moradi, Parvin Mousavi, Alexander Boag, Chris Davidson, Purang Abolmaesumi, Anant Madabhushi
SPIE Medical Imaging, pp. 725903--725903, 2009

Augmenting detection of prostate cancer in transrectal ultrasound images using SVM and RF time series
Mehdi Moradi, Purang Mousavi, AH Boag, Eric E Sauerbrei, DR Siemens, Purang Abolmaesumi
Biomedical Engineering, IEEE Transactions on 56(9), 2214--2224, IEEE, 2009

2008

A new paradigm for ultrasound-based tissue typing in prostate cancer
Mehdi Moradi
2008 - qspace.library.queensu.ca, Canadian theses

Prostate cancer probability maps based on ultrasound RF time series and SVM classifiers
Mehdi Moradi, Parvin Mousavi, Robert Siemens, Eric Sauerbrei, Alexander Boag, Purang Abolmaesumi
Medical Image Computing and Computer-Assisted Intervention--MICCAI 2008, pp. 76--84, Springer

Detection of prostate cancer from whole-mount histology images using Markov random fields
J Monaco, J Tomaszewski, M Feldman, Mehdi Moradi, Parvin Mousavi, Alexander Boag, Chris Davidson, Purang Abolmaesumi, Anant Madabhushi
Workshop on Microscopic Image Analysis with Applications in Biology (in conjunction with MICCAI), 2008

2007

A new approach to analysis of RF ultrasound echo signals for tissue characterization: animal studies
Mehdi Moradi, Parvin Mousavi, Philip A Isotalo, David R Siemens, Eric E Sauerbrei, Purang Abolmaesumi
Medical Imaging, pp. 65130P--65130P, 2007

Ultrasound RF time series for detection of prostate cancer: Feature selection and frame rate analysis
Mehdi Moradi, P Mousavi, DR Siemens, EE Sauerbrei, A Boag, P Abolmaesumi
Proceedings of IEEE Ultrasonics Symposium, pp. 2493--2496, 2007

Discrete Fourier analysis of ultrasound RF time series for detection of prostate cancer
Mehdi Moradi, Parvin Mousavi, DR Siemens, EE Sauerbrei, Phil Isotalo, Alexandre Boag, Purang Abolmaesumi
Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE, pp. 1339--1342

Tissue characterization using fractal dimension of high frequency ultrasound RF time series
Mehdi Moradi, Parvin Mousavi, Purang Abolmaesumi
Medical Image Computing and Computer-Assisted Intervention--MICCAI 2007, pp. 900--908, Springer

Computer-aided diagnosis of prostate cancer with emphasis on ultrasound-based approaches: a review
Mehdi Moradi, Parvin Mousavi, Purang Abolmaesumi
Ultrasound in medicine \& biology 33(7), 1010--1028, Elsevier, 2007

2006

P3E-7 A New Feature For Detection Of Prostate Cancer Based On RF Ultrasound Echo Signals
Mehdi Moradi, Purang Abolmaesumi, Phillip A Isotalo, David R Siemens, Eric E Sauerbrei, Parvin Mousavi
Ultrasonics Symposium, 2006. IEEE, pp. 2084--2087

Detection of prostate cancer from RF ultrasound echo signals using fractal analysis
Mehdi Moradi, Purang Abolmaesumi, Phillip A Isotalo, David R Siemens, Eric E Sauerbrei, Parvin Mousavi
Engineering in Medicine and Biology Society, 2006. EMBS'06. 28th Annual International Conference of the IEEE, pp. 2400--2403

Deformable registration using scale space keypoints
Mehdi Moradi, Purang Abolmaesoumi, Parvin Mousavi
Medical Imaging, pp. 61442G--61442G, 2006

New features for automatic classification of human chromosomes: A feasibility study
Mehdi Moradi, S Kamaledin Setarehdan
Pattern Recognition Letters 27(1), 19--28, Elsevier, 2006

2005

Medical image registration based on distinctive image features from scale-invariant (SIFT) key-points
Mehdi Moradi, Purang Abolmaesumi
International Congress Series, pp. 1292, 2005

2004

A neural network based system for intrusion detection and classification of attacks
Mehdi Moradi, Mohammad Zulkernine
Proceedings of the 2004 IEEE international conference on advances in intelligent systems-theory and applications

2003

Automatic landmark detection on chromosomes' images for feature extraction purposes
M Moradi, SK Setarehdan, SR Ghaffari
Image and Signal Processing and Analysis, 2003. ISPA 2003. Proceedings of the 3rd International Symposium on, pp. 567--570

Automatic locating the centromere on human chromosome pictures
Mehdi Moradi, Seyed Kamaledin Setarehdan, SR Ghaffari
Computer-Based Medical Systems, 2003. Proceedings. 16th IEEE Symposium, pp. 56--61

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Mehdi Moradi