Mena Gaed

According to our database1, Mena Gaed authored at least 21 papers between 2013 and 2020.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2020
Evaluating texture-based prostate cancer classification on multi-parametric magnetic resonance imaging and prostate specific membrane antigen positron emission tomography.
Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020

2019
Automatic high-grade cancer detection on prostatectomy histopathology images.
Proceedings of the Medical Imaging 2019: Digital Pathology, 2019

Texture-based prostate cancer classification on MRI: how does inter-class size mismatch affect measured system performance?
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, 2019

2018
Stochastic Modeling of Temporal Enhanced Ultrasound: Impact of Temporal Properties on Prostate Cancer Characterization.
IEEE Trans. Biomed. Eng., 2018

Automatic cancer detection and localization on prostatectomy histopathology images.
Proceedings of the Medical Imaging 2018: Digital Pathology, 2018

Development of a computer aided diagnosis model for prostate cancer classification on multi-parametric MRI.
Proceedings of the Medical Imaging 2018: Computer-Aided Diagnosis, 2018

2017
Models of temporal enhanced ultrasound data for prostate cancer diagnosis: the impact of time-series order.
Proceedings of the Medical Imaging 2017: Image-Guided Procedures, 2017

2016
How does prostate biopsy guidance error impact pathologic cancer risk assessment?
Proceedings of the Medical Imaging 2016: Image-Guided Procedures, Robotic Interventions, and Modeling, San Diego, California, United States, 27 February, 2016

Classification of prostate cancer grade using temporal ultrasound: in vivo feasibility study.
Proceedings of the Medical Imaging 2016: Image-Guided Procedures, Robotic Interventions, and Modeling, San Diego, California, United States, 27 February, 2016

Prostate Cancer: Improved Tissue Characterization by Temporal Modeling of Radio-Frequency Ultrasound Echo Data.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016, 2016

Fusion of multi-parametric MRI and temporal ultrasound for characterization of prostate cancer: in vivo feasibility study.
Proceedings of the Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, California, United States, 27 February, 2016

2015
Computer-Aided Prostate Cancer Detection Using Ultrasound RF Time Series: In Vivo Feasibility Study.
IEEE Trans. Medical Imaging, 2015

Ultrasound-Based Characterization of Prostate Cancer Using Joint Independent Component Analysis.
IEEE Trans. Biomed. Eng., 2015

Using Hidden Markov Models to capture temporal aspects of ultrasound data in prostate cancer.
Proceedings of the 2015 IEEE International Conference on Bioinformatics and Biomedicine, 2015

2014
A dimensionless dynamic contrast enhanced MRI parameter for intra-prostatic tumour target volume delineation: initial comparison with histology.
Proceedings of the Medical Imaging 2014: Image-Guided Procedures, 2014

Accuracy and variability of tumor burden measurement on multi-parametric MRI.
Proceedings of the Medical Imaging 2014: Digital Pathology, 2014

Multiparametric MR imaging of prostate cancer foci: assessing the detectability and localizability of Gleason 7 peripheral zone cancers based on image contrasts.
Proceedings of the Medical Imaging 2014: Digital Pathology, 2014

2013
Prostate Histopathology: Learning Tissue Component Histograms for Cancer Detection and Classification.
IEEE Trans. Medical Imaging, 2013

Toward quantitative digital histopathology for prostate cancer: comparison of inter-slide interpolation methods for tumour measurement.
Proceedings of the Medical Imaging 2013: Digital Pathology, 2013

3D prostate histology reconstruction: an evaluation of image-based and fiducial-based algorithms.
Proceedings of the Medical Imaging 2013: Digital Pathology, 2013

Ultrasound-Based Characterization of Prostate Cancer: An in vivo Clinical Feasibility Study.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2013, 2013


  Loading...