Journal of Biomedical Science and Engineering

Journal of Biomedical Science and Engineering

ISSN Print: 1937-6871
ISSN Online: 1937-688X
www.scirp.org/journal/jbise
E-mail: jbise@scirp.org
"A diffusion-weighted imaging based diagnostic system for early detection of prostate cancer"
written by Ahmad Firjani, Ahmed Elnakib, Fahmi Khalifa, Georgy Gimel’farb, Mohamed Abou El-Ghar, Adel Elmaghraby, Ayman El-Baz,
published by Journal of Biomedical Science and Engineering, Vol.6 No.3A, 2013
has been cited by the following article(s):
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[1] Supervised classifiers of prostate cancer
2020
[2] MRI Imaging of Seminal Vesicle Invasion (SVI) in Prostate Adenocarcinoma
2019
[3] On Computer-Aided Diagnosis of Prostate Cancer from MRI using Machine Intelligence Techniques
2019
[4] 18 Diagnosing Prostate Cancer Based on Deep Learning with Constraint Autoencoder
2019
[5] 19 MRI Imaging of Seminal Vesicle Invasion (SVI) in Prostate Adenocarcinoma
2019
[6] Diffusion-weighted MRI based System for the Early Detection of Prostate Cancer
2018
[7] A new CNN-based system for early diagnosis of prostate cancer
2018
[8] Computer-aided diagnosis of clinically significant prostate cancer from MRI images using sparse autoencoder and random forest classifier
Biocybernetics and Biomedical Engineering, 2018
[9] A Novel ADCs-Based CNN Classification System for Precise Diagnosis of Prostate Cancer
2018
[10] A New Fast Framework for Early Detection of Prostate Cancer Without Prostate Segmentation
2018
[11] Computer-Aided Diagnosis of Prostate Cancer on Diffusion Weighted Imaging: A Technical Review
2018
[12] Early diagnosis and staging of prostate cancer using magnetic resonance imaging: State of the art and perspectives
2017
[13] Diffusion-weighted magnetic resonance imaging in diagnosing graft dysfunction: a non-invasive alternative to renal biopsy.
2017
[14] A novel MRA-based framework for the detection of changes in cerebrovascular blood pressure.
2017
[15] Deformable model-based methods for image segmentation................... and Robert Keynton
Biomedical Image Segmentation, 2016
[16] A new NMF-autoencoder based CAD system for early diagnosis of prostate cancer
2016
[17] Application of an unsupervised multi-characteristic framework for intermediate-high risk prostate cancer localization using diffusion-weighted MRI
Magnetic Resonance Imaging, 2016
[18] Computational methods for the analysis of functional 4D-CT chest images.
2016
[19] A Comprehensive Non-invasive Framework for Diagnosing Prostate Cancer
Computers in Biology and Medicine, 2016
[20] A CAD system for early diagnosis of autism using different imaging modalities.
2016
[21] In vivo MRI based prostate cancer localization with random forests and auto-context model
Computerized Medical Imaging and Graphics, 2016
[22] Sparse feature learning for image analysis in segmentation, classification, and disease diagnosis.
2016
[23] A novel NMF-based CAD system for early diagnosis of prostate cancer by using 4-D diffusion-weighted magnetic resonance images (DW-MRI)
2016
[24] Image-Based Computer-Aided Diagnostic System for Early Diagnosis of Prostate Cancer
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2016, 2016
[25] A non-invasive diagnostic system for early assessment of acute renal transplant rejection.
2016
[26] Computer-aided diagnostic tool for early detection of prostate cancer
2016
[27] Biomedical Image Segmentation: Advances & Trends
2016
[28] A novel framework for automatic segmentation of kidney from DW-MRI
2015
[29] Using morphological transforms to enhance the contrast of medical images
The Egyptian Journal of Radiology and Nuclear Medicine, 2015
[30] Computerized detection of cancer in multi-parametric prostate MRI
2015
[31] A level set-based framework for 3D kidney segmentation from diffusion MR images
Image Processing (ICIP), 2015 IEEE International Conference on, 2015
[32] Fast and robust hybrid framework for infant brain classification from structural MRI: a case study for early diagnosis of autism.
2014
[33] In-vitro and in-vivo diagnostic techniques for prostate cancer: A review
Journal of Biomedical Nanotechnology, 2014
[34] Geert Litjens is with Diagnostic Image Analysis Group, Radboud University Nijmegen Medical Centre, Geert Grootteplein-Zuid 10, 6525GA Nijmegen, The Netherlands.(email: g. litjens@ rad. umcn. nl)
2014
[35] A Novel NMF Guided Level-set for DWI Prostate Segmentation
J Comput Sci Syst Biol, 2014
[36] FAST AND ROBUST HYBRID FRAMEWORK FOR INFANT BRAIN CLASSIFICATION FROM STRUCTRUAL MRI: A CASE STUDY FOR EARLY DIAGNOSIS OF AUTISM
Doctoral dissertation, University of Louisville, 2014
[37] A NOVEL NMF-BASED DWI CAD FRAMEWORK FOR PROSTATE CANCER
Doctoral dissertation, University of Louisville, 2014
[38] ANALYSIS OF CONTRAST-ENHANCED MEDICAL IMAGES
Doctoral dissertation, University of Louisville, 2014
[39] A novel NMF-based DWI CAD framework for prostate cancer.
2014
[40] Analysis of contrast-enhanced medical images.
2014
[41] MRI-based diagnostic system for early detection of prostate cancer
Biomedical Sciences and Engineering Conference (BSEC), 2013. IEEE, 2013
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