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مدل سازی ریاضی داده پزشکی

 

مدلسازی آماری تصویر با استفاده از فرایندهای تصادفی نامتغیر کروی و کاربرد آن در پردازش تصاویر پزشکی در حوزه تبدیلهای تُنُک مدل کردن صحیح سیگنال را می توان بعنوان هسته اولیه بسیاری از پردازشها دانست. در واقع مدل در نظر گرفته شده برای سیگنال، فرایند مورد نیاز برای پردازش از قبیل بهبود کیفیت [۱] ،کدینگ [۲] ،فشرده سازی [۳] ،استخراج ویژگی [۴] ،طبقه بندی [۵] و ... را تعریف می کند. بطور معمول در سیگنالها و تصاویر واقعی [۶] اعمال یک مدل معین [۷] بعلت پیچیدگی ذاتی و تاثیر عوامل متعدد در ثبت سیگنال مقدور نمی باشد. این مساله بویژه در مورد سیگنالهای حیاتی بعلت تاثیر ارگانهای مختلف داخل بدن بریکدیگر و دیگر عوامل محیطی و تکنیکی دوچندان می باشد. بر این اساس بطور معمول از مدلهای آماری [۸] همچون میدان تصادفی مارکف [۹] که فعل و انفعالات اجزای مختلف سیگنال را بصورت آماری و با استفاده از مدلهای مناسب شبیه سازی می نمایند جهت مدل کردن سیگنالها و تصاویر طبیعی استفاده می شود  .بطور معمول مدل کردن آماری تصاویر در حوزه تبدیلهای تُنُک [۱۰] با پیچیدگی کمتری در مقایسه حوزه تصویر صورت می پذیرد. بعنوان نمونه خواصی همچون دُم دار بودن توزیع کناری [۱۱]، ناهمبسته بودن تابع چگال احتمال توام [۱۲] ، همبستگی درون مقیاسی [۱۳] ، مابین مقیاسی [۱۴] و مابین زیرباندی [۱۵] از خصوصیات ضرایب ویولت تصاویر طبیعی می باشد.در این طرح با توجه به ویژگیهای فرایندهای تصادفی نامتغیر کروی [۱۶] درصدد مدل کردن خصوصیات اصلی تصاویر در حوزه تبدیلهای تُنُک می باشیم. با استفاده از آزمونهای مناسب این مدل برای داده های مختلف مورد ارزیابی قرار گرفته و در نهایت کاربرد این مدل در برخی پردازشهای تصاویر پزشکی مورد تحلیل قرار می گیرد.

 

 علاقمندان می توانند جهت کسب اطلاعات بیشتر و همکاری در اجرای طرح با آقای دکتر حسین ربانی تماس برقرار نمایند.

 

Enhancement

Coding

Compression

Feature extraction

Classification

Natural signals & images

 Deterministic

Statistical modeling

Markov Random Field

Sparse transforms

Long-tailed marginal distribution

Uncorrelated joint probability density function

Intrascale dependency

Interscale dependency

Inter-subband dependency

Spherically invariant random processes

 

لیست مقالات چاپ شده در این گروه پژوهشی به شرح زیر است:

 

Dehkordi, Maryam Taghizadeh, Saeed Sadri, and Alimohamad Doosthoseini.‎ ‪"A review of coronary vessel segmentation algorithms.‎"‬ Journal of medical signals and

sensors ۱.۱ (۲۰۱۱): ۴۹.

 

Sadri, Amir Reza, et al.‎ ‪"Impulse noise cancellation of medical images using wavelet networks and median filters.‎"‬ Journal of medical signals and sensors۲.۱ (۲۰۱۲): ۲۵.

 

Saghaei, Mahmoud.‎ ‪"An overview of randomization and minimization programs for randomized clinical trials.‎"‬ Journal of medical signals and sensors ۱.۱ (۲۰۱۱): ۵۵.

 

Rabbani, Hossein.‎ ‪"Statistical modeling of low SNR magnetic resonance images in wavelet domain using Laplacian prior and two-sided Rayleigh noise for visual quality improvement.‎"‬ Measurement Science Review ۱۱.۴ (۲۰۱۱): ۱۲۵-۱۳۰.

 

Rahimi, Farhad, and Hossein Rabbani.‎ ‪"A dual adaptive watermarking scheme in contourlet domain for DICOM images.‎"‬ Biomedical engineering online ۱۰.۱ (۲۰۱۱): ۵۳.

 

Rabbani, Hossein, and Saeed Gazor.‎ ‪"Local probability distribution of natural signals in sparse domains.‎"‬ International Journal of Adaptive Control and Signal Processing ۲۸.۱ (۲۰۱۴): ۵۲-۶۲.

 

 

A New Method for Multiple Sperm Cells Tracking.‎ Y Imani, N Teyfouri, MR Ahmadzadeh, M Golabbakhsh - Journal of medical signals and sensors, 2014

 

Speckle noise reduction of medical ultrasound images in complex wavelet domain using mixture priors.‎ H Rabbani, M Vafadust, P Abolmaesumi, S Gazor.Biomedical Engineering, IEEE Transactions on 55 (9)‎, 2152-2160

 

 

Image denoising in steerable pyramid domain based on a local Laplace prior.‎ H Rabbani Pattern Recognition 42 (9)‎, 2181-2193

 

Image/video denoising based on a mixture of Laplace distributions with local parameters in multidimensional complex wavelet domain.‎ H Rabbani, M Vafadust.‎ Signal Processing 88 (1)‎, 158-173

 

Wavelet-domain medical image denoising using bivariate Laplacian mixture model.‎ H Rabbani, R Nezafat, S Gazor.‎ Biomedical Engineering, IEEE Transactions on 56 (12)‎, 2826-2837

 

Wavelet-domain medical image denoising using bivariate Laplacian mixture model.‎ H Rabbani, R Nezafat, S Gazor.‎ Biomedical Engineering, IEEE Transactions on 56 (12)‎,

 

A dual adaptive watermarking scheme in contourlet domain for DICOM images.‎ F Rahimi, H Rabbani Biomedical engineering online 10 (1)‎, 

 

Image denoising based on a mixture of Laplace distributions with local parameters in complex wavelet domain.‎ H Rabbani, M Vafadust, S Gazor.‎ Image Processing, 2006 IEEE International Conference on, 2597-2600

 

Image denoising employing local mixture models in sparse domains.‎ H Rabbani, S Gazor.‎ Image Processing, IET 4 (5)‎, 413-428

 

Image denoising based on a mixture of bivariate Laplacian models in complex wavelet domain.‎ H Rabbani, M Vafadust, I Selesnick, S Gazor.‎ Multimedia Signal Processing, 2006 IEEE 8th Workshop on, 425-428

 

Image denoising employing a bivariate cauchy distribution with local variance in complex wavelet domain.H Rabbani, M Vafadust, S Gazor, I Selesnick.‎ Digital Signal Processing Workshop, 12th-Signal Processing Education .‎.‎.‎

 

Image denoising employing a mixture of circular symmetric Laplacian models with local parameters in complex wavelet domain H Rabbani, M Vafadust, I Selesnick, S Gazor.‎ Acoustics, Speech and Signal Processing, 2007.‎ ICASSP 2007.‎ IEEE .‎.‎.‎

 

Statistical modeling of low SNR magnetic resonance images in wavelet domain using Laplacian prior and two-sided Rayleigh noise for visual quality improvement H Rabbani.‎ Measurement Science Review 11 (4)‎, 125-130

 

Wavelet-based medical infrared image noise reduction using local model for signal and noise R Kafieh, H Rabbani Statistical Signal Processing Workshop (SSP), 2011 IEEE,

 

A visually imperceptible and robust image watermarking scheme in contourlet domain F Rahimi, H Rabani Signal Processing (ICSP), 2010 IEEE 10th International Conference on, 1817-1820۵۴۹-۵۵۲.

 

Image denoising based on a mixture of bivariate gaussian models in complex wavelet domain H Rabbani, M Vafadoost, I Selesnick, S Gazor Medical Devices and Biosensors, 2006.‎ 3rd IEEE/EMBS International Summer

 

Wavelet based image denoising with mixed Laplace model.‎ H Rabbani, M Vafadoost.‎ Proceedings of the 11th international computer society of Iran computer 

 

Detection of cancerous zones in mammograms using fractal modeling and classification by probabilistic neural network.‎ AS Noodeh, H Rabbani, AM Dehnavi, HA Noubari.‎ Biomedical Engineering (ICBME), 2010 17th Iranian Conference of, 1-4

 

Video denoising based on a bivariate cauchy distribution in 3-D complex wavelet domain H Rabbani, M Vafadust, S Gazor.‎ Signal Processing and Its Applications, 2007.‎ ISSPA 2007.‎ 9th International .‎.‎.‎

 

Wavelet based image denoising based on a mixture of laplace distributions.‎ H Rabbani, M Vafadoost Iranian Journal of Science and Technology 30 ‪(B6)‬, 711

 

Wavelet based image denoising with a mixture of Gaussian distributions with local parameters H Rabbani, M Vafadoost, I Selesnick.‎

 

Multimedia Signal Processing and Communications, 48th International .‎.‎.‎ Local probability distribution of natural signals in sparse domains.‎ H Rabbani, S Gazor.‎ International Journal of Adaptive Control and Signal Processing 28 (1)‎, 52-62

 

Shape adaptive estimation of variance in steerable pyramid domain and its application for spatially adaptive image enhancement H Rabbani.‎ Acoustics, Speech and Signal Processing, 2009.‎ ICASSP 2009.‎ IEEE .‎.‎.‎

 

A fast method for despeckling in wavelet domain using Laplacian prior and Rayleigh noise H Rabbani Information Technology and Applications in Biomedicine, 2008.‎ ITAB

 

Video denoising in three-dimensional complex wavelet domain using a doubly stochastic modeling H Rabbani, S Gazor.‎ Image Processing, IET 6 (9)‎, 1262-1274۲۰۰۸ ...

Image analysis in in vivo stem cell tracking.‎ H Rabbani, SH Javanmard.‎ Ann Rev Res Biol 1 (4)‎, 123-42

 

Image denoising in Curvelet transform domain using Gaussian mixture model with local parameters for distribution of noise-free coefficients.‎ H Rabbani, M Vafadust, S Gazor.‎ Medical Devices and Biosensors, 2007.‎ ISSS-MDBS 2007.‎ 4th IEEE/EMBS .‎.‎.‎

 

Image denoising in complex wavelet domain using a mixture of bivariate Laplacian distributions with local parameters.‎ H Rabbani, M Vafadust.‎ Defense and Security Symposium, 65750P-65750P-12

 

 

Image denoising based on a mixture of bivariate gaussian distributions with local parameters in complex wavelet domain.‎ H Rabbani.‎ Biomedical and Pharmaceutical Engineering, 2006.‎ ICBPE 2006.‎ International .‎.‎.‎

 

Circular symmetric Laplacian mixture model in wavelet diffusion for dental image denoising.‎ R Kafieh, H Rabbani, M Foroohandeh.‎ Journal of medical signals and sensors

 

A Comparison between the hp-version of Finite Element Method with EIDORS for Electrical Impedance Tomography.‎ N Saeedizadeh, S Kermani, H Rabbani.‎ Journal of medical signals and sensors 1 (3)‎, 200۲ (۲), ۱۰۳

 

Application of wavelets and fractal-based methods for detection of Microcalcification in Mammograms, A Comparative Analysis using Neural Network.‎ A SHIRAZI NOODEH, H AHMADI NOUBARI, A MEHRI DEHNAVI,Proceedings of SPIE, the International Society for Optical Engineering

 

Video deblurring in complex wavelet domain using local Laplace prior for enhancement and anisotropic spatially adaptive denoising for PSF detection.‎ H Rabbani .Image Processing (ICIP), 2010 17th IEEE International Conference on, 3329-3332

 

Wavelet-based denoising using local Laplace prior.‎ H Rabbani, M Vafadust, I Selesnick.‎ Optical Engineering+ Applications, 67012H-67012H-9

 

Medical Volume Noise Reduction Employing a Laplace Distribution with Local Variance for Modeling Contourlet Coefficients.‎ H Rabbani, M Vafadust, S Gazor.‎ Medical Devices and Biosensors, 2007.‎ ISSS-MDBS 2007.‎ 4th IEEE/EMBS .‎.‎.‎

 

Image denoising based on a mixture of circular symmetric Laplacian models in complex wavelet domain H Rabbani, M Vafadust, S Gazor.‎ Signal Processing and Its Applications, 2007.‎ ISSPA 2007.‎ 9th International .‎.‎.‎

 

Combination of graph theoretic grouping and time-frequency analysis for image segmentation R Kafieh, H Rabbani, S Gazor.‎ Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International .‎.‎.‎

 

A statistical model for 3D segmentation of retinal choroid in optical coherence tomography images F Ghasemi, H Rabbani .SPIE Medical Imaging, 90381K-90381K-6

 

Assessment of TGF-β3 on production of aggrecan by human articular chondrocytes in pellet culture system.‎ S Zamani, B Hashemibeni, E Esfandiari, A Kabiri, H Rabbani, R Abutorabi.‎ Advanced biomedical research 3

 

Endoscopy and Imaging (Diagnostic Imaging) Barrett detection and segmentation in endoscopy image by hybrid Fuzzy based level set method.‎ P Adibi, H Yousefibanaem, H Rabbani.‎ JOURNAL OF GASTROENTEROLOGY AND HEPATOLOGY 28, 263-263

 

Designing and Implementing Bioimpedance Spectroscopy Device by Measuring Impedance in a Mouse Tissue.‎ HM Dastjerdi, R Soltanzadeh, H Rabbani.‎ Journal of medical signals and sensors 3 (3)‎, 187

 

An Automatic Method for Measuring Lumbar Lordosis Angle.‎ A Farahabadi, I Farahabadi, H Rabbani, M Rezvani.‎ Journal of Isfahan Medical School 30 (200)‎

 

A new combined method for character recognizing in Farsi printed scripts using principal component analysis.‎ S Gashmard, AM Dehnavi, H Rabbani.‎ Proceedings of the International Conference on Advances in Computing .‎.‎.‎

 

A fast method for video deblurring based on a combination of gradient methods and denoising algorithms in Matlab and C environments.‎ Z Mirzadeh, R Mehri, H Rabbani.‎ IS&T/SPIE Electronic Imaging, 75290Y-75290Y-9

 

DEBLURRING OF ULTRASONIC IMAGES BASED ON ITERATIVE GRADIENT ALGORITHM, ANISOTROPIC WINDOW AND COMPLEX WAVELET-BASED DENOISING.‎ H RABBANI.‎ IRANIAN+JOURNAL+OF+BIOMEDICAL+ENGINEERING 3 (1)‎, 0

 

Edge Detection Using Discrete Complex Wavelet Transform.‎ H Rabbani, M Vafadoost, S Kasaie JOURNAL OF COMPUTATIONAL METHODS IN ENGINEERING ‪(ESTEGHLAL)‬

 

Abdominal CT image denoising based on a Laplace distribution with local variance in steerable pyramid domain .H Rabbani.‎ Information Technology and Applications in Biomedicine, 2008.‎ ITAB 2008 .‎.‎.‎

 

Local bivariate Cauchy distribution for video denoising in 3D complex wavelet domain.‎ H Rabbani, M Vafadust, I Selesnick.‎ Optical Engineering+ Applications, 66962G-

۶۶۹۶۲G-10

Modeling statistical properties of wavelets using a mixture of bivariate cauchy models and its application for image denoising in complex wavelet domain.‎ H Rabbani, M Vafadust, I Selesnick.‎ Optical Engineering+ Applications, 67012I-67012I-7

 

Wavelet-based Video Denoising Using Local Laplace Prior.‎ H RABBANI, M VAFADUST, I SELESNICK.‎ Proceedings of SPIE, the International Society for Optical Engineering .‎.‎.‎

 

Local bivariate Cauchy distribution for video denoising in 3D complex wavelet domain [6696-84]‎.‎ H Rabbani, M Vafadust, I Selesnick.‎ PROCEEDINGS-SPIE THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING 6696 (2 .‎.‎.‎

 

Modeling statistical properties of wavelets using a mixture of bivariate cauchy models and its application for image denoising in complex wavelet domain [6701-92]‎.‎ H Rabbani, M Vafadust, I Selesnick.‎ PROCEEDINGS-SPIE THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING 6701 (2 .‎.‎.‎

 

Paper: EDGE DETECTION USING DISCRETE COMPLEX WAVELET TRANSFORM.‎ H RABBANI, M VAFADOOST, S KASAIE

 

Paper: SEIZURE DIAGNOSIS IN CHILDREN BASED ON THE ELECTROENCEPHALOGRAM MODELLIND BY GAUSSIAN PROCESS MODEL.‎ Z AMINI, H RABBANI

 

Paper: DEBLURRING OF ULTRASONIC IMAGES BASED ON ITERATIVE GRADIENT ALGORITHM, ANISOTROPIC WINDOW AND COMPLEX WAVELET-BASED DENOISING.‎ H RABBANI

 

Paper: ISCHEMIA DETECTION BY ELECTROCARDIOGRAM IN WAVELET DOMAIN USING ENTROPY MEASURE. H RABBANI, MP MAHJOOB, E FARAHABADI, A FARAHABADI,

 

Automatic Analysis of Vectorcardiogram Sig-nal for Detection of Cardiovascular DiseasesAM DehnaviIsfahan University of Medical Sciences, Iran

 

تشخيص تشنج در کودکان مبتنی بر مدل‌سازی الکتروانسفاگرافی با مدل فرآیند گوسی, زهرا امینی, حسین ربانی. مجله دانشکده پزشکی اصفهان ۳۱ (۲۴۳), ۹۸۵-۹۹۶