Volume 17 (2023)
Volume 16 (2022)
Volume 15 (2021)
Volume 14 (2020)
Volume 13 (2019)
Volume 12 (2018)
Volume 11 (2017)
Volume 10 (2016)
Volume 9 (2015)
Volume 8 (2014)
Volume 7 (2013)
Volume 6 (2012)
Volume 5 (2011)
Volume 4 (2010)
Volume 3 (2009)
Volume 2 (2008)
Volume 1 (2007)
Volume -2 (2005)
Volume -1 (2004)
Medical Ultrasound / Diagnostic Sonography / Ultrasonography
Selection of Effective Features from Raw US RF Signals to Enhance Intelligent Breast Lesion Classification Using Machine Learning

Mahsa Arab; Ali Fallah; Saeid Rashidi; Maryam Mehdizadeh Dastjerdi; Nasrin Ahmadinejad

Volume 17, Issue 2 , September 2023, , Pages 140-150

  Breast cancer stands as the most prevalent form of cancer among women, with over 80% of early-stage breast abnormalities being benign. Timely detection is therefore crucial for prompt intervention. Ultrasound Radio Frequency (US RF) signals represent a non-invasive, and real-time screening method for ...  Read More

Biomedical Signal Processing / Medical Signal Processing / Biosignal Processing
Classification of Normal and Abnormal Heart Sounds Using Machine Learning Techniques

Parastoo Sadeghinia; Hamed Danandeh Hesar

Volume 16, Issue 3 , December 2022, , Pages 271-287

  Phonocardiography (PCG) signals provide valuable information about the heart valves .These auditory signals can be useful in the early diagnosis of heart diseases. Automatic heart sound classification has a promising potential in the field of heart pathology. In this research, a new method based on machine ...  Read More

Biomedical Image Processing / Medical Image Processing
An Efficient Method for Automatic Multi-Class Classification of SD-OCT Images of Human Eye Based on RNFL layer and the IS/OS Junction Detection and Ensemble Decision Tree

Sina Shamekhi

Volume 16, Issue 2 , September 2022, , Pages 95-113

  Intuitive examination of retinal layers in Spectral-Domain Optical Coherence Tomography (SD-OCT) images is one of the main methods used by physicians to diagnose retinal diseases. This method faces challenges such as noise and image complexity and the proximity of retinal layers. In recent years, the ...  Read More

Biomedical Signal Processing / Medical Signal Processing / Biosignal Processing
A New EEG Processing Approach using the Chebyshev Chaotic Map: Application in Anxiety Classification

Faezeh Daneshmand-Bahman; Ateke Goshvarpour

Volume 16, Issue 2 , September 2022, , Pages 115-131

  Anxiety disorders are one of the most common and debilitating mental disorders worldwide. On the other hand, since 2019, with the outbreak of Covid-19, anxiety has increased among people, especially the medical staff. Currently, anxiety is diagnosed (when the symptoms are severe enough) using a questionnaire ...  Read More

Biomedical Signal Processing / Medical Signal Processing / Biosignal Processing
Arrhythmia Classification Improvement by Individually Mapping the Feature Space of each patient

Hamid Shafaatfar; Mehdi Taghizadeh; Morteza Valizadeh; Mohamad Hossein Fatehi

Volume 16, Issue 2 , September 2022, , Pages 147-158

  Automatic detection of cardiac arrhythmias is very important for the successful treatment of heart disease and machine learning is used for this purpose. To correctly classify arrhythmic classes, it is important to extract the appropriate features to distinguish between different classes. In this paper, ...  Read More

Biomedical Signal Processing / Medical Signal Processing / Biosignal Processing
Classification of Alcoholic and Non-Alcoholic Individuals based on Frequency and Non-Frequency Features of Electroencephalogram Signal

Maryam Dorvashi; Neda Behzadfar; Ghazanfar Shahgholian

Volume 14, Issue 2 , July 2020, , Pages 109-119

  Consumption of alcohol contributes to disorders in brain. In this study, in order to detect the consumption of alcohol, electroencephalogram (EEG) signal of 20 participants (10 alcoholic and 10 control subjects) recorded by 64 channels was investigated. Frequency and non-frequency features of EEG signal ...  Read More

Feature Selection based on Information Theory to Select Effective Genes for Diagnosis of Cancer Subtypes using Microarray Data

Abolfazl Tabatabaei; Vali Derhami; Razieh Sheikhpour; Mohammad-Reza Pajoohan

Volume 13, Issue 4 , December 2019, , Pages 337-348

  Feature selection is a well-known preprocessing technique in machine learning, data mining and especially bioinformatics microarray analysis with a high-dimension, low-sample-size (HDLSS) data. The diagnosis of genes responsible for disease using microarray data is an important issue to promoting knowledge ...  Read More

Biomedical Signal Processing / Medical Signal Processing / Biosignal Processing
Designing a Deep Fuzzy Rule-Based System for Depression Staging

Raheleh Davoodi; Mohammad Hasan Moradi

Volume 12, Issue 1 , June 2018, , Pages 25-39

  Depression is one of the most common mental disorders in the current century where early diagnosis can result in better treatment. One of the depression diagnostic methods is the analysis of the brain electrical signals. In this paper, we are seeking for a method to distinguish among the levels of the ...  Read More

Bioinformatics / Biomedical Informatics / Medical Informatics / Health Informatics
Dimensionality Reduction of Binding Site Sequence Data on Human Genome Using a Deep Autoencoder Neural Network

Hossein Bankikoshki; Seyed Ali Seyyedsalehi; Fatemeh Zare Mirakabad

Volume 11, Issue 3 , September 2017, , Pages 219-230

  The use of genomic nucleotide sequences as biochemical signals in machine learning methods is possible by converting these sequences into numerical codes. This conversion results in an unrealistic increase in the dimension of the data and encounters some data analysis operations such as visualization ...  Read More

Biomedical Image Processing / Medical Image Processing
Full Automatic Classification of Suspicious Areas in Breast Thermo Images for Early Cancer Detection

Amir Ehsan Lashkari; Fatemeh Pak; Mohammad Firouzmand

Volume 9, Issue 1 , April 2015, , Pages 71-84

  Breast cancer is the most common type of cancer among women. The important key to treat the breast cancer is early detection of it because according to many pathological studies more 80% of all abnormalities are still benign at primary stages; so in recent years, many studies and extensive research done ...  Read More

Biomedical Image Processing / Medical Image Processing
Voxel Based Treatment Prediction Using Diffusion Anisotropy Indices and Spatial Information in Glioblastoma Multiform Tumor

Hadi Sabahi; Hamid Soltanian Zadeh; Lisa Scarpace; Tom Mikkelsen

Volume 5, Issue 4 , June 2011, , Pages 289-295

  In this paper, we propose a method to predict the outcome of Bevacizumab therapy on Glioblastoma Multiform (GBM) tumors. The method uses diffusion anisotropy indices (DAI) and spatial information to predict the treatment response of each tumor voxel. These DAIs are Fractional Anisotropy, Mean Diffusivity, ...  Read More

Development of P300 detection by Combination of Time, Frequency and Spatial Feature Extraction Methods

Zahra Amini; Vahid Abootalebi; Mohammad Taghi Sadeghi

Volume 4, Issue 4 , June 2010, , Pages 293-306

  The aim of this paper is to design a pattern recognition based system to detect P300 component in multi-channel electroencephalogram (EEG) trials. This system has two main blocks, feature extraction and classification. In feature extraction block, in addition to conventional features namely morphological, ...  Read More

Biomedical Signal Processing / Medical Signal Processing / Biosignal Processing
Real-Time Classification of Surface Electromyogram Signal using Correntropy

Mohammad Mehdi Ramezani; Ahmad Reza Sharafat

Volume 4, Issue 2 , June 2010, , Pages 123-134

  In this paper, we propose a novel approach for classification of surface electromyogram (sEMG) signal with a view to controlling myoelectric prosthetic devices. The sEMG signal generated during isometric contraction is modeled by a stochastic process whose probability density function (PDF) is non- Gaussian ...  Read More

ERP Analysis Of Episodic Memory Recall

Majid Ghoshuni; Mohammad Ali Khalilzadeh; Ali Moghimi

Volume 1, Issue 4 , June 2007, , Pages 251-267

  Episodic memory is the explicit recollection of incidents occurred at a particular time and place in One’s Personal Past. In This Study, Detection of Episodic Memory Activity In Event Related Potentials (ERPs) was done. ERPs were recorded while the subjects made old/new recognition judgments on ...  Read More

Biomedical Image Processing / Medical Image Processing
Classification Of Cardiac Arrhythmias By Learning Vector Quantizater Network And Based On The Extracted Features From The Wavelet Transformation

Jamal Esmaeilpour; Sattar Mirzakouchaki; Jalil Seyfali Harsini; Abdorrahim Kadkhoda Mohammadi

Volume 1, Issue 3 , June 2007, , Pages 167-176

  In this paper, the role of Vector Quantizer Neural Network in classification of six types of ECG signals has been investigated using the features that extracted from Daubechies6 Wavelet transformation. The six types of signals are: normal beat, left bundle branch block beat, right bundle branch block ...  Read More