Mr. Morteza Heidari Profile

Morteza Heidari

at Univ of Oklahoma

SPIE Involvement:

Author | Student Chapter Vice President

Publications (14)

Proceedings Article | 2 March 2020 Paper

A new case-based CAD scheme using a hierarchical SSIM feature extraction method to classify between malignant and benign cases

Morteza Heidari, Seyedehnafiseh Mirniaharikandehei, Gopichandh Danala, Yuchen Qiu, Bin Zheng

Proc. SPIE. 11318, Medical Imaging 2020: Imaging Informatics for Healthcare, Research, and Applications

KEYWORDS: Mammography, Computer aided diagnosis and therapy, Feature extraction, Breast, Image segmentation, Image analysis, Cancer, Chest, Computer aided design, Tumor growth modeling

Read Abstract +

Proceedings Article | 28 February 2020 Paper

A new interactive visual-aided decision-making supporting tool to predict severity of acute ischemic stroke

Gopichandh Danala, Sai Kiran Reddy Maryada, Morteza Heidari, Bappaditya Ray, Masoom Desai, Bin Zheng

Proc. SPIE. 11317, Medical Imaging 2020: Biomedical Applications in Molecular, Structural, and Functional Imaging

KEYWORDS: Brain, Blood, Image segmentation, Visualization, Artificial intelligence, Blood circulation, Neuroimaging, Computer aided design, Ischemic stroke, Computed tomography

Read Abstract +

Proceedings Article | 15 March 2019 Paper

Assessment of short-term breast cancer risk using a frequency domain correlation based imaging marker

Morteza Heidari, Alan Hollingsworth, Seyedehnafiseh Mirniaharikandehei, Gopichandh Danala, Yuchen Qiu, Hong Liu, Bin Zheng

Proc. SPIE. 10954, Medical Imaging 2019: Imaging Informatics for Healthcare, Research, and Applications

KEYWORDS: Mammography, Breast cancer, Cancer, Feature extraction, Machine learning, Breast, Tumor growth modeling, Performance modeling, Computer aided diagnosis and therapy, Image fusion

Read Abstract +

Proceedings Article | 15 March 2019 Presentation + Paper

Developing a computer-aided image analysis and visualization tool to predict region-specific brain tissue “at risk” for developing acute ischemic stroke

Gopichandh Danala, Morteza Heidari, Faranak Aghaei, Bappaditya Ray, Bin Zheng

Proc. SPIE. 10953, Medical Imaging 2019: Biomedical Applications in Molecular, Structural, and Functional Imaging

KEYWORDS: Brain, Image segmentation, Neuroimaging, Image analysis, Visualization, Artificial intelligence, Blood, Computer aided design, Blood circulation, Tissues

Read Abstract +

Proceedings Article | 15 March 2019 Presentation + Paper

Design, fabrication and evaluation of non-imaging, label-free pre-screening tool using quantified bio-electrical tissue profile

Ali Zarafshani, Yunzhi Wang, Seyedeh-Nafiseh Mirniaharikandehei, Morteza Heidari, Faranak Aghaei, Siqi Wang, Liangzhong Xiang, Bin Zheng

Proc. SPIE. 10953, Medical Imaging 2019: Biomedical Applications in Molecular, Structural, and Functional Imaging

KEYWORDS: Tissues, Breast, Breast cancer, Mammography, Cancer, Computer aided design, Tissue optics, Machine learning, Feature extraction, Mathematics

Read Abstract +

The design, fabrication, and performance of pre-screening tool using bioelectrical tissue profile is described. A probe of 8 electrodes using active-probe-sensing (AP-sensing) module was linearity distortion in the frequency response bonded to the 8 sub-regions of the breast surface forming the Bioimpedance transfer measurement system. Each measurement channel acquired the data from 1/8 of breast according to each breast defined in 8 sub-regions with split current injection channel and response behavioural bioelectricity detection. For this tissue bioelectrical measurement system, the electrodes were placed on the breast surface and before the bioelectrical profile were measured, we investigated a closed loop technique to compensate for the effects and measure the channel-skin-contact impedance. The AP-sensing module and connecting pads could be placed in the measurement electrode-Bras according to different breast size, and all measurement sub-regions should be equivalent for each case, but could be different in scale of 1- 2cm in related to different breast size. Bilateral structure was applied to compare each breast tissue bioelectrical properties in related to tissue behavioural in different frequency. Bioelectrical measurement efficiency was evaluated by the use of bioelectrical plots equivalent to a theoretical plot of the pure tissue profile versus average intracellular and extracellular and admittance behavioural of breast tissue able to flow electric field using Cole-Cole structure tissue modelling as a well-known bioelectrical tissue profile. The bioelectrical tissue profile as a pre-screening tool using theoretical pure tissue profiles and experimental measurements were evaluated in related a conventional Bioimpedance spectroscopy instruments. Breast bioelectrical profile of different breast density categories and average measurement values were significant, according to exist of fibro-glandular tissues in the total breast volume. The different of the theoretical values corresponding to pure fatty and fibro-glandular breast tissue behaviour was slightly different with the experimental measurements. We demonstrated the bioelectrical profile of breast tissue and extracting bioelectrical features that comparing in a bilateral structure to apply bioelectrical features as a supplementary data in the machine learning algorithms and present correspond risk factor for susceptibility of breast cancer in future studies. The preliminary equivalent theoretical and experimental results, evaluate the possibility of this new, non-imaging and label-free quantitative technique.

Proceedings Article | 15 March 2019 Paper

Developing a quantitative ultrasound image feature analysis scheme to assess tumor treatment efficacy using a mouse model

Seyedehnafiseh Mirniaharikandehei, Joshua VanOsdol, Morteza Heidari, Gopichandh Danala, Ashish Ranjan, Bin Zheng

Proc. SPIE. 10955, Medical Imaging 2019: Ultrasonic Imaging and Tomography

KEYWORDS: Tumors, Ultrasonography, Image segmentation, Feature extraction, Image analysis, Computer aided design, Image fusion, Cancer, Mouse models, Computer aided diagnosis and therapy

Read Abstract +

Proceedings Article | 13 March 2019 Presentation + Paper

Association of computer-aided detection results and breast cancer risk

Seyedehnafiseh Mirniaharikandehei, Morteza Heidari, Gopichandh Danala, Wei Qian, Yuchen Qiu, Bin Zheng

Proc. SPIE. 10950, Medical Imaging 2019: Computer-Aided Diagnosis

KEYWORDS: Mammography, Computer aided diagnosis and therapy, Computer aided design, Image fusion, Cancer, Computer-aided diagnosis, Breast cancer, Breast, Solid modeling, Image processing

Read Abstract +

Proceedings Article | 4 March 2019 Presentation + Paper

Assessment of a quantitative mammographic imaging marker for breast cancer risk prediction

Morteza Heidari, Seyedehnafiseh Mirniaharikandehei, Abolfazl Zargari Khuzani, Wei Qian, Yuchen Qiu, Bin Zheng

Proc. SPIE. 10952, Medical Imaging 2019: Image Perception, Observer Performance, and Technology Assessment

KEYWORDS: Breast cancer, Cancer, Computer aided diagnosis and therapy, Mammography, Tumor growth modeling, Solid modeling, Image fusion, Computer aided design, Performance modeling, Breast

Read Abstract +

Proceedings Article | 6 March 2018 Presentation + Paper

Applying a machine learning model using a locally preserving projection based feature regeneration algorithm to predict breast cancer risk

Morteza Heidari, Abolfazl Zargari Khuzani, Gopichandh Danala, Seyedehnafiseh Mirniaharikandehei, Wei Qian, Bin Zheng

Proc. SPIE. 10579, Medical Imaging 2018: Imaging Informatics for Healthcare, Research, and Applications

KEYWORDS: Machine learning, Breast cancer, Tumor growth modeling, Cancer, Mammography, Breast, Image segmentation, Data modeling, Tissues, Feature extraction

Read Abstract +

Proceedings Article | 6 March 2018 Presentation + Paper

A hybrid deep learning approach to predict malignancy of breast lesions using mammograms

Yunzhi Wang, Morteza Heidari, Seyedehnafiseh Mirniaharikandehei, Jing Gong, Wei Qian, Yuchen Qiu, Bin Zheng

Proc. SPIE. 10579, Medical Imaging 2018: Imaging Informatics for Healthcare, Research, and Applications

KEYWORDS: Mammography, Image segmentation, Computer aided design, Computer aided diagnosis and therapy, Breast, RGB color model, Machine learning, Feature extraction, CAD systems, Imaging informatics

Read Abstract +

Proceedings Article | 27 February 2018 Paper

Applying a CAD-generated imaging marker to assess short-term breast cancer risk

Seyedehnafiseh Mirniaharikandehei, Ali Zarafshani, Morteza Heidari, Yunzhi Wang, Faranak Aghaei, Bin Zheng

Proc. SPIE. 10575, Medical Imaging 2018: Computer-Aided Diagnosis

KEYWORDS: Mammography, Computer aided diagnosis and therapy, Breast cancer, Cancer, Computer aided design, Image fusion, Breast, Machine learning, Performance modeling, Computer-aided diagnosis

Read Abstract +

Proceedings Article | 27 February 2018 Presentation + Paper

Improving performance of breast cancer risk prediction using a new CAD-based region segmentation scheme

Morteza Heidari, Abolfazl Zargari Khuzani, Gopichandh Danala, Yuchen Qiu , Bin Zheng

Proc. SPIE. 10575, Medical Imaging 2018: Computer-Aided Diagnosis

KEYWORDS: Breast cancer, Image segmentation, Breast, Cancer, Tissues, Mammography, Feature extraction, Tumor growth modeling, Solid modeling, X-ray technology

Read Abstract +

Proceedings Article | 27 February 2018 Paper

Applying a new unequally weighted feature fusion method to improve CAD performance of classifying breast lesions

Abolfazl Zargari Khuzani, Gopichandh Danala, Morteza Heidari, Yue Du, Najmeh Mashhadi, Yuchen Qiu, Bin Zheng

Proc. SPIE. 10575, Medical Imaging 2018: Computer-Aided Diagnosis

KEYWORDS: Image segmentation, Breast, Computer aided design, Feature extraction, Image fusion, Mammography, Tumors, Computer aided diagnosis and therapy, Optimization (mathematics), Breast cancer

Read Abstract +

Proceedings Article | 27 February 2018 Paper

Computer-aided classification of breast masses using contrast-enhanced digital mammograms

Gopichandh Danala, Faranak Aghaei, Morteza Heidari, Teresa Wu, Bhavika Patel, Bin Zheng

Proc. SPIE. 10575, Medical Imaging 2018: Computer-Aided Diagnosis

KEYWORDS: Image segmentation, Breast, Mammography, Computer aided diagnosis and therapy, Computer aided design, Image classification, Tumors, Tissues, Digital mammography, Image acquisition, Image contrast enhancement

Read Abstract +

Showing 5 of 14 publications

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Keywords/Phrases

Search In:

Publication Years