Material Detection Based on GMM-Based Power Density Function Estimation and Fused Image in Dual-Energy X-ray Images

Pourghassem, Hossein; Fesharaki, Nooshin Jafari; Tahmasebi, Ava

doi:10.1109/cicn.2012.142

Cited by 4 publications

(2 citation statements)

References 7 publications

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“…A novel algorithm for material recognition to be used in baggage control points at the airports and other checkpoints was developed in [ 39 ]. This algorithm is based on dual-energy analysis combined with spectral analysis of digital radiation images of the objects under inspection.…”

Section: Technology Used For X-ray Screeningmentioning

confidence: 99%

Application and Advances in Radiographic and Novel Technologies Used for Non-Intrusive Object Inspection

Mamchur

Pekša

Clainche

et al. 2022

Sensors

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Increase in trading and travelling flows has resulted in the need for non-intrusive object inspection and identification methods. Traditional techniques proved to be effective for decades; however, with the latest advances in technology, the intruder can implement more sophisticated methods to bypass inspection points control techniques. The present study provides an overview of the existing and developing techniques for non-intrusive inspection control, current research trends, and future challenges in the field. Both traditional and developing methods, techniques, and technologies were analyzed with the use of traditional and novel sensor types. Finally, it was concluded that the improvement of non-intrusive inspection experience could be gained with the additional use of novel types of sensors (such as biosensors) combined with traditional techniques (X-ray inspection).

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Section: Technology Used For X-ray Screeningmentioning

confidence: 99%

Application and Advances in Radiographic and Novel Technologies Used for Non-Intrusive Object Inspection

Mamchur

Pekša

Clainche

et al. 2022

Sensors

View full text Add to dashboard Cite

show abstract

“…In a general manner, the GMM distribution can be written as a linear superposition of Gaussians [39] in the form…”

Section: Distribution Function-based Dependency Probabilitymentioning

confidence: 99%

Optimal Query-Based Relevance Feedback in Medical Image Retrieval Using Score Fusion-Based Classification

Behnam

Pourghassem

2014

J Digit Imaging

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In this paper, a new content-based medical image retrieval (CBMIR) framework using an effective classification method and a novel relevance feedback (RF) approach are proposed. For a large-scale database with diverse collection of different modalities, query image classification is inevitable due to firstly, reducing the computational complexity and secondly, increasing influence of data fusion by removing unimportant data and focus on the more valuable information. Hence, we find probability distribution of classes in the database using Gaussian mixture model (GMM) for each feature descriptor and then using the fusion of obtained scores from the dependency probabilities, the most relevant clusters are identified for a given query. Afterwards, visual similarity of query image and images in relevant clusters are calculated. This method is performed separately on all feature descriptors, and then the results are fused together using feature similarity ranking level fusion algorithm. In the RF level, we propose a new approach to find the optimal queries based on relevant images. The main idea is based on density function estimation of positive images and strategy of moving toward the aggregation of estimated density function. The proposed framework has been evaluated on ImageCLEF 2005 database consisting of 10,000 medical X-ray images of 57 semantic classes. The experimental results show that compared with the existing CBMIR systems, our framework obtains the acceptable performance both in the image classification and in the image retrieval by RF.

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An Automatic Fuzzy-based Multi-temporal Brain Digital Subtraction Angiography Image Fusion Algorithm Using Curvelet Transform and Content Selection Strategy

Momeni

Pourghassem

2014

J Med Syst

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Recently image fusion has prominent role in medical image processing and is useful to diagnose and treat many diseases. Digital subtraction angiography is one of the most applicable imaging to diagnose brain vascular diseases and radiosurgery of brain. This paper proposes an automatic fuzzy-based multi-temporal fusion algorithm for 2-D digital subtraction angiography images. In this algorithm, for blood vessel map extraction, the valuable frames of brain angiography video are automatically determined to form the digital subtraction angiography images based on a novel definition of vessel dispersion generated by injected contrast material. Our proposed fusion scheme contains different fusion methods for high and low frequency contents based on the coefficient characteristic of wrapping second generation of curvelet transform and a novel content selection strategy. Our proposed content selection strategy is defined based on sample correlation of the curvelet transform coefficients. In our proposed fuzzy-based fusion scheme, the selection of curvelet coefficients are optimized by applying weighted averaging and maximum selection rules for the high frequency coefficients. For low frequency coefficients, the maximum selection rule based on local energy criterion is applied to better visual perception. Our proposed fusion algorithm is evaluated on a perfect brain angiography image dataset consisting of one hundred 2-D internal carotid rotational angiography videos. The obtained results demonstrate the effectiveness and efficiency of our proposed fusion algorithm in comparison with common and basic fusion algorithms.

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Material Detection Based on GMM-Based Power Density Function Estimation and Fused Image in Dual-Energy X-ray Images

Cited by 4 publications

References 7 publications

Application and Advances in Radiographic and Novel Technologies Used for Non-Intrusive Object Inspection

Application and Advances in Radiographic and Novel Technologies Used for Non-Intrusive Object Inspection

Optimal Query-Based Relevance Feedback in Medical Image Retrieval Using Score Fusion-Based Classification

An Automatic Fuzzy-based Multi-temporal Brain Digital Subtraction Angiography Image Fusion Algorithm Using Curvelet Transform and Content Selection Strategy

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