Dynamic contrast enhancement based on histogram specification

Dual-energy contrast-enhanced spectral mammography (CESM) is a new promising method for visualizing pathological changes in breast, which combines digital mammography and a functional assessment of vascularization using intravenous contrast ehnancement. According to accumulated experience CESM is well tolerated by patients and is similar to magnetic resonance imaging with dynamic contrast enhancement (MRI with DCE), but at the same time, CESM is more affordable and can be performed in patients with contraindications for MRI. However, few studies have been conducted to evaluate the role of CESM. In the world literature, interpretation of contrast images is based only on the degree of accumulation of the contrast agent, but we propose a more detailed assessment of the structure of the hypervascular lesions by highlighting the contrast enhancement patterns. Objective: to determine the diagnostic effectiveness of CESM using the contrast enhancement patterns in malignant and benign lesions. Materials and methods. 239 women with suspicious for breast cancer lesions were examined from August 2018 to December 2019. The mean age of the women was 51 years. 322 lesions were revealed, 149 (46.3%) were malignant, 173 (53.7%) were benign. All lesions were histologically confirmed. As a result of the analysis of our data, 9 types of contrast enhancement patterns were distinguished: reticulate, granular, annular, diffuse-spherical, lacunar, cloud-like, heterogeneous-annular, point, cotton-like. Results. Using an additional diagnostic feature - contrast enhancement patterns in lesions, increased the sensitivity of CESM from 91.3% to 98.0% (p=0.26), specificity from 80.3% to 93, 6% (p=0.013), accuracy from 85.4 to 95.7% (p=0.004) in comparison with using of only one feature of contrast enhancement intensity in the differential diagnosis of malignant and benign lesions. Conclusion: thus, this approach of interpreting subtraction images allows to increase the efficiency of CESM in diagnosis of breast cancer.

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Dynamic contrast enhancement in widefield microscopy using projector-generated illumination patterns

New Journal of Physics ◽

10.1088/1367-2630/9/10/363 ◽

2007 ◽

Vol 9 (10) ◽

pp. 363-363 ◽

Cited By ~ 16

Author(s):

Edward Carlo Samson ◽

Carlo Mar Blanca

Keyword(s):

Contrast Enhancement ◽

Dynamic Contrast Enhancement

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Dynamic Contrast Enhancement

Handbook of Research on Advanced Techniques in Diagnostic Imaging and Biomedical Applications ◽

10.4018/978-1-60566-314-2.ch025 ◽

2009 ◽

pp. 392-406

Author(s):

Valentina Russo ◽

Roberto Setola

Keyword(s):

Contrast Enhancement ◽

Empirical Model ◽

Inflammatory Diseases ◽

Research Topic ◽

Pharmacokinetic Analysis ◽

Dynamic Contrast Enhancement ◽

Non Invasive ◽

Analysis Technique ◽

Pathological Tissues

The aim of this chapter is to provide an overview about models and methodologies used for the Dynamic Contrast Enhancement (DCE) analysis. DCE is a non-invasive methodology aimed to diagnostic the nature of a lesion on the base of the perfusion’s dynamic of specific contrast agents. The idea at the base of DCE is that, in several pathological tissues, including tumors and inflammatory diseases, the angiogenic process is abnormal, hence the characterization of vascularisation structure may be used to support the diagnosis. In this chapter, we will describe the basic DCE procedures and introduce some of its most innovative evolution based on the pharmacokinetic analysis technique (PK), and the empirical model (EM). Even if DCE is still a medical research topic, there is large interest for this type of approach in biomedical applications as witnessed by the availability of specific tools in the last generation top-class US, CT and MR machines.

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Optimized Contrast Enhancement for Infrared Images Based on Global and Local Histogram Specification

Remote Sensing ◽

10.3390/rs11070849 ◽

2019 ◽

Vol 11 (7) ◽

pp. 849 ◽

Cited By ~ 3

Author(s):

Chengwei Liu ◽

Xiubao Sui ◽

Xiaodong Kuang ◽

Yuan Liu ◽

Guohua Gu ◽

...

Keyword(s):

Contrast Enhancement ◽

Visual Quality ◽

Local Contrast ◽

Original Image ◽

Infrared Images ◽

Histogram Specification ◽

Block Based ◽

Global And Local ◽

2D Histogram

In this paper, an optimized contrast enhancement method combining global and local enhancement results is proposed to improve the visual quality of infrared images. Global and local contrast enhancement methods have their merits and demerits, respectively. The proposed method utilizes the complementary characteristics of these two methods to achieve noticeable contrast enhancement without artifacts. In our proposed method, the 2D histogram, which contains both global and local gray level distribution characteristics of the original image, is computed first. Then, based on the 2D histogram, the global and local enhanced results are obtained by applying histogram specification globally and locally. Lastly, the enhanced result is computed by solving an optimization equation subjected to global and local constraints. The pixel-wise regularization parameters for the optimization equation are adaptively determined based on the edge information of the original image. Thus, the proposed method is able to enhance the local contrast while preserving the naturalness of the original image. Qualitative and quantitative evaluation results demonstrate that the proposed method outperforms the block-based methods for improving the visual quality of infrared images.

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