A Review on Various Enhancement Techniques for Mammograms

Chahal, Jasleen K.; Panag, Navneet Kaur

doi:10.5120/21526-4506

Cited by 2 publications

(1 citation statement)

References 3 publications

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“…It is the most widely used agent for this purpose because of the advantages of 99mTcsestamibi tagging and its great efficiency in detecting carcinomas [56]. • Enhancement based upon wavelet transform and morphology, morphological operations (enhancement of image using multi-scale morphology) [59] • Direct contrast enhancement techniques [60] • Adaptive neighborhood contrast enhancement [61] • Removal of noise using wiener function [62] • An intuitionistic fuzzification scheme based on the optimization of intuitionistic fuzzy entropy and contrast limited adaptive histogram equalization (CLAHE) [63] • Mammogram enhancement, non-subsampled pyramid (NSP), low pass filter (LPF), high pass filter (HPF), directional filter bank (DFB), 2D-directional edge filter (HTDE), combining directional and scale features, adaptive histogram equalization (AHE), one-dimensional spatial profile of difference of Gaussian and HTDE filter, detection of microcalcification (MC) [64,65]…”

Section: Mammographymentioning

confidence: 99%

Digital Image Processing and Its Application for Medical Physics and Biomedical Engineering Area

Karmaker¹

2022

Digital Image Processing Applications

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The proper use of imaging modalities produces an image that aids in the detection of early stage abnormalities such as cancer, the identification of small precise lesions, and the presentation of internal illustration. A high-quality image can help doctors, radiologists, medical physicists, biomedical engineers, and scientists to make important decisions on ameliorate treatment planning that can reduce cancer mortality rates and provide life-saving results. This chapter outlines the features, attributes, and processing techniques of various medical imaging modalities utilized in the fields of radiation therapy and biomedical engineering. This study highlighted the significance of image processing in medical physics and biomedical engineering, characteristics of mammography, computed tomography (CT), ultrasound, magnetic resonance imaging (MRI), and positron emission tomography (PET) images. With their advanced application, various image processing approaches are distinguished. Images are collected through the journal, useful websites, the internet, or other sources. That can help teachers, students, researchers, scientists, and others comprehend and learn how to apply image processing techniques and which techniques will suit which modalities image. This chapter will provide a clear understanding of image processing techniques for medical physics and biomedical engineering participants, as well as an abundance of learning opportunities.

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Section: Mammographymentioning

confidence: 99%

Digital Image Processing and Its Application for Medical Physics and Biomedical Engineering Area

Karmaker¹

2022

Digital Image Processing Applications

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Trade-off between breast mean glandular dose and image quality in digital and conventional mammogram systems: A multicenter study

et al. 2021

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Evaluating the patient dose or exposure parameters considering the image quality can improve the chances of accurate diagnosis and reduce the unnecessary exposures from medical devices such as mammography. This study aimed to evaluate digital and conventional mammography machines while considering the trade-off between image quality and mean glandular dose (MGD) using a phantom. In the present study, one full-field digital mammography (FFDM) and two film-screen mammography (FSM) machines were investigated. The MGD values and image quality were assessed using the American College of Radiology (ACR) phantom at various mAs and constant kVp values. The results were obtained and compared with European guidelines. Friedman and Wilcoxon statistical tests were used to show the comparison. The results from the quality control (QC) tests demonstrated that all machines are functioning well. The best image quality in the digital mammography machine was observed at the MGD of 1.8 mGy and 55 mAs. In addition, the two conventional machines had the best image quality regarding the imaging of the ACR phantom at 65 mAs with an MGD of 2.1 mGy. These values were considered as appropriate values for the studied mammography systems. Furthermore, the Friedman test demonstrated that there are significant differences between the measured image quality values obtained from the different machines (p < 0.05), however, according to the Wilcoxon test there were not any significant differences between the conventional machines at various mAs values. Owing to the results, for a medium breast size, the image quality will not be improved with increasing the exposure after a specified MGD corresponds to a certain mAs. It is notable that this value is smaller in digital mammography system at a reasonably low dose.

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A Review on Various Enhancement Techniques for Mammograms

Cited by 2 publications

References 3 publications

Digital Image Processing and Its Application for Medical Physics and Biomedical Engineering Area

Digital Image Processing and Its Application for Medical Physics and Biomedical Engineering Area

Trade-off between breast mean glandular dose and image quality in digital and conventional mammogram systems: A multicenter study

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