A study on the dependence of exposure dose reduction and image evaluation on the distance from the dental periapical X-ray machine

2019

IEEE Access

This paper presents the development of a multi-frequency holographic microwave imaging (HMI) algorithm and investigates the feasibility and effectiveness of the proposed algorithm for breast imaging. A realistic numerical system, including various realistic breast models and image data acquisition model, has been developed using the MATLAB software to demonstrate the working principle of the multifrequency HMI method. Several numerical experiments have been conducted to evaluate the performance of the proposed method for breast tumor detection. A comparison study of single-and multi-frequency HMIs have been performed to investigate the effectiveness, sensitivity, and accuracy of the proposed method. Results demonstrated that the multi-frequency HMI could improve the breast image quality and accurately detect the small tumors even when they located inside dense tissue. Compared to the single-frequency HMI, the multi-frequency imaging approach could obtain detailed structural information about the breast and identify small lesions more accurately and effectively. The proposed method has the potential to become a great and helpful vision tool for investigating microwave diagnostic techniques. INDEX TERMSMicrowave imaging, holographic microwave imaging, breast cancer, multi-frequency, microwave antenna array.

Section: Introductionmentioning

confidence: 99%

Multi-Frequency Holographic Microwave Imaging for Breast Lesion Detection

2019

IEEE Access

“…Breast cancer is one of the most severe health issues in women worldwide [1]. Although X-ray mammography is the current standard breast imaging tool [2], it has some limitations, such as uses harmful radiations, unsuitable for pregnant women and dense breasts [3]. Microwave imaging (MI) is a relatively cost-effective and promising tool for the diagnosis of various diseases, including lung cancer [4], breast cancer [5]- [7], brain stroke [8], [9], heart disease [10], and bone cancer [11].…”

Section: Introductionmentioning

confidence: 99%

Enhanced Holographic Microwave Imaging for MNP Target Tumor Detection

2019

IEEE Access

Holographic microwave imaging (HMI) has been proposed as a potential imaging tool for breast cancer detection. However, this method is not sensitive enough to small tumors especially when they located inside the fibro-glandular tissue. This paper investigates the possibility of the use of enhanced HMI to improve the quality of breast image and diagnostic sensitivity by applying magnetic nanoparticles (MNP). A numerical system, including a realistic breast model, 16-element transducer array, a 2-element magnetic coil array, and an image processing model, has been developed to evaluate the effectiveness of the enhanced HMI method for mapping of a dense breast. The numerical results demonstrated that the proposed method could detect the MNP target breast tumor and distinguish the small tumor from fibro-glandular tissue in a dense breast, which has the potential to develop a useful imaging tool for early breast cancer detection in the future.INDEX TERMS Microwave imaging, diagnosis and therapy, magnetic nanoparticles, nanotechnology.

“…However, these techniques have some limitations. X-ray produces harmful radiation to the human body [ 2 ], and it is difficult for early abnormal tissue detection due to the relatively small contrast between the healthy tissue and the abnormal tissue at X-ray frequencies. PET is an excellent choice for imaging soft tissues, but it suffers from poor image resolution and relatively high-cost [ 3 ].…”

Section: Introductionmentioning

confidence: 99%

Three-Dimensional Holographic Electromagnetic Imaging for Accessing Brain Stroke

2018

Sensors

The authors recently developed a two-dimensional (2D) holographic electromagnetic induction imaging (HEI) for biomedical imaging applications. However, this method was unable to detect small inclusions accurately. For example, only one of two inclusions can be detected in the reconstructed image if the two inclusions were located at the same XY plane but in different Z-directions. This paper provides a theoretical framework of three-dimensional (3D) HEI to accurately and effectively detect inclusions embedded in a biological object. A numerical system, including a realistic head phantom, a 16-element excitation sensor array, a 16-element receiving sensor array, and image processing model has been developed to evaluate the effectiveness of the proposed method for detecting small stroke. The achieved 3D HEI images have been compared with 2D HEI images. Simulation results show that the 3D HEI method can accurately and effectively identify small inclusions even when two inclusions are located at the same XY plane but in different Z-directions. This preliminary study shows that the proposed method has the potential to develop a useful imaging tool for the diagnosis of neurological diseases and injuries in the future.