MRI Imaging, Comparison of MRI with other Modalities, Noise in MRI Images and Machine Learning Techniques for Noise Removal: A Review

Khan, Sajid Ullah; Ullah, Najeeb; Ahmed, Imran; Ahmad, Irshad; Mahsud, Muhammad Irfan

doi:10.2174/1573405614666180726124952

Cited by 21 publications

(12 citation statements)

References 23 publications

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“…Magnetic Resonance Imaging (MRI) is a medical imaging technique that records changing strong magnetic fields and radio waves to produce detailed images of the organ and soft tissues of the human body [38,47,48]. MRI is the most effective imaging modality that offers precise accuracy and sensitivity in detecting structural abnormalities of the body compared to the other technique, as shown in Figure 6 [49][50][51]. However, MRI is an expensive technology, and a waiting list is often long.…”

Section: Magnetic Resonance Imaging (Mri)mentioning

confidence: 99%

Existing and Emerging Breast Cancer Detection Technologies and Its Challenges: A Review

et al. 2021

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Breast cancer is the most leading cancer occurring in women and is a significant factor in female mortality. Early diagnosis of breast cancer with Artificial Intelligent (AI) developments for breast cancer detection can lead to a proper treatment to affected patients as early as possible that eventually help reduce the women mortality rate. Reliability issues limit the current clinical detection techniques, such as Ultra-Sound, Mammography, and Magnetic Resonance Imaging (MRI) from screening images for precise elucidation. The capability to detect a tumor in early diagnosis, expensive, relatively long waiting time due to pandemic and painful procedure for a patient to perform. This article aims to review breast cancer screening methods and recent technological advancements systematically. In addition, this paper intends to explore the progression and challenges of AI in breast cancer detection. The next state of the art between image and signal processing will be presented, and their performance is compared. This review will facilitate the researcher to insight the view of breast cancer detection technologies advancement and its challenges.

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Section: Magnetic Resonance Imaging (Mri)mentioning

confidence: 99%

Existing and Emerging Breast Cancer Detection Technologies and Its Challenges: A Review

et al. 2021

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“…16 In MRI images, different grey values indicate different energy released by human tissues. 17 Typically, CT has a higher resolution for bones, while MRI has a better resolution for soft tissues. Hence, to fully exploit the respective advantage of those image data, this study fuse CT and MRI data to reconstruct a complete 3D human brain model.…”

Section: Construction Of Virtual Surgical Scene For Lvp Operationmentioning

confidence: 99%

“…In CT images, different grey values represent different amounts of X‐ray absorption by human tissues 16 . In MRI images, different grey values indicate different energy released by human tissues 17 . Typically, CT has a higher resolution for bones, while MRI has a better resolution for soft tissues.…”

Section: Construction Of Virtual Surgical Scene For Lvp Operationmentioning

confidence: 99%

Haptic‐based virtual reality simulator for lateral ventricle puncture operation

Deng

et al. 2020

Robotics Computer Surgery

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Background: The implementation of lateral ventricle puncture (LVP) operation is challenging due to the complex anatomy structure of human brains. Surgical simulator has been proved to be effective in surgical training. However, few works consider the integration of visual and haptic feedback. Methods: Aim at achieving a realistic haptic interaction, this paper proposes a haptic-based virtual reality (VR) simulator for the LVP operation. In this simulator, we first reconstruct the three-dimension (3D) model of human brains for tissue/ instrument interaction. Then a preoperative planning method based on geometry analysis is introduced to find the feasible entry point of LVP operation. A hierarchical bounding-box collision detection approach is proposed to render haptic feedback that is transferred to humans. Finally, a set of experiments on the proposed simulator and 3D printed models of human brains is carried out. Results: Two sets of experiments are conducted to evaluate the effectiveness of the proposed haptic-based simulator: experiments in the simulator and experiments on a 3D printed brain model. The proposed simulator allows neurosurgeons to train the LVP operation by visualizing the 3D virtual human brain and feeling realistic haptic feedback. Conclusions: We demonstrated that the proposed haptic-based VR simulator can improve the performance of the LVP operation effectively and reduce the operation time.

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“…Since magnetic resonance imaging (MRI) was invented in the early 1970s, it has been widely used in medicine for diagnosis modality and massively developed by many researchers [1,2,3]. In MRI, the use of contrast agents is very useful to improve image quality on the object of observation.…”

Section: Introductionmentioning

confidence: 99%

Quantitative Analysis of Electrical Current Effect on Magnetic Resonance Image Tissue Intensity

Ain

Choridah²,

Kurniadi³

et al. 2023

Jurnal Teknologi

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Recent studies in magnetic resonance imaging (MRI) aim to improve image quality while reducing scan time. Electrical current injection in the form of magnetic resonance electrical impedance tomography (MREIT) is believed to be affecting image quality and scan time thus can improve the possibility of becoming a non-chemical contrast agent in MRI. This study will observe and analyze the effect of electrical current injection on a phantom object to determine whether there is a different tissue image intensity. A thigh of lamb was used as a biological tissue phantom. The scan was performed on both T1and T2-weighted without and with an electrical current injection of 0.5 mA Electrical current injection decreased mean of tissue image intensity on T1-weighted images on both muscle (1759 vs 794) and bone (2752 vs 1550) (p<0.05). On the other hand, the electrical current increased mean of tissue image intensity on T2-weighted images on both muscle (303 vs 897) and bone (579 vs 1499) (p<0.05). There is also a difference in tissue image intensity on both T1 and T2-weighted images with and without electrical current injection on bone and muscle. The implication of this difference in image quality is a subject for further study.

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MRI Imaging, Comparison of MRI with other Modalities, Noise in MRI Images and Machine Learning Techniques for Noise Removal: A Review

Cited by 21 publications

References 23 publications

Existing and Emerging Breast Cancer Detection Technologies and Its Challenges: A Review

Existing and Emerging Breast Cancer Detection Technologies and Its Challenges: A Review

Haptic‐based virtual reality simulator for lateral ventricle puncture operation

Quantitative Analysis of Electrical Current Effect on Magnetic Resonance Image Tissue Intensity

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