Review of Computational Methods on Brain Symmetric and Asymmetric Analysis from Neuroimaging Techniques

Kalavathi, P.; Senthamilselvi, M.; Prasath, V. B. Surya

doi:10.3390/technologies5020016

Cited by 19 publications

(12 citation statements)

References 55 publications

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“…where cθ ≡ cos θ, sθ ≡ sin θ, and so on. The pitch (ω) angle will be zero for MSP, and yaw (θ) and roll (ϕ) angles are calculated using Equations (19) and (28), respectively. The translation vector between the two coordinate systems, i.e., the center of the volume and centroid of the image grid, can be written as:…”

Section: Transformation For Tilt Correctionmentioning

confidence: 99%

“…These approaches can be divided into two distinct groups, varying in their exclusive interpretation of prescribed MSP: (1) shape-based algorithms that identify the location of cerebral IF using features of the head images to estimate MSP; and (2) content-based algorithms that considered MSP as the plane which maximizes the bilateral symmetry of the brain. A comprehensive survey of all the existing MSP extraction methods can be found in a recent review [19].Shape-based algorithms first segment the longitudinal fissure of the brain MRIs and employ it as a landmark for symmetry analysis and MSP extraction. For instance, Brummer [20] utilized Hough transform for straight line identification on each coronal slice and computed the MSP using interpolation.…”

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An Efficient Automatic Midsagittal Plane Extraction in Brain MRI

Rehman

Lee

2018

Applied Sciences

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In this paper, a fully automatic and computationally efficient midsagittal plane (MSP) extraction technique in brain magnetic resonance images (MRIs) has been proposed. Automatic detection of MSP in neuroimages can significantly aid in registration of medical images, asymmetric analysis, and alignment or tilt correction (recenter and reorientation) in brain MRIs. The parameters of MSP are estimated in two steps. In the first step, symmetric features and principal component analysis (PCA)-based technique is used to vertically align the bilateral symmetric axis of the brain. In the second step, PCA is used to achieve a set of parallel lines (principal axes) from the selected two-dimensional (2-D) elliptical slices of brain MRIs, followed by a plane fitting using orthogonal regression. The developed algorithm has been tested on 157 real T 1 -weighted brain MRI datasets including 14 cases from the patients with brain tumors. The presented algorithm is compared with a state-of-the-art approach based on bilateral symmetry maximization. Experimental results revealed that the proposed algorithm is fast (<1.04 s per MRI volume) and exhibits superior performance in terms of accuracy and precision (a mean z-distance of 0.336 voxels and a mean angle difference of 0.06).2 of 23 misalignment of brain MRIs. A general phenomenon in brain MRI scanning is that many neuroimaging scanners produce tilted and distorted brain images. The tilt of the head is not always detectable, due to many reasons such as the health conditions, immobility of patients, imprecision of the data calibration systems, and the inexperience of the technicians. Consequently, the slices of the brain MRIs are no more alike within the same orientation, at either the axial or coronal level [15]. Disoriented and misaligned brain MRIs can betray visual inspection and prevalently yield erroneous clinical perception [16]. In summary, assessment of brain MRIs for any anomaly based on cross-referencing of brain hemispheres (left and right), either by a human expert or computer-based software could be affected by false geometrical representation. Consequently, it is essential to correct the tilt and realign the brain MRIs data before further analysis.Manual misalignment correction is extremely time-consuming and laborious to perform on a huge scale. It also demands an urbane knowledge of brain anatomy. Therefore, it is neither sufficient nor efficient. Alignment or tilt correction of brain MRIs is tantamount to realigning the MSP with the center of the image matrix or image coordinate system [14]. If the MSP is computed precisely, the orientation problem of the MRI volume can be resolved. Thus, the tilt of the head volume can be assessed and adjusted. An ideal MSP can be defined as a virtual geometric plane passing through the interhemispheric fissure (IF) [17], about which the three-dimensional (3-D) anatomical structure of the brain (such as the ventricles, anterior/posterior commissures, corpus callosum, thalamus) exhibits maximum bilateral symmetry [18].Previously, ...

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Section: Transformation For Tilt Correctionmentioning

confidence: 99%

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confidence: 99%

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An Efficient Automatic Midsagittal Plane Extraction in Brain MRI

Rehman

Lee

2018

Applied Sciences

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“…Modern medical imaging techniques have given rise to the development of methodologies for the construction of data analysis systems for medical applications such as lesion segmentation and diseases diagnosis . Such systems uses information extracted from medical images data sets obtained by computed tomography (CT) or magnetic resonance imaging (MRI), providing surgeons with tools for better decision making.…”

Section: Introductionmentioning

confidence: 99%

Risk assessment methodology for trajectory planning in keyhole neurosurgery using genetic algorithms

Villanueva-Naquid

Soubervielle‐Montalvo

Aguilar-Ponce

et al. 2020

Robotics Computer Surgery

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Background: Preoperative assessment to find the safest trajectory in keyhole neurosurgery can reduce post operative complications. Methods: We introduced a novel preoperative risk assessment semiautomated methodology based on the sum of N maximum risk values using a generic genetic algorithm for the safest trajectory search. Results: A set of candidates trajectories were found for two surgical procedures. The trajectories search is done using a risk map considering the proximity of voxels within risk structures in multiple points and a genetic algorithm to avoid an exhaustive search. The trajectories were validated by a group of neurosurgeons. Conclusions: The trajectories obtained with the proposal method were shorter in 5% and have greater distance from the voxels within the blood vessels in 4.7%. The use of genetic algorithm (GA) speeds up the search for the safest trajectory, decreasing in 99.9% the time required for an exhaustive search.

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“…The final review paper authored by Kalavathi et al [4] researched the brain, which is the most complex organ in the human body, and it is divided into two hemispheres-left and right. The left hemisphere is responsible for control of the right side of our body, whereas the right hemisphere is responsible for control of the left side of our body.…”

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Special Issue on “Medical Imaging & Image Processing II”

Zhang

Dong

2018

Technologies

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Medical Imaging is becoming an essential component in various fields of bio-medical research and clinical practice: Neuroscientists detect regional metabolic brain activity from positron emission tomography (PET), functional magnetic resonance imaging (MRI), and magnetic resonance spectrum imaging (MRSI) scans; biologists study cells and generate 3D confocal microscopy data sets; virologists generate 3D reconstructions of viruses from micrographs; and radiologists identify and quantify tumors from MRI and computed tomography (CT) scans.On the other hand, Image Processing includes the analysis, enhancement, and display of biomedical images. Image reconstruction and modeling techniques allow instant processing of 2D signals to create 3D images. Image processing and analysis can be used to determine the diameter, volume, and vasculature of a tumor or organ, flow parameters of blood or other fluids, and microscopic changes that have yet to raise any otherwise discernible flags. Image classification techniques help to detect subjects suffered from particular diseases and to detect disease-related regions.This Special Issue of Technologies comprises 4 selected papers about medical imaging and image processing. The first paper by Rashid et al.[1] investigated telemedicine, which is defined as the use of Information and Communication Technology (ICT) for clinical health care from a distance. The exchange of radiographic images and electronic patient health information/records (ePHI/R) for diagnostic purposes had the risk of confidentiality, ownership identity, and authenticity. In their paper, a data-hiding technique for ePHI/R was proposed. The color information in the cover image was used for key generation, and stego-images were produced with an ideal case. As a result, the whole stego-system was perfectly secure. This method included the features of watermarking and steganography techniques. Their method was applied to radiographic images. For the radiographic images, their method resembled watermarking, which was an ePHI/R data system. Experiments showed promising results for the application of their method to radiographic images in ePHI/R for both transmission and storage purposes.The second paper by Boudjelal et al.[2] stated that positron emission tomography (PET) is an imaging technique that generates 3D detail of physiological processes at the cellular level. This technique requires a radioactive tracer, which decays and releases a positron that collides with an electron; consequently, annihilation photons are emitted, which can be measured. The purpose of PET is to use the measurement of photons to reconstruct the distribution of radioisotopes in the body. Currently, PET is undergoing a revamp, with advancements in data measurement instruments and the computing methods used to create the images. These computer methods are required to solve the inverse problem of "image reconstruction from projection". In this paper, the authors proposed a novel kernel-based regularization technique for maximum-likelihood expe...

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Review of Computational Methods on Brain Symmetric and Asymmetric Analysis from Neuroimaging Techniques

Cited by 19 publications

References 55 publications

An Efficient Automatic Midsagittal Plane Extraction in Brain MRI

An Efficient Automatic Midsagittal Plane Extraction in Brain MRI

Risk assessment methodology for trajectory planning in keyhole neurosurgery using genetic algorithms

Special Issue on “Medical Imaging & Image Processing II”

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