Tracing the Deformed Midline on Brain Ct

Liao, Chun-Chih; Chiang, I-Jen; Xiao, Furen; Wong, Jau Min

doi:10.4015/s1016237206000452

Cited by 21 publications

(15 citation statements)

References 19 publications

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“…In acute ischemic stroke, the MSP facilitates automatic and rapid identification of infarct hemisphere [12]. In CT scans, particularly, the MSP is also used to estimate the midline shift, which is a commonly used quantitative feature for evaluating severity of brain compression that can lead to death [13].…”

Section: Introductionmentioning

confidence: 99%

“…They are based on knowledge that the falx cerebri can be used as reference to estimate the MSP. The method [13] extracts the falx cerebri from superior axial slices, estimates the midsagittal line for each slice and constructs the MSP afterwards. Similarly, the method by Darius and Mecislovas [24] calculates midsagittal line from the falx attachment to the skull which is usually characterized by skull thickening in the attachment region.…”

Section: Introductionmentioning

confidence: 99%

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Robust calculation of the midsagittal plane in CT scans using the Kullback–Leibler’s measure

et al. 2009

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Robust calculation of the midsagittal plane in CT scans using the Kullback–Leibler’s measure

et al. 2009

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“…We have carried out several studies on automatic recognition of the MLS, the evidence of SFH on brain CT images [4][5][6]. Using visual inspection, we use a quadratic curve to model the deformed midline at the foramen of Monro, near the base of the cerebrum.…”

Section: Clinical Implications: Subfalcine and Transtentorial Herniatmentioning

confidence: 99%

“…The special discipline of biomechanics which is concerned with injury caused by mechanical interaction is denoted as trauma biomechanics [3]. We have proposed methods that can automatically measure the magnitude of MLS with symmetry-based and landmark-based methods [4][5][6]. To our knowledge, there has been no biomechanical model dedicated to simulating brain herniation in the literature.…”

Section: Introductionmentioning

confidence: 99%

Modeling and simulation of brain herniation caused by subdural hematoma using finite-element method

et al. 2018

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Abstract. Brain shift and herniation are important signs of increased intracranial pressure (ICP) caused by hematomas or other types of intracranial mass. We propose a novel finite-element model that can be deformed in response to increased ICP. The half sphere model of the brain is partially divided into two compartments by the intact mid-sagittal plane, allowing subfalcine herniation. A 40 mm circle in the center of its equatorial plane allows transtentorial herniation. We perform a single load step, structural static analysis, simulating a left-sided subdural hematoma (SDH) compressing the cerebral hemispheres from the outer surface of the left hemisphere. Subfalcine and transtentorial brain herniations are reproduced and visualized. The Poisson's ratio represents the tightness of the brain and the pressure load represents the ICP. There is a linear relationship between maximal deformation and the pressure load. The maximal deformation at the basal circumference and that at the basal midline closely resembles the maximal thickness of the SDH and the midline shift. We have developed a simple finiteelement model that can simulate brain shift and herniation caused by pressure loads exerted on its surface by a mass. The experimental results correlate well with clinical observation on patients with acute and chronic SDH.

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“…Some examples of the literature for the deformed midline are by using the biomechanical properties of different types of intracranial tissue. The author [48] had presented an automated method to detect and classify an abnormality into acute infarct, chronic infarct and hemorrhage at the slice level of non-contrast CT images. The proposed method consists of three main steps: image enhancement, detection of mid-line symmetry and classification of abnormal slices.…”

Section: Detection Of Midline In Brain Imagesmentioning

confidence: 99%

A Review of Epilepsy Diagnosis Using PET Parameters

Kumar

Mehta

Patil

2012

JBBS

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Epilepsy is caused by abnormal excessive electric discharges from the neurons in the brain. Epileptic seizures are nonspecific responses of the brain to many types of insults. The structural abnormalities causing epilepsy can be identified using various state of art imaging methods. Through a combination of brain activity monitoring, imaging and mapping techniques, physicians can locate the specific area in the brain causing epileptic discharges and identify its location in relation to those areas in the brain controlling vital functions. Positron Emission Tomography (PET) has emerged as a useful tool to identify abnormal metabolic activity of the epileptogenic foci. Parameters like asymmetric index, standard uptake value (SUV) etc. obtained by PET are processed and analyzed for identifying the origin of epileptic seizures. This paper discusses the techniques used to diagnose in general and to localize the epileptogenic regions using post-processing other features on PET imaging.

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Tracing the Deformed Midline on Brain Ct

Abstract: Midline shift (MLS) is the most important

Cited by 21 publications

References 19 publications

Robust calculation of the midsagittal plane in CT scans using the Kullback–Leibler’s measure

Robust calculation of the midsagittal plane in CT scans using the Kullback–Leibler’s measure

Modeling and simulation of brain herniation caused by subdural hematoma using finite-element method

A Review of Epilepsy Diagnosis Using PET Parameters

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