Computer-aided diagnosis of intracranial hematoma with brain deformation on computed tomography

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

doi:10.1016/j.compmedimag.2010.03.003

Cited by 37 publications

(34 citation statements)

References 19 publications

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“…9 Three board-certi¯ed neurosurgeons perform computer-assisted volumetric measurement of all skull defects with our proprietary software previously used to outline the hematomas. 10 Because only soft tissues remained at the sites of skull defects, the human experts delineated the contour of the missing part based on the shape of the corresponding contralateral skull region. The averaged volumes (V man ) form the gold standard for evaluating the performance of algorithms proposed in this paper.…”

Section: Methodsmentioning

confidence: 99%

“…10 We term the voxels in the downsized images as \blocks" to avoid confusion. First, the skull regions are segmented in downsized images generated with an 8 Â 8 maximum¯lter to¯ll up the foramina.…”

Section: Segmentation Of the Skull And The Intracranial Regions In Ctmentioning

confidence: 99%

“…10 These patients with large hematomas are highly likely to undergo DCs, resulting in large skull defects. Although our previous methodology is able to tolerate skull defects with diameters up to 0.8 cm, it cannot handle these large defects.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Automated Volumetry of Postoperative Skull Defect on Brain Ct

Huang

Liao

Xiao

et al. 2013

Biomed. Eng. Appl. Basis Commun.

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The volume of the skull defect should be one of the most important quantitative measures for decompressive craniectomy. However, there has been no study focusing on automated estimation of the volume from postoperative computed tomography (CT). This study develops and validates three methods that can automatically locate, recover and measure the missing skull region based on symmetry without preoperative images. The low resolution estimate (LRE) method involves downsizing CT images,¯nding the axis of symmetry for each slice, and estimating the location and size of the missing skull regions. The intact mid-sagittal plane (i MSP) can be de¯ned either by dimension-bydimension (DBD) method as a global symmetry plane or by Liu's method as a regression from each slices. The skull defect volume can then be calculated by skull volume di®erence (SVD) with respect to each i MSP. During a 48-month period between July 2006 and June 2010 at a regional hospital in northern Taiwan, we collected 30 sets of nonvolumetric CT images after craniectomies. Three board-certi¯ed neurosurgeons perform computer-assisted volumetric analysis of skull defect volume V Man as the gold standard for evaluating the performance of our algorithm. We compare the error of the three volumetry methods. The error of V LRE is smaller than that of V Liu (p < 0:0001) and V DBD (p ¼ 0:034). The error of V DBD is signi¯cant smaller than that of V Liu (p ¼ 0:001). The correlation coe±cients between V Man and V LRE , V Liu , V DBD are 0.98, 0.88 and 0.95, respectively. In conclusion, these methods can help to de¯ne the skull defect volume in postoperative images and provide information of the immediate volume gain after decompressive craniectomies. The i MSP of the postoperative skull can be reliably identi¯ed using the DBD method.

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Section: Methodsmentioning

confidence: 99%

Section: Segmentation Of the Skull And The Intracranial Regions In Ctmentioning

confidence: 99%

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Automated Volumetry of Postoperative Skull Defect on Brain Ct

Huang

Liao

Xiao

et al. 2013

Biomed. Eng. Appl. Basis Commun.

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“…After diagnosis, these hemorrhages can be treated either clinically or surgically. Various clinical practice guidelines (CPG) have been proposed for surgeons to decide, whether to surgically evacuate the hemorrhage clot or not, based on the volume, type, thickness of hemorrhage and grade of brain compression [2][3][4]. In other words, once the quantitative diagnosis of the brain hemorrhage has been completed, then clinicians can plan the treatment strategy.…”

Section: Introductionmentioning

confidence: 99%

Comparative analysis of various segmentation methods for brain hemorrhage detection using CT images

Bhadauria¹,

Patel²,

Bist³

et al. 2014

2014 9th International Conference on Industrial and Information Systems (ICIIS)

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Brain hemorrhage which happens as a result of bleeding due to rupturing of blood vessels within the brain matter is the main causes of human death. This discharge of blood may disturb the normal circulation of the brain. Computed Tomography (CT) has been the primary modality for the detection of brain hemorrhages because it is widely available, less expensive, quick to perform, and depicts rapidly. However intensity inhomogeneity, worst tissue contrast and weak boundaries in CT images may cause significant difficulties in hemorrhage detection. Thus in this paper the performance of various segmentation methods for hemorrhage detection from brain CT images have been evaluated.

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“…To verify this value, we measured the thickness of the SDH and the corresponding MLS on initial CT images in 12 surgically-treated acute SDH patients younger than 50 years of age, collected from our previous studies [5,20]. All patients showed signs of increased ICP.…”

Section: Clinical Implications: Subfalcine and Transtentorial Herniatmentioning

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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Computer-aided diagnosis of intracranial hematoma with brain deformation on computed tomography

Cited by 37 publications

References 19 publications

Automated Volumetry of Postoperative Skull Defect on Brain Ct

Automated Volumetry of Postoperative Skull Defect on Brain Ct

Comparative analysis of various segmentation methods for brain hemorrhage detection using CT images

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

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