Wada-test, functional magnetic resonance imaging and direct electrical stimulation - brain mapping methods

International Nuclear Information System (INIS)

Minkin, K.; Tanova, R.; Busarski, A.; Penkov, M.; Penev, L.; Hadjidekov, V.

2009-01-01

Modern neurosurgery requires accurate preoperative and intraoperative localization of brain pathologies but also of brain functions. The presence of individual variations in healthy subjects and the shift of brain functions in brain diseases provoke the introduction of various methods for brain mapping. The aim of this paper was to analyze the most widespread methods for brain mapping: Wada-test, functional magnetic resonance imaging (fMRI) and intraoperative direct electrical stimulation (DES). This study included 4 patients with preoperative brain mapping using Wada-test and fMRI. Intraoperative mapping with DES during awake craniotomy was performed in one case. The histopathological diagnosis was low-grade glioma in 2 cases, cortical dysplasia (1 patient) and arteriovenous malformation (1 patient). The brain mapping permits total lesion resection in three of four patients. There was no new postoperative deficit despite surgery near or within functional brain areas. Brain plasticity provoking shift of eloquent areas from their usual locations was observed in two cases. The brain mapping methods allow surgery in eloquent brain areas recognized in the past as 'forbidden areas'. Each method has advantages and disadvantages. The precise location of brain functions and pathologies frequently requires combination of different brain mapping methods. (authors)

Method of image segmentation using a neural network. Application to MR imaging of brain tumors

International Nuclear Information System (INIS)

Engler, E.; Gautherie, M.

1992-01-01

An original method of numerical images segmentation has been developed. This method is based on pixel clustering using a formal neural network configurated by supervised learning of pre-classified examples. The method has been applied to series of MR images of brain tumors (gliomas) with a view to proceed with a 3D-extraction of the tumor volume. This study is part of a project on cancer thermotherapy including the development of a scan-focused ultrasound system of tumor heating and a 3D-numerical thermal model

Brain medical image diagnosis based on corners with importance-values.

Science.gov (United States)

Gao, Linlin; Pan, Haiwei; Li, Qing; Xie, Xiaoqin; Zhang, Zhiqiang; Han, Jinming; Zhai, Xiao

2017-11-21

Brain disorders are one of the top causes of human death. Generally, neurologists analyze brain medical images for diagnosis. In the image analysis field, corners are one of the most important features, which makes corner detection and matching studies essential. However, existing corner detection studies do not consider the domain information of brain. This leads to many useless corners and the loss of significant information. Regarding corner matching, the uncertainty and structure of brain are not employed in existing methods. Moreover, most corner matching studies are used for 3D image registration. They are inapplicable for 2D brain image diagnosis because of the different mechanisms. To address these problems, we propose a novel corner-based brain medical image classification method. Specifically, we automatically extract multilayer texture images (MTIs) which embody diagnostic information from neurologists. Moreover, we present a corner matching method utilizing the uncertainty and structure of brain medical images and a bipartite graph model. Finally, we propose a similarity calculation method for diagnosis. Brain CT and MRI image sets are utilized to evaluate the proposed method. First, classifiers are trained in N-fold cross-validation analysis to produce the best θ and K. Then independent brain image sets are tested to evaluate the classifiers. Moreover, the classifiers are also compared with advanced brain image classification studies. For the brain CT image set, the proposed classifier outperforms the comparison methods by at least 8% on accuracy and 2.4% on F1-score. Regarding the brain MRI image set, the proposed classifier is superior to the comparison methods by more than 7.3% on accuracy and 4.9% on F1-score. Results also demonstrate that the proposed method is robust to different intensity ranges of brain medical image. In this study, we develop a robust corner-based brain medical image classifier. Specifically, we propose a corner detection

Research for correction pre-operative MRI images of brain during operation using particle method simulation

International Nuclear Information System (INIS)

Shino, Ryosaku; Koshizuka, Seiichi; Sakai, Mikio; Ito, Hirotaka; Iseki, Hiroshi; Muragaki, Yoshihiro

2010-01-01

In the neurosurgical procedures, surgeon formulates a surgery plan based on pre-operative images such as MRI. However, the brain is transformed by removal of the affected area. In this paper, we propose a method for reconstructing pre-operative images involving the deformation with physical simulation. First, the domain of brain is identified in pre-operative images. Second, we create particles for physical simulation. Then, we carry out the linear elastic simulation taking into account the gravity. Finally, we reconstruct pre-operative images with deformation according to movement of the particles. We show the effectiveness of this method by reconstructing the pre-operative image actually taken before surgery. (author)

Electromagnetic brain imaging

International Nuclear Information System (INIS)

Sekihara, Kensuke

2008-01-01

Present imaging methods of cerebral neuro-activity like brain functional MRI and positron emission tomography (PET) secondarily measure only average activities within a time of the second-order (low time-resolution). In contrast, the electromagnetic brain imaging (EMBI) directly measures the faint magnetic field (10 -12 -10 -13 T) yielded by the cerebral activity with use of multiple arrayed sensors equipped on the head surface within a time of sub-millisecond order (high time-resolution). The sensor array technology to find the signal source from the measured data is common in wide areas like signal procession for radar, sonar, and epicenter detection by seismic wave. For estimating and reconstructing the active region in the brain in EMBI, the efficient method must be developed and this paper describes the direct and inverse problems concerned in signal and image processions of EMBI. The direct problem involves the cerebral magnetic field/lead field matrix and inverse problem for reconstruction of signal source, the MUSIC (multiple signal classification) algorithm, GLRT (generalized likelihood ratio test) scan, and adaptive beamformer. As an example, given are results of magnetic intensity changes (unit, fT) in the somatosensory cortex vs time (msec) measured by 160 sensors and of images reconstructed from EMBI and MRI during electric muscle afferent input from the hand. The real-time imaging is thus possible with EMBI and extremely, the EMBI image, the real-time cerebral signals, can inversely operate a machine, of which application directs toward the brain/machine interface development. (R.T.)

High-precision surface formation method and the 3-D shaded display of the brain obtained from CT images

International Nuclear Information System (INIS)

Niki, Noboru; Fukuda, Hiroshi

1987-01-01

Our aim is to display the precise 3-D appearance of the brain based on data provided by CT images. For this purpose, we have developed a method of precisely forming surfaces from brain contours. The method expresses the brain surface as the sum of several partial surfaces. Each partial surface is individually constructed from respective parts of brain contours. The brain surface is finally made up of a superposition of partial surfaces. Two surface formation algorithms based on this principle are presented. One expresses the brain surface as the sum of a brain outline surface and sulcus surfaces. The other expresses the brain surface as the sum of surfaces in the same part of the brain. The effectiveness of these algorithms is shown by evaluation of contours obtained from dog and human brain samples and CT images. The latter algorithm is shown to be superior for high-resolution CT images. Optional cut-away views of the brain constructed by these algorithms are also shown. (author)

A Method for Automatic Extracting Intracranial Region in MR Brain Image

Science.gov (United States)

Kurokawa, Keiji; Miura, Shin; Nishida, Makoto; Kageyama, Yoichi; Namura, Ikuro

It is well known that temporal lobe in MR brain image is in use for estimating the grade of Alzheimer-type dementia. It is difficult to use only region of temporal lobe for estimating the grade of Alzheimer-type dementia. From the standpoint for supporting the medical specialists, this paper proposes a data processing approach on the automatic extraction of the intracranial region from the MR brain image. The method is able to eliminate the cranium region with the laplacian histogram method and the brainstem with the feature points which are related to the observations given by a medical specialist. In order to examine the usefulness of the proposed approach, the percentage of the temporal lobe in the intracranial region was calculated. As a result, the percentage of temporal lobe in the intracranial region on the process of the grade was in agreement with the visual sense standards of temporal lobe atrophy given by the medical specialist. It became clear that intracranial region extracted by the proposed method was good for estimating the grade of Alzheimer-type dementia.

A tri-modality image fusion method for target delineation of brain tumors in radiotherapy.

Directory of Open Access Journals (Sweden)

Lu Guo

Full Text Available To develop a tri-modality image fusion method for better target delineation in image-guided radiotherapy for patients with brain tumors.A new method of tri-modality image fusion was developed, which can fuse and display all image sets in one panel and one operation. And a feasibility study in gross tumor volume (GTV delineation using data from three patients with brain tumors was conducted, which included images of simulation CT, MRI, and 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET examinations before radiotherapy. Tri-modality image fusion was implemented after image registrations of CT+PET and CT+MRI, and the transparency weight of each modality could be adjusted and set by users. Three radiation oncologists delineated GTVs for all patients using dual-modality (MRI/CT and tri-modality (MRI/CT/PET image fusion respectively. Inter-observer variation was assessed by the coefficient of variation (COV, the average distance between surface and centroid (ADSC, and the local standard deviation (SDlocal. Analysis of COV was also performed to evaluate intra-observer volume variation.The inter-observer variation analysis showed that, the mean COV was 0.14(± 0.09 and 0.07(± 0.01 for dual-modality and tri-modality respectively; the standard deviation of ADSC was significantly reduced (p<0.05 with tri-modality; SDlocal averaged over median GTV surface was reduced in patient 2 (from 0.57 cm to 0.39 cm and patient 3 (from 0.42 cm to 0.36 cm with the new method. The intra-observer volume variation was also significantly reduced (p = 0.00 with the tri-modality method as compared with using the dual-modality method.With the new tri-modality image fusion method smaller inter- and intra-observer variation in GTV definition for the brain tumors can be achieved, which improves the consistency and accuracy for target delineation in individualized radiotherapy.

The registration accuracy analysis of different CT-MRI imaging fusion method in brain tumor

International Nuclear Information System (INIS)

Lu Jie; Yin Yong; Shao Qian; Zhang Zicheng; Chen Jinhu; Chen Zhaoqiu

2010-01-01

Objective: To find an effective CT-MRI image fusion protocol in brain tumor by analyzing the registration accuracy of different methods. Methods: The simulation CT scan and MRI T 1 WI imaging of 10 brain tumor patients obtained with same position were registered by Tris-Axes landmark ,Tris-Axes landmark + manual adjustment, mutual information and mutual information + manual adjustment method. The clinical tumor volume (CTV) were contoured on both CT and MRI images respectively. The accuracy of image fusion was assessed by the mean distance of five bone markers (d 1-5 ), central position of CTV (d CTV ) the percentage of CTV overlap (P CT-MRI ) between CT and MRI images. The difference between different methods was analyzed by Freedman M non-parameter test. Results: The difference of the means d1-5 between the Tris-Axes landmark,Tris-Axes landmark plus manual adjustment,mutual information and mutual information plus manual adjustment methods were 0.28 cm ±0.12 cm, 0.15 cm ±0.02 cm, 0.25 cm± 0.19 cm, 0.10 cm ± 0.06 cm, (M = 14.41, P = 0.002). the means d CTV were 0.59 cm ± 0.28 cm, 0.60 cm± 0.32 cm, 0.58 cm ± 0.39 cm, 0.42 cm± 0.30 cm (M = 9.72, P = 0.021), the means P CT-MRI were 0.69% ±0.18%, 0.68% ±0.16%, 0.66% ±0.17%, 0.74% ±0.14% (M =14.82, P=0.002), respectively. Conclusions: Mutual information plus manual adjustment registration method was the preferable fusion method for brain tumor patients. (authors)

Hemorrhage detection in MRI brain images using images features

Science.gov (United States)

Moraru, Luminita; Moldovanu, Simona; Bibicu, Dorin; Stratulat (Visan), Mirela

2013-11-01

The abnormalities appear frequently on Magnetic Resonance Images (MRI) of brain in elderly patients presenting either stroke or cognitive impairment. Detection of brain hemorrhage lesions in MRI is an important but very time-consuming task. This research aims to develop a method to extract brain tissue features from T2-weighted MR images of the brain using a selection of the most valuable texture features in order to discriminate between normal and affected areas of the brain. Due to textural similarity between normal and affected areas in brain MR images these operation are very challenging. A trauma may cause microstructural changes, which are not necessarily perceptible by visual inspection, but they could be detected by using a texture analysis. The proposed analysis is developed in five steps: i) in the pre-processing step: the de-noising operation is performed using the Daubechies wavelets; ii) the original images were transformed in image features using the first order descriptors; iii) the regions of interest (ROIs) were cropped from images feature following up the axial symmetry properties with respect to the mid - sagittal plan; iv) the variation in the measurement of features was quantified using the two descriptors of the co-occurrence matrix, namely energy and homogeneity; v) finally, the meaningful of the image features is analyzed by using the t-test method. P-value has been applied to the pair of features in order to measure they efficacy.

Imaging Human Brain Perfusion with Inhaled Hyperpolarized 129Xe MR Imaging.

Science.gov (United States)

Rao, Madhwesha R; Stewart, Neil J; Griffiths, Paul D; Norquay, Graham; Wild, Jim M

2018-02-01

Purpose To evaluate the feasibility of directly imaging perfusion of human brain tissue by using magnetic resonance (MR) imaging with inhaled hyperpolarized xenon 129 ( 129 Xe). Materials and Methods In vivo imaging with 129 Xe was performed in three healthy participants. The combination of a high-yield spin-exchange optical pumping 129 Xe polarizer, custom-built radiofrequency coils, and an optimized gradient-echo MR imaging protocol was used to achieve signal sensitivity sufficient to directly image hyperpolarized 129 Xe dissolved in the human brain. Conventional T1-weighted proton (hydrogen 1 [ 1 H]) images and perfusion images by using arterial spin labeling were obtained for comparison. Results Images of 129 Xe uptake were obtained with a signal-to-noise ratio of 31 ± 9 and demonstrated structural similarities to the gray matter distribution on conventional T1-weighted 1 H images and to perfusion images from arterial spin labeling. Conclusion Hyperpolarized 129 Xe MR imaging is an injection-free means of imaging the perfusion of cerebral tissue. The proposed method images the uptake of inhaled xenon gas to the extravascular brain tissue compartment across the intact blood-brain barrier. This level of sensitivity is not readily available with contemporary MR imaging methods. © RSNA, 2017.

PET/MRI for Oncologic Brain Imaging

DEFF Research Database (Denmark)

Rausch, Ivo; Rischka, Lucas; Ladefoged, Claes N

2017-01-01

The aim of this study was to compare attenuation-correction (AC) approaches for PET/MRI in clinical neurooncology.Methods:Forty-nine PET/MRI brain scans were included: brain tumor studies using18F-fluoro-ethyl-tyrosine (18F-FET) (n= 31) and68Ga-DOTANOC (n= 7) and studies of healthy subjects using18...... by Siemens Healthcare). As a reference, AC maps were derived from patient-specific CT images (CTref). PET data were reconstructed using standard settings after AC with all 4 AC methods. We report changes in diagnosis for all brain tumor patients and the following relative differences values (RDs...... of the whole brain and 10 anatomic regions segmented on MR images.Results:For brain tumor imaging (A and B), the standard PET-based diagnosis was not affected by any of the 3 MR-AC methods. For A, the average RDs of SUVmeanwere -10%, -4%, and -3% and of the VOIs 1%, 2%, and 7% for DIXON, UTE, and BD...

Apparatus and method for motion tracking in brain imaging

DEFF Research Database (Denmark)

2013-01-01

Disclosed is apparatus and method for motion tracking of a subject in medical brain imaging. The method comprises providing a light projector and a first camera; projecting a first pattern sequence (S1) onto a surface region of the subject with the light projector, wherein the subject is positioned......2,1) based on the detected first pattern sequence (S1'); projecting the second pattern sequence (S2) onto a surface region of the subject with the light projector; detecting the projected second pattern sequence (S2') with the first camera; and determining motion tracking parameters based...

Groupwise registration of MR brain images with tumors

Science.gov (United States)

Tang, Zhenyu; Wu, Yihong; Fan, Yong

2017-09-01

A novel groupwise image registration framework is developed for registering MR brain images with tumors. Our method iteratively estimates a normal-appearance counterpart for each tumor image to be registered and constructs a directed graph (digraph) of normal-appearance images to guide the groupwise image registration. Particularly, our method maps each tumor image to its normal appearance counterpart by identifying and inpainting brain tumor regions with intensity information estimated using a low-rank plus sparse matrix decomposition based image representation technique. The estimated normal-appearance images are groupwisely registered to a group center image guided by a digraph of images so that the total length of ‘image registration paths’ to be the minimum, and then the original tumor images are warped to the group center image using the resulting deformation fields. We have evaluated our method based on both simulated and real MR brain tumor images. The registration results were evaluated with overlap measures of corresponding brain regions and average entropy of image intensity information, and Wilcoxon signed rank tests were adopted to compare different methods with respect to their regional overlap measures. Compared with a groupwise image registration method that is applied to normal-appearance images estimated using the traditional low-rank plus sparse matrix decomposition based image inpainting, our method achieved higher image registration accuracy with statistical significance (p  =  7.02  ×  10-9).

Prediction of standard-dose brain PET image by using MRI and low-dose brain [{sup 18}F]FDG PET images

Energy Technology Data Exchange (ETDEWEB)

Kang, Jiayin [School of Electronics Engineering, Huaihai Institute of Technology, Lianyungang, Jiangsu 222005, China and IDEA Laboratory, Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599 (United States); Gao, Yaozong [IDEA Laboratory, Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599 and Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599 (United States); Shi, Feng [IDEA Laboratory, Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599 (United States); Lalush, David S. [Joint UNC-NCSU Department of Biomedical Engineering, North Carolina State University, Raleigh, North Carolina 27695 (United States); Lin, Weili [MRI Laboratory, Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599 (United States); Shen, Dinggang, E-mail: dgshen@med.unc.edu [IDEA Laboratory, Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599 and Department of Brain and Cognitive Engineering, Korea University, Seoul 136-713 (Korea, Republic of)

2015-09-15

Purpose: Positron emission tomography (PET) is a nuclear medical imaging technology that produces 3D images reflecting tissue metabolic activity in human body. PET has been widely used in various clinical applications, such as in diagnosis of brain disorders. High-quality PET images play an essential role in diagnosing brain diseases/disorders. In practice, in order to obtain high-quality PET images, a standard-dose radionuclide (tracer) needs to be used and injected into a living body. As a result, it will inevitably increase the patient’s exposure to radiation. One solution to solve this problem is predicting standard-dose PET images using low-dose PET images. As yet, no previous studies with this approach have been reported. Accordingly, in this paper, the authors propose a regression forest based framework for predicting a standard-dose brain [{sup 18}F]FDG PET image by using a low-dose brain [{sup 18}F]FDG PET image and its corresponding magnetic resonance imaging (MRI) image. Methods: The authors employ a regression forest for predicting the standard-dose brain [{sup 18}F]FDG PET image by low-dose brain [{sup 18}F]FDG PET and MRI images. Specifically, the proposed method consists of two main steps. First, based on the segmented brain tissues (i.e., cerebrospinal fluid, gray matter, and white matter) in the MRI image, the authors extract features for each patch in the brain image from both low-dose PET and MRI images to build tissue-specific models that can be used to initially predict standard-dose brain [{sup 18}F]FDG PET images. Second, an iterative refinement strategy, via estimating the predicted image difference, is used to further improve the prediction accuracy. Results: The authors evaluated their algorithm on a brain dataset, consisting of 11 subjects with MRI, low-dose PET, and standard-dose PET images, using leave-one-out cross-validations. The proposed algorithm gives promising results with well-estimated standard-dose brain [{sup 18}F]FDG PET

Prediction of standard-dose brain PET image by using MRI and low-dose brain ["1"8F]FDG PET images

International Nuclear Information System (INIS)

Kang, Jiayin; Gao, Yaozong; Shi, Feng; Lalush, David S.; Lin, Weili; Shen, Dinggang

2015-01-01

Purpose: Positron emission tomography (PET) is a nuclear medical imaging technology that produces 3D images reflecting tissue metabolic activity in human body. PET has been widely used in various clinical applications, such as in diagnosis of brain disorders. High-quality PET images play an essential role in diagnosing brain diseases/disorders. In practice, in order to obtain high-quality PET images, a standard-dose radionuclide (tracer) needs to be used and injected into a living body. As a result, it will inevitably increase the patient’s exposure to radiation. One solution to solve this problem is predicting standard-dose PET images using low-dose PET images. As yet, no previous studies with this approach have been reported. Accordingly, in this paper, the authors propose a regression forest based framework for predicting a standard-dose brain ["1"8F]FDG PET image by using a low-dose brain ["1"8F]FDG PET image and its corresponding magnetic resonance imaging (MRI) image. Methods: The authors employ a regression forest for predicting the standard-dose brain ["1"8F]FDG PET image by low-dose brain ["1"8F]FDG PET and MRI images. Specifically, the proposed method consists of two main steps. First, based on the segmented brain tissues (i.e., cerebrospinal fluid, gray matter, and white matter) in the MRI image, the authors extract features for each patch in the brain image from both low-dose PET and MRI images to build tissue-specific models that can be used to initially predict standard-dose brain ["1"8F]FDG PET images. Second, an iterative refinement strategy, via estimating the predicted image difference, is used to further improve the prediction accuracy. Results: The authors evaluated their algorithm on a brain dataset, consisting of 11 subjects with MRI, low-dose PET, and standard-dose PET images, using leave-one-out cross-validations. The proposed algorithm gives promising results with well-estimated standard-dose brain ["1"8F]FDG PET image and substantially

Structural Image Analysis of the Brain in Neuropsychology Using Magnetic Resonance Imaging (MRI) Techniques.

Science.gov (United States)

Bigler, Erin D

2015-09-01

Magnetic resonance imaging (MRI) of the brain provides exceptional image quality for visualization and neuroanatomical classification of brain structure. A variety of image analysis techniques provide both qualitative as well as quantitative methods to relate brain structure with neuropsychological outcome and are reviewed herein. Of particular importance are more automated methods that permit analysis of a broad spectrum of anatomical measures including volume, thickness and shape. The challenge for neuropsychology is which metric to use, for which disorder and the timing of when image analysis methods are applied to assess brain structure and pathology. A basic overview is provided as to the anatomical and pathoanatomical relations of different MRI sequences in assessing normal and abnormal findings. Some interpretive guidelines are offered including factors related to similarity and symmetry of typical brain development along with size-normalcy features of brain anatomy related to function. The review concludes with a detailed example of various quantitative techniques applied to analyzing brain structure for neuropsychological outcome studies in traumatic brain injury.

Semiautomated volumetry of the cerebrum, cerebellum-brain stem, and temporal lobe on brain magnetic resonance images

International Nuclear Information System (INIS)

Hayashi, Norio; Matsuura, Yukihiro; Kawahara, Kazuhiro; Tsujii, Hideo; Yamamoto, Tomoyuki; Sanada, Shigeru; Suzuki, Masayuki; Matsui, Osamu

2008-01-01

The aim of this study was to develop an automated method of segmenting the cerebrum, cerebellum-brain stem, and temporal lobe simultaneously on magnetic resonance (MR) images. We obtained T1-weighted MR images from 10 normal subjects and 19 patients with brain atrophy. To perform automated volumetry from MR images, we performed the following three steps: segmentation of the brain region; separation between the cerebrum and the cerebellum-brain stem; and segmentation of the temporal lobe. Evaluation was based on the correctly recognized region (CRR) (i.e., the region recognized by both the automated and manual methods). The mean CRRs of the normal and atrophic brains were 98.2% and 97.9% for the cerebrum, 87.9% and 88.5% for the cerebellum-brain stem, and 76.9% and 85.8% for the temporal lobe, respectively. We introduce an automated volumetric method for the cerebrum, cerebellum-brain stem, and temporal lobe on brain MR images. Our method can be applied to not only the normal brain but also the atrophic brain. (author)

Brain imaging and brain function

International Nuclear Information System (INIS)

Sokoloff, L.

1985-01-01

This book is a survey of the applications of imaging studies of regional cerebral blood flow and metabolism to the investigation of neurological and psychiatric disorders. Contributors review imaging techniques and strategies for measuring regional cerebral blood flow and metabolism, for mapping functional neural systems, and for imaging normal brain functions. They then examine the applications of brain imaging techniques to the study of such neurological and psychiatric disorders as: cerebral ischemia; convulsive disorders; cerebral tumors; Huntington's disease; Alzheimer's disease; depression and other mood disorders. A state-of-the-art report on magnetic resonance imaging of the brain and central nervous system rounds out the book's coverage

Brain volume measurement using three-dimensional magnetic resonance images

International Nuclear Information System (INIS)

Ishimaru, Yoshihiro

1996-01-01

This study was designed to validate accurate measurement method of human brain volume using three dimensional (3D) MRI data on a workstation, and to establish optimal correcting method of human brain volume on diagnosis of brain atrophy. 3D MRI data were acquired by fast SPGR sequence using 1.5 T MR imager. 3D MRI data were segmented by region growing method and 3D image was displayed by surface rendering method on the workstation. Brain volume was measured by the volume measurement function of the workstation. In order to validate the accurate measurement method, phantoms and a specimen of human brain were examined. Phantom volume was measured by changing the lower level of threshold value. At the appropriate threshold value, percentage of error of phantoms and the specimen were within 0.6% and 0.08%, respectively. To establish the optimal correcting method, 130 normal volunteers were examined. Brain volumes corrected with height weight, body surface area, and alternative skull volume were evaluated. Brain volume index, which is defined as dividing brain volume by alternative skull volume, had the best correlation with age (r=0.624, p<0.05). No gender differences was observed in brain volume index in contrast to in brain volume. The clinical usefulness of this correcting method for brain atrophy diagnosis was evaluated in 85 patients. Diagnosis by 2D spin echo MR images was compared with brain volume index. Diagnosis of brain atrophy by 2D MR image was concordant with the evaluation by brain volume index. These results indicated that this measurement method had high accuracy, and it was important to set the appropriate threshold value. Brain volume index was the appropriate indication for evaluation of human brain volume, and was considered to be useful for the diagnosis of brain atrophy. (author)

Clinical evaluation of FMPSPGR sequence of the brain MR imaging

International Nuclear Information System (INIS)

Takahashi, Mitsuyuki; Hasegawa, Makoto; Mori, Naohiko; Yamanoguchi, Minoru; Matsubara, Tadashi

1998-01-01

In order to apply the FMPSPGR (fast multi planar spoiled GRASS) method to diagnose brain diseases, authors obtained the optimal condition for imaging by the phantom experiments and examined the clinical usefulness. Six kinds of the phantom, which were 4 of diluted Gd solution with different concentrations, olive oil and physiological saline solution were used. From the phantom experiments, TR/TE/FR=300/3.3/90 degrees was the optimal condition. The evaluation of the clinical images was performed on the same section by the ST method and the FMPSPGR method. Fifteen patients (9 men and 6 women, aged from 17 to 80 years) suspected of brain diseases were examined, including 8 of cerebral infarction, 1 of pontine infarction, 1 of brain contusion, 1 of intracerebral bleeding and 4 of brain tumors. Four cases of brain tumor were evaluated on the contrast imaging and the others were on the plain imaging. In the plain imaging, the FMPSPGR method was better than the SE method on the low signal region in the T1 weighted imaging. Furthermore, in the contrast imaging, it could give more clear images of the lesion in anterior cranial pit by suppressing artifacts of blood flow. The present results indicate that the FMPSPGR method is useful to diagnose brain diseases. (K.H.)

Brain's tumor image processing using shearlet transform

Science.gov (United States)

Cadena, Luis; Espinosa, Nikolai; Cadena, Franklin; Korneeva, Anna; Kruglyakov, Alexey; Legalov, Alexander; Romanenko, Alexey; Zotin, Alexander

2017-09-01

Brain tumor detection is well known research area for medical and computer scientists. In last decades there has been much research done on tumor detection, segmentation, and classification. Medical imaging plays a central role in the diagnosis of brain tumors and nowadays uses methods non-invasive, high-resolution techniques, especially magnetic resonance imaging and computed tomography scans. Edge detection is a fundamental tool in image processing, particularly in the areas of feature detection and feature extraction, which aim at identifying points in a digital image at which the image has discontinuities. Shearlets is the most successful frameworks for the efficient representation of multidimensional data, capturing edges and other anisotropic features which frequently dominate multidimensional phenomena. The paper proposes an improved brain tumor detection method by automatically detecting tumor location in MR images, its features are extracted by new shearlet transform.

MR imaging of the brain: tumors

International Nuclear Information System (INIS)

Sartor, K.

1999-01-01

The radiologic modality that most likely provides the imaging information needed in a patient suspected of having a brain tumor is MR imaging. A brain tumor can be reliably ruled out if the MR examination is performed properly and experts interpret the results as negative. If there is a tumor, however, its exact location and topography must be determined. Important for therapy and prognosis are also tumor properties such as histologic type and grade, as well as effects on adjacent brain structures. Although potentially a noninvasive method of in vivo neuropathology, MR is still far from being sufficiently specific, as dissimilar lesions may look the same despite the use of refined imaging protocols. The evolution of MR imaging continues, however, making further methodologic improvement likely. Presently, advanced methods, such as diffusion- and perfusion-weighted MR imaging, functional MR imaging, neuronavigation based on MR imaging data, and the use of MR imaging during surgery (intraoperative MR imaging), influence the way patients are treated. Likewise, follow-up imaging (monitoring) of tumor patients by MR has become more effective, and experience has shown how to distinguish reactive changes from recurrent tumor. In the future, MR imaging may gain importance in the development of novel therapeutic concepts. (orig.)

MR image-guided portal verification for brain treatment field

International Nuclear Information System (INIS)

Yin, F.-F.; Gao, Q.H.; Xie, H.; Nelson, D.F.; Yu, Y.; Kwok, W.E.; Totterman, S.; Schell, M.C.; Rubin, P.

1996-01-01

Purpose/Objective: Although MR images have been extensively used for the treatment planning of radiation therapy of cancers, especially for brain cancers, they are not effectively used for the portal verification due to lack of bone/air information in MR images and geometric distortions. Typically, MR images are utilized through correlation with CT images, and this procedure is usually very labor and time consuming. For many brain cancer patients to be treated using conventional external beam radiation, MR images with proper distortion correction provide sufficient information for treatment planning and dose calculation, and a projection images may be generated for each specific treatment port and to be used as a reference image for treatment verification. The question is how to transfer anatomical features in MR images to the projection image as landmarks which could be correlated automatically to those in the portal image. The goal of this study is to generate digitally reconstructed projection images from MR brain images with some important anatomical features (brain contour, skull and gross tumor) as well as their relative locations to be used as references for the development of computerized portal verification scheme. Materials/Methods: Compared to conventional digital reconstructed radiograph from CT images, generation of digitally reconstructed projection images from MR images is heavily involved with pixel manipulation of MR images to correlate information from two types of images (MR, portal x-ray images) which are produced based on totally different imaging principles. Initially a wavelet based multi-resolution adaptive thresholding method is used to segment the skull slice-by-slice in MR brain axial images, and identified skull pixels are re-assigned to relatively higher intensities so that projection images will have comparable grey-level information as that in typical brain portal images. Both T1- and T2-weighted images are utilized to eliminate fat

Fuzzy object models for newborn brain MR image segmentation

Science.gov (United States)

Kobashi, Syoji; Udupa, Jayaram K.

2013-03-01

Newborn brain MR image segmentation is a challenging problem because of variety of size, shape and MR signal although it is the fundamental study for quantitative radiology in brain MR images. Because of the large difference between the adult brain and the newborn brain, it is difficult to directly apply the conventional methods for the newborn brain. Inspired by the original fuzzy object model introduced by Udupa et al. at SPIE Medical Imaging 2011, called fuzzy shape object model (FSOM) here, this paper introduces fuzzy intensity object model (FIOM), and proposes a new image segmentation method which combines the FSOM and FIOM into fuzzy connected (FC) image segmentation. The fuzzy object models are built from training datasets in which the cerebral parenchyma is delineated by experts. After registering FSOM with the evaluating image, the proposed method roughly recognizes the cerebral parenchyma region based on a prior knowledge of location, shape, and the MR signal given by the registered FSOM and FIOM. Then, FC image segmentation delineates the cerebral parenchyma using the fuzzy object models. The proposed method has been evaluated using 9 newborn brain MR images using the leave-one-out strategy. The revised age was between -1 and 2 months. Quantitative evaluation using false positive volume fraction (FPVF) and false negative volume fraction (FNVF) has been conducted. Using the evaluation data, a FPVF of 0.75% and FNVF of 3.75% were achieved. More data collection and testing are underway.

Imaging brain tumour microstructure.

Science.gov (United States)

Nilsson, Markus; Englund, Elisabet; Szczepankiewicz, Filip; van Westen, Danielle; Sundgren, Pia C

2018-05-08

Imaging is an indispensable tool for brain tumour diagnosis, surgical planning, and follow-up. Definite diagnosis, however, often demands histopathological analysis of microscopic features of tissue samples, which have to be obtained by invasive means. A non-invasive alternative may be to probe corresponding microscopic tissue characteristics by MRI, or so called 'microstructure imaging'. The promise of microstructure imaging is one of 'virtual biopsy' with the goal to offset the need for invasive procedures in favour of imaging that can guide pre-surgical planning and can be repeated longitudinally to monitor and predict treatment response. The exploration of such methods is motivated by the striking link between parameters from MRI and tumour histology, for example the correlation between the apparent diffusion coefficient and cellularity. Recent microstructure imaging techniques probe even more subtle and specific features, providing parameters associated to cell shape, size, permeability, and volume distributions. However, the range of scenarios in which these techniques provide reliable imaging biomarkers that can be used to test medical hypotheses or support clinical decisions is yet unknown. Accurate microstructure imaging may moreover require acquisitions that go beyond conventional data acquisition strategies. This review covers a wide range of candidate microstructure imaging methods based on diffusion MRI and relaxometry, and explores advantages, challenges, and potential pitfalls in brain tumour microstructure imaging. Copyright © 2018. Published by Elsevier Inc.

Brain MR image segmentation using NAMS in pseudo-color.

Science.gov (United States)

Li, Hua; Chen, Chuanbo; Fang, Shaohong; Zhao, Shengrong

2017-12-01

Image segmentation plays a crucial role in various biomedical applications. In general, the segmentation of brain Magnetic Resonance (MR) images is mainly used to represent the image with several homogeneous regions instead of pixels for surgical analyzing and planning. This paper proposes a new approach for segmenting MR brain images by using pseudo-color based segmentation with Non-symmetry and Anti-packing Model with Squares (NAMS). First of all, the NAMS model is presented. The model can represent the image with sub-patterns to keep the image content and largely reduce the data redundancy. Second, the key idea is proposed that convert the original gray-scale brain MR image into a pseudo-colored image and then segment the pseudo-colored image with NAMS model. The pseudo-colored image can enhance the color contrast in different tissues in brain MR images, which can improve the precision of segmentation as well as directly visual perceptional distinction. Experimental results indicate that compared with other brain MR image segmentation methods, the proposed NAMS based pseudo-color segmentation method performs more excellent in not only segmenting precisely but also saving storage.

MR image-guided portal verification for brain treatment field

International Nuclear Information System (INIS)

Yin Fangfang; Gao Qinghuai; Xie Huchen; Nelson, Diana F.; Yu Yan; Kwok, W. Edmund; Totterman, Saara; Schell, Michael C.; Rubin, Philip

1998-01-01

Purpose: To investigate a method for the generation of digitally reconstructed radiographs directly from MR images (DRR-MRI) to guide a computerized portal verification procedure. Methods and Materials: Several major steps were developed to perform an MR image-guided portal verification procedure. Initially, a wavelet-based multiresolution adaptive thresholding method was used to segment the skin slice-by-slice in MR brain axial images. Some selected anatomical structures, such as target volume and critical organs, were then manually identified and were reassigned to relatively higher intensities. Interslice information was interpolated with a directional method to achieve comparable display resolution in three dimensions. Next, a ray-tracing method was used to generate a DRR-MRI image at the planned treatment position, and the ray tracing was simply performed on summation of voxels along the ray. The skin and its relative positions were also projected to the DRR-MRI and were used to guide the search of similar features in the portal image. A Canny edge detector was used to enhance the brain contour in both portal and simulation images. The skin in the brain portal image was then extracted using a knowledge-based searching technique. Finally, a Chamfer matching technique was used to correlate features between DRR-MRI and portal image. Results: The MR image-guided portal verification method was evaluated using a brain phantom case and a clinical patient case. Both DRR-CT and DRR-MRI were generated using CT and MR phantom images with the same beam orientation and then compared. The matching result indicated that the maximum deviation of internal structures was less than 1 mm. The segmented results for brain MR slice images indicated that a wavelet-based image segmentation technique provided a reasonable estimation for the brain skin. For the clinical patient case with a given portal field, the MR image-guided verification method provided an excellent match between

Brain imaging

International Nuclear Information System (INIS)

Mishkin, F.S.

1978-01-01

The techniques of brain imaging and results in perfusion studies and delayed images are outlined. An analysis of the advantages and disadvantages of the brain scan in a variety of common problems is discussed, especially as compared with other available procedures. Both nonneoplastic and neoplastic lesions are considered. (Auth/C.F.)

Performance Analysis of Unsupervised Clustering Methods for Brain Tumor Segmentation

Directory of Open Access Journals (Sweden)

Tushar H Jaware

2013-10-01

Full Text Available Medical image processing is the most challenging and emerging field of neuroscience. The ultimate goal of medical image analysis in brain MRI is to extract important clinical features that would improve methods of diagnosis & treatment of disease. This paper focuses on methods to detect & extract brain tumour from brain MR images. MATLAB is used to design, software tool for locating brain tumor, based on unsupervised clustering methods. K-Means clustering algorithm is implemented & tested on data base of 30 images. Performance evolution of unsupervised clusteringmethods is presented.

Human brain imaging

International Nuclear Information System (INIS)

Kuhar, M.J.

1987-01-01

Just as there have been dramatic advances in the molecular biology of the human brain in recent years, there also have been remarkable advances in brain imaging. This paper reports on the development and broad application of microscopic imaging techniques which include the autoradiographic localization of receptors and the measurement of glucose utilization by autoradiography. These approaches provide great sensitivity and excellent anatomical resolution in exploring brain organization and function. The first noninvasive external imaging of receptor distributions in the living human brain was achieved by positron emission tomography (PET) scanning. Developments, techniques and applications continue to progress. Magnetic resonance imaging (MRI) is also becoming important. Its initial clinical applications were in examining the structure and anatomy of the brain. However, more recent uses, such as MRI spectroscopy, indicate the feasibility of exploring biochemical pathways in the brain, the metabolism of drugs in the brain, and also of examining some of these procedures at an anatomical resolution which is substantially greater than that obtainable by PET scanning. The issues will be discussed in greater detail

ViRPET--combination of virtual reality and PET brain imaging

Science.gov (United States)

Majewski, Stanislaw; Brefczynski-Lewis, Julie

2017-05-23

Various methods, systems and apparatus are provided for brain imaging during virtual reality stimulation. In one example, among others, a system for virtual ambulatory environment brain imaging includes a mobile brain imager configured to obtain positron emission tomography (PET) scans of a subject in motion, and a virtual reality (VR) system configured to provide one or more stimuli to the subject during the PET scans. In another example, a method for virtual ambulatory environment brain imaging includes providing stimulation to a subject through a virtual reality (VR) system; and obtaining a positron emission tomography (PET) scan of the subject while moving in response to the stimulation from the VR system. The mobile brain imager can be positioned on the subject with an array of imaging photodetector modules distributed about the head of the subject.

SPECT brain perfusion imaging in mild traumatic brain injury

International Nuclear Information System (INIS)

Li Juan; Liu Baojun; Zhao Feng; He Lirong; Xia Yucheng

2003-01-01

Objective: To study the clinical value of SPECT brain perfusion imaging after mild traumatic brain injury and to evaluate the mechanism of brain blood flow changes in the brain traumatic symptoms. Methods: SPECT 99 Tc m -ethylene cysteinate dimer (ECD) brain perfusion imaging was performed on 39 patients with normal consciousness and normal computed tomography. The study was performed on 23 patients within 3 months after the accidental injury and on 16 patients at more than 3 months post-injury. The cerebellum was used as the reference site (100% maximum value). Any decrease in cerebral perfusion in cortex or basal ganglia to below 70%, or even to below 50% in the medial temporal lobe, compared to the cerebellar reference was considered abnormal. Results: The results of 23 patients (59%) were abnormal. Among them, 20 patients showed 74 focal lesions with an average of 3.7 per patient (15 studies performed within 3 months and 8 studies performed more than 3 months after injury). The remaining 3 showed diffuse hypoperfusion (two at the early stage and one at more than 3 months after the injury). The 13 abnormal studies performed at the early stage showed 58 lesions (average, 4.5 per patient), whereas there was a reduction to an average of 2.3 per patient in the 7 patients (total 16 lesions) at more than 3 months post-injury. In the 20 patients with focal lesions, mainly the following regions were involved: frontal lobes 43.2% (32/74), basal ganglia 24.3% (18/74) and temporal lobes 17.6% (13/74). Conclusions: 1) SPECT brain perfusion imaging is more sensitive than computed tomography in detecting brain lesions of mild traumatic brain injury. 2) SPECT brain perfusion imaging is more sensitive at early stage than at late stage after injury. 3) The most common complaints were headache, dizziness, memory deficit. The patients without loss of consciousness may present brain hypoperfusion, too. 4) The changes may explain a neurological component of the patient symptoms in

The imaging diagnosis of diffuse brain swelling due to severe brain trauma

International Nuclear Information System (INIS)

Shen Jianqiang; Hu Jiawang

2008-01-01

Objective: To discuss the clinical and pathological characteristics and the imaging types of the diffuse brain swelling due to severe brain trauma. Methods: The clinical data and CT and MR images on 48 cases with diffuse brain swelling due to severe brain trauma were analyzed. Results: Among these 48 cases of the diffuse brain swelling due to severe brain trauma, 33 cases were complicated with brain contusions (including 12 cases brain diffuse axonal injury, 1 case infarct of the right basal ganglion), 31 cases were complicated with hematoma (epidural, subdural or intracerebral), 27 cases were complicated with skull base fracture, and 10 cases were complicated with subarachnoid hematoma. The CT and MR imaging of the diffuse brain swelling included as followed: (1) Symmetrically diffuse brain swelling in both cerebral hemispheres with cerebral ventricles decreased or disappeared, without median line shift. (2)Diffuse brain swelling in one side cerebral hemisphere with cerebral ventricles decreased or disappeared at same side, and median line shift to other side. (3) Subarachnoid hematoma or little subcortex intracerebral hematoma were complicated. (4) The CT value of the cerebral could be equal, lower or higher comparing with normal. Conclusion: The pathological reason of diffuse brain swelling was the brain vessel expanding resulting from hypothalamus and brainstem injured in severe brain trauma. There were four CT and MR imaging findings in diffuse brain swelling. The diffuse brain swelling without hematoma may be caused by ischemical reperfusion injury. (authors)

Progress in clinical research and application of resting state functional brain imaging

International Nuclear Information System (INIS)

Long Miaomiao; Ni Hongyan

2013-01-01

Resting state functional brain imaging experimental design is free of stimulus task and offers various parametric maps through different data-driven post processing methods with endogenous BOLD signal changes as the source of imaging. Mechanism of resting state brain activities could be extensively studied with improved patient compliance and clinical application compared with task related functional brain imaging. Also resting state functional brain imaging can be used as a method of data acquisition, with implicit neuronal activity as a kind of experimental design, to reveal characteristic brain activities of epileptic patient. Even resting state functional brain imaging data processing method can be used to analyze task related functional MRI data, opening new horizons of task related functional MRI study. (authors)

An automatic rat brain extraction method based on a deformable surface model.

Science.gov (United States)

Li, Jiehua; Liu, Xiaofeng; Zhuo, Jiachen; Gullapalli, Rao P; Zara, Jason M

2013-08-15

The extraction of the brain from the skull in medical images is a necessary first step before image registration or segmentation. While pre-clinical MR imaging studies on small animals, such as rats, are increasing, fully automatic imaging processing techniques specific to small animal studies remain lacking. In this paper, we present an automatic rat brain extraction method, the Rat Brain Deformable model method (RBD), which adapts the popular human brain extraction tool (BET) through the incorporation of information on the brain geometry and MR image characteristics of the rat brain. The robustness of the method was demonstrated on T2-weighted MR images of 64 rats and compared with other brain extraction methods (BET, PCNN, PCNN-3D). The results demonstrate that RBD reliably extracts the rat brain with high accuracy (>92% volume overlap) and is robust against signal inhomogeneity in the images. Copyright © 2013 Elsevier B.V. All rights reserved.

Functional brain imaging; Funktionelle Hirnbildgebung

Energy Technology Data Exchange (ETDEWEB)

Gizewski, E.R. [Medizinische Universitaet Innsbruck, Universitaetsklinik fuer Neuroradiologie, Innsbruck (Austria)

2016-02-15

Functional magnetic resonance imaging (fMRI) is a non-invasive method that has become one of the major tools for understanding human brain function and in recent years has also been developed for clinical applications. Changes in hemodynamic signals correspond to changes in neuronal activity with good spatial and temporal resolution in fMRI. Using high-field MR systems and increasingly dedicated statistics and postprocessing, activated brain areas can be detected and superimposed on anatomical images. Currently, fMRI data are often combined in multimodal imaging, e. g. with diffusion tensor imaging (DTI) sequences. This method is helping to further understand the physiology of cognitive brain processes and is also being used in a number of clinical applications. In addition to the blood oxygenation level-dependent (BOLD) signals, this article deals with the construction of fMRI investigations, selection of paradigms and evaluation in the clinical routine. Clinically, this method is mainly used in the planning of brain surgery, analyzing the location of brain tumors in relation to eloquent brain areas and the lateralization of language processing. As the BOLD signal is dependent on the strength of the magnetic field as well as other limitations, an overview of recent developments is given. Increases of magnetic field strength (7 T), available head coils and advances in MRI analytical methods have led to constant improvement in fMRI signals and experimental design. Especially the depiction of eloquent brain regions can be done easily and quickly and has become an essential part of presurgical planning. (orig.) [German] Mittlerweile ist die funktionelle MRT (fMRT) eine Methode, die nicht mehr nur in der neurowissenschaftlichen Routine verwendet wird. Die fMRT ermoeglicht die nichtinvasive Darstellung der Hirnaktivitaet in guter raeumlicher und zeitlicher Aufloesung unter Ausnutzung der Durchblutungsaenderung aufgrund der erhoehten Nervenzellaktivitaet. Unter

Potential brain imaging using near field radiomety

International Nuclear Information System (INIS)

Oikonomou, A; Karanasiou, I S; Uzunoglu, N K

2009-01-01

During the past decades there has been a tremendous increase throughout the scientific community for developing methods of understanding human brain functionality, as diagnosis and treatment of diseases and malfunctions could be effectively developed through understanding of how the brain works. In parallel, research effort is driven on minimizing drawbacks of existing imaging techniques including potential risks from radiation and invasive attributes of the imaging methodologies. Towards that direction, we are proposing a near filed radiometry imaging system for intracranial applications. The methodology is based on the fact that human tissues emit chaotic thermal type radiation at temperatures above the absolute zero. Using a phase shifted antenna array system, resolution, detection depth and sensitivity are increased. Several different setups are theoretically investigated and compared, so as to make the proposed system useful for clinical applications. Combining previous research as well as new findings, the possibility of using the proposed system as a complementary method for brain imaging is discussed in the present paper.

Brain Volume Estimation Enhancement by Morphological Image Processing Tools

Directory of Open Access Journals (Sweden)

Zeinali R.

2017-12-01

Full Text Available Background: Volume estimation of brain is important for many neurological applications. It is necessary in measuring brain growth and changes in brain in normal/ abnormal patients. Thus, accurate brain volume measurement is very important. Magnetic resonance imaging (MRI is the method of choice for volume quantification due to excellent levels of image resolution and between-tissue contrast. Stereology method is a good method for estimating volume but it requires to segment enough MRI slices and have a good resolution. In this study, it is desired to enhance stereology method for volume estimation of brain using less MRI slices with less resolution. Methods: In this study, a program for calculating volume using stereology method has been introduced. After morphologic method, dilation was applied and the stereology method enhanced. For the evaluation of this method, we used T1-wighted MR images from digital phantom in BrainWeb which had ground truth. Results: The volume of 20 normal brain extracted from BrainWeb, was calculated. The volumes of white matter, gray matter and cerebrospinal fluid with given dimension were estimated correctly. Volume calculation from Stereology method in different cases was made. In three cases, Root Mean Square Error (RMSE was measured. Case I with T=5, d=5, Case II with T=10, D=10 and Case III with T=20, d=20 (T=slice thickness, d=resolution as stereology parameters. By comparing these results of two methods, it is obvious that RMSE values for our proposed method are smaller than Stereology method. Conclusion: Using morphological operation, dilation allows to enhance the estimation volume method, Stereology. In the case with less MRI slices and less test points, this method works much better compared to Stereology method.

FCM Clustering Algorithms for Segmentation of Brain MR Images

Directory of Open Access Journals (Sweden)

Yogita K. Dubey

2016-01-01

Full Text Available The study of brain disorders requires accurate tissue segmentation of magnetic resonance (MR brain images which is very important for detecting tumors, edema, and necrotic tissues. Segmentation of brain images, especially into three main tissue types: Cerebrospinal Fluid (CSF, Gray Matter (GM, and White Matter (WM, has important role in computer aided neurosurgery and diagnosis. Brain images mostly contain noise, intensity inhomogeneity, and weak boundaries. Therefore, accurate segmentation of brain images is still a challenging area of research. This paper presents a review of fuzzy c-means (FCM clustering algorithms for the segmentation of brain MR images. The review covers the detailed analysis of FCM based algorithms with intensity inhomogeneity correction and noise robustness. Different methods for the modification of standard fuzzy objective function with updating of membership and cluster centroid are also discussed.

Brain tumor segmentation using holistically nested neural networks in MRI images.

Science.gov (United States)

Zhuge, Ying; Krauze, Andra V; Ning, Holly; Cheng, Jason Y; Arora, Barbara C; Camphausen, Kevin; Miller, Robert W

2017-10-01

Gliomas are rapidly progressive, neurologically devastating, largely fatal brain tumors. Magnetic resonance imaging (MRI) is a widely used technique employed in the diagnosis and management of gliomas in clinical practice. MRI is also the standard imaging modality used to delineate the brain tumor target as part of treatment planning for the administration of radiation therapy. Despite more than 20 yr of research and development, computational brain tumor segmentation in MRI images remains a challenging task. We are presenting a novel method of automatic image segmentation based on holistically nested neural networks that could be employed for brain tumor segmentation of MRI images. Two preprocessing techniques were applied to MRI images. The N4ITK method was employed for correction of bias field distortion. A novel landmark-based intensity normalization method was developed so that tissue types have a similar intensity scale in images of different subjects for the same MRI protocol. The holistically nested neural networks (HNN), which extend from the convolutional neural networks (CNN) with a deep supervision through an additional weighted-fusion output layer, was trained to learn the multiscale and multilevel hierarchical appearance representation of the brain tumor in MRI images and was subsequently applied to produce a prediction map of the brain tumor on test images. Finally, the brain tumor was obtained through an optimum thresholding on the prediction map. The proposed method was evaluated on both the Multimodal Brain Tumor Image Segmentation (BRATS) Benchmark 2013 training datasets, and clinical data from our institute. A dice similarity coefficient (DSC) and sensitivity of 0.78 and 0.81 were achieved on 20 BRATS 2013 training datasets with high-grade gliomas (HGG), based on a two-fold cross-validation. The HNN model built on the BRATS 2013 training data was applied to ten clinical datasets with HGG from a locally developed database. DSC and sensitivity of

Connectome imaging for mapping human brain pathways.

Science.gov (United States)

Shi, Y; Toga, A W

2017-09-01

With the fast advance of connectome imaging techniques, we have the opportunity of mapping the human brain pathways in vivo at unprecedented resolution. In this article we review the current developments of diffusion magnetic resonance imaging (MRI) for the reconstruction of anatomical pathways in connectome studies. We first introduce the background of diffusion MRI with an emphasis on the technical advances and challenges in state-of-the-art multi-shell acquisition schemes used in the Human Connectome Project. Characterization of the microstructural environment in the human brain is discussed from the tensor model to the general fiber orientation distribution (FOD) models that can resolve crossing fibers in each voxel of the image. Using FOD-based tractography, we describe novel methods for fiber bundle reconstruction and graph-based connectivity analysis. Building upon these novel developments, there have already been successful applications of connectome imaging techniques in reconstructing challenging brain pathways. Examples including retinofugal and brainstem pathways will be reviewed. Finally, we discuss future directions in connectome imaging and its interaction with other aspects of brain imaging research.

Image-guided procedures in brain biopsy.

Science.gov (United States)

Fujita, K; Yanaka, K; Meguro, K; Narushima, K; Iguchi, M; Nakai, Y; Nose, T

1999-07-01

Image-guided procedures, such as computed tomography (CT)-guided stereotactic and ultrasound-guided methods, can assist neurosurgeons in localizing the relevant pathology. The characteristics of image-guided procedures are important for their appropriate use, especially in brain biopsy. This study reviewed the results of various image-guided brain biopsies to ascertain the advantages and disadvantages. Brain biopsies assisted by CT-guided stereotactic, ultrasound-guided, Neuronavigator-guided, and the combination of ultrasound and Neuronavigator-guided procedures were carried out in seven, eight, one, and three patients, respectively. Four patients underwent open biopsy without a guiding system. Twenty of 23 patients had a satisfactory diagnosis after the initial biopsy. Three patients failed to have a definitive diagnosis after the initial procedure, one due to insufficient volume sampling after CT-guided procedure, and two due to localization failure by ultrasound because the lesions were nonechogenic. All patients who underwent biopsy using the combination of ultrasound and Neuronavigator-guided methods had a satisfactory result. The CT-guided procedure provided an efficient method of approaching any intracranial target and was appropriate for the diagnosis of hypodense lesions, but tissue sampling was sometimes not sufficient to achieve a satisfactory diagnosis. The ultrasound-guided procedure was suitable for the investigation of hyperdense lesions, but was difficult to localize nonechogenic lesions. The combination of ultrasound and Neuronavigator methods improved the diagnostic accuracy even in nonechogenic lesions such as malignant lymphoma. Therefore, it is essential to choose the most appropriate guiding method for brain biopsy according to the radiological nature of the lesions.

Brain spect imaging

International Nuclear Information System (INIS)

Lee, R.G.L.; Hill, T.C.; Holman, B.L.

1989-01-01

This paper discusses how the rapid development of single-photon radiopharmaceuticals has given new life to tomographic brain imaging in nuclear medicine. Further developments in radiopharmaceuticals and refinements in neuro-SPECT (single-photon emission computed tomography) instrumentation should help to reinstate brain scintigraphy as an important part of neurologic diagnosis. SPECT of the brain evolved from experimentation using prototype instrumentation during the early 1960s. Although tomographic studies provided superior diagnostic accuracy when compared to planar techniques, the arrival of X-ray CT of the head resulted in the rapid demise of technetium brain imaging

Thresholding magnetic resonance images of human brain

Institute of Scientific and Technical Information of China (English)

Qing-mao HU; Wieslaw L NOWINSKI

2005-01-01

In this paper, methods are proposed and validated to determine low and high thresholds to segment out gray matter and white matter for MR images of different pulse sequences of human brain. First, a two-dimensional reference image is determined to represent the intensity characteristics of the original three-dimensional data. Then a region of interest of the reference image is determined where brain tissues are present. The non-supervised fuzzy c-means clustering is employed to determine: the threshold for obtaining head mask, the low threshold for T2-weighted and PD-weighted images, and the high threshold for T1-weighted, SPGR and FLAIR images. Supervised range-constrained thresholding is employed to determine the low threshold for T1-weighted, SPGR and FLAIR images. Thresholding based on pairs of boundary pixels is proposed to determine the high threshold for T2- and PD-weighted images. Quantification against public data sets with various noise and inhomogeneity levels shows that the proposed methods can yield segmentation robust to noise and intensity inhomogeneity. Qualitatively the proposed methods work well with real clinical data.

Comparison of seven optical clearing methods for mouse brain

Science.gov (United States)

Wan, Peng; Zhu, Jingtan; Yu, Tingting; Zhu, Dan

2018-02-01

Recently, a variety of tissue optical clearing techniques have been developed to reduce light scattering for imaging deeper and three-dimensional reconstruction of tissue structures. Combined with optical imaging techniques and diverse labeling methods, these clearing methods have significantly promoted the development of neuroscience. However, most of the protocols were proposed aiming for specific tissue type. Though there are some comparison results, the clearing methods covered are limited and the evaluation indices are lack of uniformity, which made it difficult to select a best-fit protocol for clearing in practical applications. Hence, it is necessary to systematically assess and compare these clearing methods. In this work, we evaluated the performance of seven typical clearing methods, including 3DISCO, uDISCO, SeeDB, ScaleS, ClearT2, CUBIC and PACT, on mouse brain samples. First, we compared the clearing capability on both brain slices and whole-brains by observing brain transparency. Further, we evaluated the fluorescence preservation and the increase of imaging depth. The results showed that 3DISCO, uDISCO and PACT posed excellent clearing capability on mouse brains, ScaleS and SeeDB rendered moderate transparency, while ClearT2 was the worst. Among those methods, ScaleS was the best on fluorescence preservation, and PACT achieved the highest increase of imaging depth. This study is expected to provide important reference for users in choosing most suitable brain optical clearing method.

Computerized analysis of brain perfusion parameter images

International Nuclear Information System (INIS)

Turowski, B.; Haenggi, D.; Wittsack, H.J.; Beck, A.; Aurich, V.

2007-01-01

Purpose: The development of a computerized method which allows a direct quantitative comparison of perfusion parameters. The display should allow a clear direct comparison of brain perfusion parameters in different vascular territories and over the course of time. The analysis is intended to be the basis for further evaluation of cerebral vasospasm after subarachnoid hemorrhage (SAH). The method should permit early diagnosis of cerebral vasospasm. Materials and Methods: The Angiotux 2D-ECCET software was developed with a close cooperation between computer scientists and clinicians. Starting from parameter images of brain perfusion, the cortex was marked, segmented and assigned to definite vascular territories. The underlying values were averages for each segment and were displayed in a graph. If a follow-up was available, the mean values of the perfusion parameters were displayed in relation to time. The method was developed under consideration of CT perfusion values but is applicable for other methods of perfusion imaging. Results: Computerized analysis of brain perfusion parameter images allows an immediate comparison of these parameters and follow-up of mean values in a clear and concise manner. Values are related to definite vascular territories. The tabular output facilitates further statistic evaluations. The computerized analysis is precisely reproducible, i. e., repetitions result in exactly the same output. (orig.)

Functional brain imaging of gastrointestinal sensation in health and disease

Institute of Scientific and Technical Information of China (English)

Lukas Van Oudenhove; Steven J Coen; Qasim Aziz

2007-01-01

It has since long been known, from everyday experience as well as from animal and human studies, that psychological processes-both affective and cognitiveexert an influence on gastrointestinal sensorimotor function. More specifically, a link between psychological factors and visceral hypersensitivity has been suggested,mainly based on research in functional gastrointestinal disorder patients. However, until recently, the exact nature of this putative relationship remained unclear,mainly due to a lack of non-invasive methods to study the (neurobiological) mechanisms underlying this relationship in non-sleeping humans. As functional brain imaging, introduced in visceral sensory neuroscience some 10 years ago, does provide a method for in vivo study of brain-gut interactions, insight into the neurobiological mechanisms underlying visceral sensation in general and the influence of psychological factors more particularly,has rapidly grown. In this article, an overview of brain imaging evidence on gastrointestinal sensation will be given, with special emphasis on the brain mechanisms underlying the interaction between affective & cognitive processes and visceral sensation. First, the reciprocal neural pathways between the brain and the gut (braingut axis) will be briefly outlined, including brain imaging evidence in healthy volunteers. Second, functional brain imaging studies assessing the influence of psychological factors on brain processing of visceral sensation in healthy humans will be discussed in more detail.Finally, brain imaging work investigating differences in brain responses to visceral distension between healthy volunteers and functional gastrointestinal disorder patients will be highlighted.

A new methodical approach in neuroscience: assessing inter-personal brain coupling using functional near-infrared imaging (fNIRI hyperscanning

Directory of Open Access Journals (Sweden)

Felix eScholkmann

2013-11-01

Full Text Available Since the first demonstration of how to simultaneously measure brain activity using functional magnetic resonance imaging (fMRI on two subjects about 10 years ago, a new paradigm in neuroscience is emerging: the assessment of the inter-brain coupling between two or more subjects, termed hyperscanning. The hyperscanning approach has the potential to enable a new view on how the brain works and will reveal as yet undiscovered brain functions based on brain-to-brain coupling, since the single-subject setting cannot capture them. In particular, functional near-infrared imaging (fNIRI hyperscanning is a promising new method, offering a cost-effective, easy to apply and reliable technology to measure inter-personal interactions in a natural context. In this short review we report on fNIRI hyperscanning studies published so far and summarize opportunities and challenges for future studies.

Creation and evaluation of complementary composite three-dimensional image in various brain diseases. An application of three-dimensional brain SPECT image and three-dimensional CT image

International Nuclear Information System (INIS)

Seiki, Yoshikatsu; Shibata, Iekado; Mito, Toshiaki; Sugo, Nobuo

2000-01-01

The purpose of this study was to develop 3D composite images for use in functional and anatomical evaluation of various cerebral pathologies. Imaging studies were performed in normal volunteers, patients with hydrocephalus and patients with brain tumor (meningioma and metastatic tumor) using a three-detector SPECT system (Prism 3000) and helical CT scanner (Xvigor). 123 I-IMP was used in normal volunteers and patients with hydrocephalus, and 201 TLCL in patients with brain tumor. An Application Visualization System-Medical Viewer (AVS-MV) was used on a workstation (Titan 2) to generate 3D images. A new program was developed by synthesizing surface rendering and volume rendering techniques. The clinical effects of shunt operations were successfully evaluated in patients with hydrocephalus by means of translucent 3D images of the deep brain. Changes in the hypoperfusion area around the cerebral ventricle were compared with morphological changes in the cerebral ventricle on CT. In addition to the information concerning the characteristics of brain tumors and surrounding edemas, hemodynamic changes and changeable hypoperfusion areas around the tumors were visualized on 3D composite CT and SPECT images. A new method of generating 3D composite images of CT and SPECT was developed by combining graphic data from different systems on the same workstation. Complementary 3D composite images facilitated quantitative analysis of brain volume and functional analysis in various brain diseases. (author)

Brain perfusion imaging with iodinated amines

International Nuclear Information System (INIS)

Kung, H.F.

1989-01-01

Traditional nuclear medicine brain study using 99m Tc pertechnetate, glucoheptonate or diethlenetriaminepentacetic acid (DTPA) and planar imaging has experienced a significant decline in the past 10 years. This is mainly due to the introduction of X-ray CT and more recently the nuclear magnetic resonance (NMR) imaging, by which detailed morphology of the brain, including the detection of breakdown of the blood-brain barrier, can be obtained. The nuclear medicine brain imaging is only prescribed as a complementary test when X-ray CT is negative or equivocal and clinical suspicion remains. The attention of nuclear medicine brain imaging has been shifted from the detection of the breakdown of the blood-brain barrier to the study of brain function-perfusion, metabolism, and receptor binding, etc. The functional brain imaging provides diagnostic information usually unattainable by other radiological techniques. In this article, the iodinated amines as brain perfusion imaging agents are reviewed. Potential clinical application of these agents is discussed

Research on segmentation based on multi-atlas in brain MR image

Science.gov (United States)

Qian, Yuejing

2018-03-01

Accurate segmentation of specific tissues in brain MR image can be effectively achieved with the multi-atlas-based segmentation method, and the accuracy mainly depends on the image registration accuracy and fusion scheme. This paper proposes an automatic segmentation method based on the multi-atlas for brain MR image. Firstly, to improve the registration accuracy in the area to be segmented, we employ a target-oriented image registration method for the refinement. Then In the label fusion, we proposed a new algorithm to detect the abnormal sparse patch and simultaneously abandon the corresponding abnormal sparse coefficients, this method is made based on the remaining sparse coefficients combined with the multipoint label estimator strategy. The performance of the proposed method was compared with those of the nonlocal patch-based label fusion method (Nonlocal-PBM), the sparse patch-based label fusion method (Sparse-PBM) and majority voting method (MV). Based on our experimental results, the proposed method is efficient in the brain MR images segmentation compared with MV, Nonlocal-PBM, and Sparse-PBM methods.

Brain Imaging, Forward Inference, and Theories of Reasoning

Science.gov (United States)

Heit, Evan

2015-01-01

This review focuses on the issue of how neuroimaging studies address theoretical accounts of reasoning, through the lens of the method of forward inference (Henson, 2005, 2006). After theories of deductive and inductive reasoning are briefly presented, the method of forward inference for distinguishing between psychological theories based on brain imaging evidence is critically reviewed. Brain imaging studies of reasoning, comparing deductive and inductive arguments, comparing meaningful versus non-meaningful material, investigating hemispheric localization, and comparing conditional and relational arguments, are assessed in light of the method of forward inference. Finally, conclusions are drawn with regard to future research opportunities. PMID:25620926

Brain imaging, forward inference, and theories of reasoning.

Science.gov (United States)

Heit, Evan

2014-01-01

This review focuses on the issue of how neuroimaging studies address theoretical accounts of reasoning, through the lens of the method of forward inference (Henson, 2005, 2006). After theories of deductive and inductive reasoning are briefly presented, the method of forward inference for distinguishing between psychological theories based on brain imaging evidence is critically reviewed. Brain imaging studies of reasoning, comparing deductive and inductive arguments, comparing meaningful versus non-meaningful material, investigating hemispheric localization, and comparing conditional and relational arguments, are assessed in light of the method of forward inference. Finally, conclusions are drawn with regard to future research opportunities.

Brain imaging and schizophrenia

International Nuclear Information System (INIS)

Martinot, J.L.; Dao-Castellana, M.H.

1991-01-01

Brain structures and brain function have been investigated by the new brain imaging techniques for more than ten years. In Psychiatry, these techniques could afford a new understanding of mental diseases. In schizophrenic patients, CAT scanner and RMI pointed out statistically significant ventricular enlargments which are presently considered as evidence for abnormalities in brain maturation. Functional imaging techniques reported metabolic dysfunctions in the cortical associative areas which are probably linked to the cognitive features of schizophrenics [fr

Emerging Techniques in Brain Tumor Imaging: What Radiologists Need to Know

Energy Technology Data Exchange (ETDEWEB)

Kim, Minjae; Kim, Ho Sung [Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul 05505 (Korea, Republic of)

2016-11-01

Among the currently available brain tumor imaging, advanced MR imaging techniques, such as diffusion-weighted MR imaging and perfusion MR imaging, have been used for solving diagnostic challenges associated with conventional imaging and for monitoring the brain tumor treatment response. Further development of advanced MR imaging techniques and postprocessing methods may contribute to predicting the treatment response to a specific therapeutic regimen, particularly using multi-modality and multiparametric imaging. Over the next few years, new imaging techniques, such as amide proton transfer imaging, will be studied regarding their potential use in quantitative brain tumor imaging. In this review, the pathophysiologic considerations and clinical validations of these promising techniques are discussed in the context of brain tumor characterization and treatment response.

Computational and mathematical methods in brain atlasing.

Science.gov (United States)

Nowinski, Wieslaw L

2017-12-01

Brain atlases have a wide range of use from education to research to clinical applications. Mathematical methods as well as computational methods and tools play a major role in the process of brain atlas building and developing atlas-based applications. Computational methods and tools cover three areas: dedicated editors for brain model creation, brain navigators supporting multiple platforms, and atlas-assisted specific applications. Mathematical methods in atlas building and developing atlas-aided applications deal with problems in image segmentation, geometric body modelling, physical modelling, atlas-to-scan registration, visualisation, interaction and virtual reality. Here I overview computational and mathematical methods in atlas building and developing atlas-assisted applications, and share my contribution to and experience in this field.

Whole brain imaging with Serial Two-Photon Tomography

Directory of Open Access Journals (Sweden)

Stephen P Amato

2016-03-01

Full Text Available Imaging entire mouse brains at submicron resolution has historically been a challenging undertaking and largely confined to the province of dedicated atlasing initiatives. The has limited systematic investigations into important areas of neuroscience, such as neural circuits, brain mapping and neurodegeneration. In this paper, we describe in detail Serial Two-Photon (STP tomography, a robust, reliable method for imaging entire brains with histological detail. We provide examples of how the basic methodology can be extended to other imaging modalities, such as optical coherence tomography, in order to provide unique contrast mechanisms. Furthermore we provide a survey of the research that STP tomography has enabled in the field of neuroscience, provide examples of how this technology enables quantitative whole brain studies, and discuss the current limitations of STP tomography-based approaches

3-D brain image registration using optimal morphological processing

International Nuclear Information System (INIS)

Loncaric, S.; Dhawan, A.P.

1994-01-01

The three-dimensional (3-D) registration of Magnetic Resonance (MR) and Positron Emission Tomographic (PET) images of the brain is important for analysis of the human brain and its diseases. A procedure for optimization of (3-D) morphological structuring elements, based on a genetic algorithm, is presented in the paper. The registration of the MR and PET images is done by means of a registration procedure in two major phases. In the first phase, the Iterative Principal Axis Transform (IPAR) is used for initial registration. In the second phase, the optimal shape description method based on the Morphological Signature Transform (MST) is used for final registration. The morphological processing is used to improve the accuracy of the basic IPAR method. The brain ventricle is used as a landmark for MST registration. A near-optimal structuring element obtained by means of a genetic algorithm is used in MST to describe the shape of the ventricle. The method has been tested on the set of brain images demonstrating the feasibility of approach. (author). 11 refs., 3 figs

Automatic segmentation of MR brain images with a convolutional neural network

NARCIS (Netherlands)

Moeskops, P.; Viergever, M.A.; Mendrik, A.M.; de Vries, L.S.; Benders, M.J.N.L.; Išgum, I.

2016-01-01

Automatic segmentation in MR brain images is important for quantitative analysis in large-scale studies with images acquired at all ages. This paper presents a method for the automatic segmentation of MR brain images into a number of tissue classes using a convolutional neural network. To ensure

Evaluation of FSE and FSPGR MRI imaging methods for planning cranial stereotactic irradiation of a metastatic brain tumor

International Nuclear Information System (INIS)

Terada, Masaki; Tanoi, Chiharu

2003-01-01

Cranial stereotactic irradiation (STI) of a metastatic brain tumor (BT) was planned by fusing CT images with MRI images using the landmark method of the X-Knife System. The MRI images revealed the BT, the critical optic nerve and brain stem of structures and the eyeball and blood vessels that are landmarks. It was important to improve visibility of the BT with sufficient contrast. Therefore, comparison examinations were performed using the two dimensions fast spin echo (2DFSE), the two dimensions fast spoiled gradient echo (2DFSPGR), and the three dimensions fast spoiled gradient echo (3DFSPGR) methods of T1-weighted imaging with Gd-DTPA contrast. Critical structures and the internal structures of the landmark method were suitable for planning STI when the results of three or more points were combined in visual evaluations. However, the 2DFSE method could showed three or more points. The BT also be visually evaluated using three or less points by the FSPGR method, but had reduced visibility. From detailed contents, the fall of visual evaluation by the small thin and solid BT of the diameter of a BT was characteristic. In the whole signal noise ratio (SNR), the 3DFSPGR method is excellent in images analysis, and the 2DFSE method was excellent in contrast noise ratio (CNR) of a BT. The cystic BT accompanied by dropsy was images with clear and good depiction in all scan parameter. However, the FSPGR method was the boundary not clear in the small solid BT, the FSE method was able to recognize the maximum of the diameter of BT most, and depiction was good. Artifacts of blood flow and motion of the FSE method is a fault. However, the FSE method had the highest useful depiction ability of all BT in the STI plan. (author)

Structural brain imaging in diabetes : A methodological perspective

NARCIS (Netherlands)

Jongen, Cynthia; Biessels, Geert Jan

2008-01-01

Brain imaging provides information on brain anatomy and function and progression of cerebral abnormalities can be monitored. This may provide insight into the aetiology of diabetes related cerebral disorders. This paper focuses on the methods for the assessment of white matter hyperintensities and

Functional magnetic resonance imaging of higher brain activity

International Nuclear Information System (INIS)

Cui He; Wang Yunjiu; Chen Runsheng; Tang Xiaowei.

1996-01-01

Functional magnetic resonance images (fMRIs) exhibit small differences in the magnetic resonance signal intensity in positions corresponding to focal areas of brain activation. These signal are caused by variation in the oxygenation state of the venous vasculature. Using this non-invasive and dynamic method, it is possible to localize functional brain activation, in vivo, in normal individuals, with an accuracy of millimeters and a temporal resolution of seconds. Though a series of technical difficulties remain, fMRI is increasingly becoming a key method for visualizing the working brain, and uncovering the topographical organization of the human brain, and understanding the relationship between brain and the mind

Study of automated segmentation of the cerebellum and brainstem on brain MR images

International Nuclear Information System (INIS)

Hayashi, Norio; Matsuura, Yukihiro; Sanada, Shigeru; Suzuki, Masayuki

2005-01-01

MR imaging is an important method for diagnosing abnormalities of the brain. This paper presents an automated method to segment the cerebellum and brainstem for brain MR images. MR images were obtained from 10 normal subjects (male 4, female 6; 22-75 years old, average 31.0 years) and 15 patients with brain atrophy (male 3, female 12; 62-85 years of age, average 76.0 years). The automated method consisted of the following four steps: segmentation of the brain on original images, detection of an upper plane of the cerebellum using the Hough transform, correction of the plane using three-dimensional (3D) information, and segmentation of the cerebellum and brainstem using the plane. The results indicated that the regions obtained by the automated method were visually similar to those obtained by a manual method. The average rates of coincidence between the automated method and manual method were 83.0±9.0% in normal subjects and 86.4±3.6% in patients. (author)

Markerless motion estimation for motion-compensated clinical brain imaging

Science.gov (United States)

Kyme, Andre Z.; Se, Stephen; Meikle, Steven R.; Fulton, Roger R.

2018-05-01

Motion-compensated brain imaging can dramatically reduce the artifacts and quantitative degradation associated with voluntary and involuntary subject head motion during positron emission tomography (PET), single photon emission computed tomography (SPECT) and computed tomography (CT). However, motion-compensated imaging protocols are not in widespread clinical use for these modalities. A key reason for this seems to be the lack of a practical motion tracking technology that allows for smooth and reliable integration of motion-compensated imaging protocols in the clinical setting. We seek to address this problem by investigating the feasibility of a highly versatile optical motion tracking method for PET, SPECT and CT geometries. The method requires no attached markers, relying exclusively on the detection and matching of distinctive facial features. We studied the accuracy of this method in 16 volunteers in a mock imaging scenario by comparing the estimated motion with an accurate marker-based method used in applications such as image guided surgery. A range of techniques to optimize performance of the method were also studied. Our results show that the markerless motion tracking method is highly accurate (brain imaging and holds good promise for a practical implementation in clinical PET, SPECT and CT systems.

Imaging visual function of the human brain

International Nuclear Information System (INIS)

Marg, E.

1988-01-01

Imaging of human brain structure and activity with particular reference to visual function is reviewed along with methods of obtaining the data including computed tomographic (CT) scan, magnetic resonance imaging (MRI), magnetic resonance spectroscopy (MRS), and positron emission tomography (PET). The literature is reviewed and the potential for a new understanding of brain visual function is discussed. PET is reviewed from basic physical principles to the most recent visual brain findings with oxygen-15. It is shown that there is a potential for submillimeter localization of visual functions with sequentially different visual stimuli designed for the temporal separation of the responses. Single photon emission computed tomography (SPECT), a less expensive substitute for PET, is also discussed. MRS is covered from basic physical principles to the current state of the art of in vivo biochemical analysis. Future possible clinical applications are discussed. Improved understanding of the functional neural organization of vision and brain will open a window to maps and circuits of human brain function.119 references

Automatic labeling of MR brain images through extensible learning and atlas forests.

Science.gov (United States)

Xu, Lijun; Liu, Hong; Song, Enmin; Yan, Meng; Jin, Renchao; Hung, Chih-Cheng

2017-12-01

Multiatlas-based method is extensively used in MR brain images segmentation because of its simplicity and robustness. This method provides excellent accuracy although it is time consuming and limited in terms of obtaining information about new atlases. In this study, an automatic labeling of MR brain images through extensible learning and atlas forest is presented to address these limitations. We propose an extensible learning model which allows the multiatlas-based framework capable of managing the datasets with numerous atlases or dynamic atlas datasets and simultaneously ensure the accuracy of automatic labeling. Two new strategies are used to reduce the time and space complexity and improve the efficiency of the automatic labeling of brain MR images. First, atlases are encoded to atlas forests through random forest technology to reduce the time consumed for cross-registration between atlases and target image, and a scatter spatial vector is designed to eliminate errors caused by inaccurate registration. Second, an atlas selection method based on the extensible learning model is used to select atlases for target image without traversing the entire dataset and then obtain the accurate labeling. The labeling results of the proposed method were evaluated in three public datasets, namely, IBSR, LONI LPBA40, and ADNI. With the proposed method, the dice coefficient metric values on the three datasets were 84.17 ± 4.61%, 83.25 ± 4.29%, and 81.88 ± 4.53% which were 5% higher than those of the conventional method, respectively. The efficiency of the extensible learning model was evaluated by state-of-the-art methods for labeling of MR brain images. Experimental results showed that the proposed method could achieve accurate labeling for MR brain images without traversing the entire datasets. In the proposed multiatlas-based method, extensible learning and atlas forests were applied to control the automatic labeling of brain anatomies on large atlas datasets or dynamic

Development of quantitative analysis method for stereotactic brain image. Assessment of reduced accumulation in extent and severity using anatomical segmentation

International Nuclear Information System (INIS)

Mizumura, Sunao; Kumita, Shin-ichiro; Cho, Keiichi; Ishihara, Makiko; Nakajo, Hidenobu; Toba, Masahiro; Kumazaki, Tatsuo

2003-01-01

Through visual assessment by three-dimensional (3D) brain image analysis methods using stereotactic brain coordinates system, such as three-dimensional stereotactic surface projections and statistical parametric mapping, it is difficult to quantitatively assess anatomical information and the range of extent of an abnormal region. In this study, we devised a method to quantitatively assess local abnormal findings by segmenting a brain map according to anatomical structure. Through quantitative local abnormality assessment using this method, we studied the characteristics of distribution of reduced blood flow in cases with dementia of the Alzheimer type (DAT). Using twenty-five cases with DAT (mean age, 68.9 years old), all of whom were diagnosed as probable Alzheimer's disease based on National Institute of Neurological and Communicative Disorders and Stroke-Alzheimer's Disease and Related Disorders Association (NINCDS-ADRDA), we collected I-123 iodoamphetamine SPECT data. A 3D brain map using the 3D-stereotactic surface projections (SSP) program was compared with the data of 20 cases in the control group, who age-matched the subject cases. To study local abnormalities on the 3D images, we divided the whole brain into 24 segments based on anatomical classification. We assessed the extent of an abnormal region in each segment (rate of the coordinates with a Z-value that exceeds the threshold value, in all coordinates within a segment), and severity (average Z-value of the coordinates with a Z-value that exceeds the threshold value). This method clarified orientation and expansion of reduced accumulation, through classifying stereotactic brain coordinates according to the anatomical structure. This method was considered useful for quantitatively grasping distribution abnormalities in the brain and changes in abnormality distribution. (author)

AUTOMATED CLASSIFICATION AND SEGREGATION OF BRAIN MRI IMAGES INTO IMAGES CAPTURED WITH RESPECT TO VENTRICULAR REGION AND EYE-BALL REGION

Directory of Open Access Journals (Sweden)

C. Arunkumar

2014-05-01

Full Text Available Magnetic Resonance Imaging (MRI images of the brain are used for detection of various brain diseases including tumor. In such cases, classification of MRI images captured with respect to ventricular and eye ball regions helps in automated location and classification of such diseases. The methods employed in the paper can segregate the given MRI images of brain into images of brain captured with respect to ventricular region and images of brain captured with respect to eye ball region. First, the given MRI image of brain is segmented using Particle Swarm Optimization (PSO algorithm, which is an optimized algorithm for MRI image segmentation. The algorithm proposed in the paper is then applied on the segmented image. The algorithm detects whether the image consist of a ventricular region or an eye ball region and classifies it accordingly.

A survey of MRI-based medical image analysis for brain tumor studies

Science.gov (United States)

Bauer, Stefan; Wiest, Roland; Nolte, Lutz-P.; Reyes, Mauricio

2013-07-01

MRI-based medical image analysis for brain tumor studies is gaining attention in recent times due to an increased need for efficient and objective evaluation of large amounts of data. While the pioneering approaches applying automated methods for the analysis of brain tumor images date back almost two decades, the current methods are becoming more mature and coming closer to routine clinical application. This review aims to provide a comprehensive overview by giving a brief introduction to brain tumors and imaging of brain tumors first. Then, we review the state of the art in segmentation, registration and modeling related to tumor-bearing brain images with a focus on gliomas. The objective in the segmentation is outlining the tumor including its sub-compartments and surrounding tissues, while the main challenge in registration and modeling is the handling of morphological changes caused by the tumor. The qualities of different approaches are discussed with a focus on methods that can be applied on standard clinical imaging protocols. Finally, a critical assessment of the current state is performed and future developments and trends are addressed, giving special attention to recent developments in radiological tumor assessment guidelines.

A survey of MRI-based medical image analysis for brain tumor studies

International Nuclear Information System (INIS)

Bauer, Stefan; Nolte, Lutz-P; Reyes, Mauricio; Wiest, Roland

2013-01-01

MRI-based medical image analysis for brain tumor studies is gaining attention in recent times due to an increased need for efficient and objective evaluation of large amounts of data. While the pioneering approaches applying automated methods for the analysis of brain tumor images date back almost two decades, the current methods are becoming more mature and coming closer to routine clinical application. This review aims to provide a comprehensive overview by giving a brief introduction to brain tumors and imaging of brain tumors first. Then, we review the state of the art in segmentation, registration and modeling related to tumor-bearing brain images with a focus on gliomas. The objective in the segmentation is outlining the tumor including its sub-compartments and surrounding tissues, while the main challenge in registration and modeling is the handling of morphological changes caused by the tumor. The qualities of different approaches are discussed with a focus on methods that can be applied on standard clinical imaging protocols. Finally, a critical assessment of the current state is performed and future developments and trends are addressed, giving special attention to recent developments in radiological tumor assessment guidelines. (topical review)

Robust generative asymmetric GMM for brain MR image segmentation.

Science.gov (United States)

Ji, Zexuan; Xia, Yong; Zheng, Yuhui

2017-11-01

Accurate segmentation of brain tissues from magnetic resonance (MR) images based on the unsupervised statistical models such as Gaussian mixture model (GMM) has been widely studied during last decades. However, most GMM based segmentation methods suffer from limited accuracy due to the influences of noise and intensity inhomogeneity in brain MR images. To further improve the accuracy for brain MR image segmentation, this paper presents a Robust Generative Asymmetric GMM (RGAGMM) for simultaneous brain MR image segmentation and intensity inhomogeneity correction. First, we develop an asymmetric distribution to fit the data shapes, and thus construct a spatial constrained asymmetric model. Then, we incorporate two pseudo-likelihood quantities and bias field estimation into the model's log-likelihood, aiming to exploit the neighboring priors of within-cluster and between-cluster and to alleviate the impact of intensity inhomogeneity, respectively. Finally, an expectation maximization algorithm is derived to iteratively maximize the approximation of the data log-likelihood function to overcome the intensity inhomogeneity in the image and segment the brain MR images simultaneously. To demonstrate the performances of the proposed algorithm, we first applied the proposed algorithm to a synthetic brain MR image to show the intermediate illustrations and the estimated distribution of the proposed algorithm. The next group of experiments is carried out in clinical 3T-weighted brain MR images which contain quite serious intensity inhomogeneity and noise. Then we quantitatively compare our algorithm to state-of-the-art segmentation approaches by using Dice coefficient (DC) on benchmark images obtained from IBSR and BrainWeb with different level of noise and intensity inhomogeneity. The comparison results on various brain MR images demonstrate the superior performances of the proposed algorithm in dealing with the noise and intensity inhomogeneity. In this paper, the RGAGMM

Functional brain imaging to investigate the higher brain dysfunction induced by diffuse brain injury

International Nuclear Information System (INIS)

Nariai, Tadashi; Inaji, Motoki; Ohno, Kikuo; Hiura, Mikio; Ishii, Kenji; Hosoda, Chihiro

2011-01-01

Higher brain dysfunction is the major problem of patients who recover from neurotrauma the prevents them from returning to their previous social life. Many such patients do not have focal brain damage detected with morphological imaging. We focused on studying the focal brain dysfunction that can be detected only with functional imaging with positron emission tomography (PET) in relation to the score of various cognition batteries. Patients who complain of higher brain dysfunction without apparent morphological cortical damage were recruited for this study. Thirteen patients with diffuse axonal injury (DAI) or cerebral concussion was included. They underwent a PET study to image glucose metabolism by 18 F-fluorodeoxyglucose (FDG), and central benodiazepine receptor (cBZD-R) (marker of neuronal body) by 11 C-flumazenil, together with cognition measurement by WAIS-R, WMS-R, and WCST etc. PET data were compared with age matched normal controls using statistical parametric mapping (SPM)2. DAI patients had a significant decrease in glucose matabolism and cBZD-R distribution in the cingulated cortex than normal controls. Patients diagnosed with concussion because of shorter consciousness disturbance also had abnormal FDG uptake and cBZD-R distribution. Cognition test scores were variable among patients. Degree of decreased glucose metabolism and cBZD-R distribution in the dominant hemishphere corresponded well to the severity of cognitive disturbance. PET molecular imaging was useful to depict focal cortical dysfunction of neurotrauma patients even when morphological change was not apparent. This method may be promising to clarify the pathophysiology of higher brain dysfunction of patients with diffuse axonal injury or chronic traumatic encephalopathy. (author)

Study of a simple method and software for quantitative measurement of rCBF with 99Tcm-ECD SPECT brain imaging

International Nuclear Information System (INIS)

Shu Boxue; Lai Huaan; Li Zhigang; Shi An

2000-01-01

Objective: To create a simple, practical, stable and easy to popularize rCBF quantitative measurement method. Methods: 1) Creating attenuation correction factor (δ) of brain; 2) Proving a factor (ρ) between planar image and tomographic image; 3) Creating SPECT system to determine the dead time and to correct linear regression equation; 4) Measuring lung retardation rate (R 1 ); 5) Improving Nickel model and editing the software; 6) Clinical application; The modified method was performed in 24 subjects, including 15 healthy controls, 8 patients with epilepsy in intermission and 1 patient with brain infarction. Results: δ = 1.7, ρ = 2.23, R 1 -1 ·100 g -1 . The rCBFs of foci in 8 cases of epilepsy were obviously decreased, (22.5∼34.2) mL·min -1 ·100 g -1 , and in the case of brain infarction was only 7.2 mL·min -1 ·100 g -1 . Conclusions: The method is reliable, practical and easy to perform with good quality control. Overall, it is of high clinical value

[Research on K-means clustering segmentation method for MRI brain image based on selecting multi-peaks in gray histogram].

Science.gov (United States)

Chen, Zhaoxue; Yu, Haizhong; Chen, Hao

2013-12-01

To solve the problem of traditional K-means clustering in which initial clustering centers are selected randomly, we proposed a new K-means segmentation algorithm based on robustly selecting 'peaks' standing for White Matter, Gray Matter and Cerebrospinal Fluid in multi-peaks gray histogram of MRI brain image. The new algorithm takes gray value of selected histogram 'peaks' as the initial K-means clustering center and can segment the MRI brain image into three parts of tissue more effectively, accurately, steadily and successfully. Massive experiments have proved that the proposed algorithm can overcome many shortcomings caused by traditional K-means clustering method such as low efficiency, veracity, robustness and time consuming. The histogram 'peak' selecting idea of the proposed segmentootion method is of more universal availability.

Physiological basis and image processing in functional magnetic resonance imaging: Neuronal and motor activity in brain

Directory of Open Access Journals (Sweden)

Sharma Rakesh

2004-05-01

Full Text Available Abstract Functional magnetic resonance imaging (fMRI is recently developing as imaging modality used for mapping hemodynamics of neuronal and motor event related tissue blood oxygen level dependence (BOLD in terms of brain activation. Image processing is performed by segmentation and registration methods. Segmentation algorithms provide brain surface-based analysis, automated anatomical labeling of cortical fields in magnetic resonance data sets based on oxygen metabolic state. Registration algorithms provide geometric features using two or more imaging modalities to assure clinically useful neuronal and motor information of brain activation. This review article summarizes the physiological basis of fMRI signal, its origin, contrast enhancement, physical factors, anatomical labeling by segmentation, registration approaches with examples of visual and motor activity in brain. Latest developments are reviewed for clinical applications of fMRI along with other different neurophysiological and imaging modalities.

Non-FDG PET imaging of brain tumors

Institute of Scientific and Technical Information of China (English)

HUANG Zemin; GUAN Yihui; ZUO Chuantao; ZHANG Zhengwei; XUE Fangping; LIN Xiangtong

2007-01-01

Due to relatively high uptake of glucose in the brain cortex, the use of FDG PET imaging is greatly limited in brain tumor imaging, especially for low-grade gliomas and some metastatic tumours. More and more tracers with higher specificity were developed lately for brain tumor imaging. There are 3 main types of non-FDG PET tracers:amino acid tracers, choline tracers and nucleic acid tracers. These tracers are now widely applied in many aspects of brain tumor imaging. This article summarized the general use of non-FDG PET in different aspects of brain tumor imaging.

S-HAMMER: hierarchical attribute-guided, symmetric diffeomorphic registration for MR brain images.

Science.gov (United States)

Wu, Guorong; Kim, Minjeong; Wang, Qian; Shen, Dinggang

2014-03-01

Deformable registration has been widely used in neuroscience studies for spatial normalization of brain images onto the standard space. Because of possible large anatomical differences across different individual brains, registration performance could be limited when trying to estimate a single directed deformation pathway, i.e., either from template to subject or from subject to template. Symmetric image registration, however, offers an effective way to simultaneously deform template and subject images toward each other until they meet at the middle point. Although some intensity-based registration algorithms have nicely incorporated this concept of symmetric deformation, the pointwise intensity matching between two images may not necessarily imply the matching of correct anatomical correspondences. Based on HAMMER registration algorithm (Shen and Davatzikos, [2002]: IEEE Trans Med Imaging 21:1421-1439), we integrate the strategies of hierarchical attribute matching and symmetric diffeomorphic deformation to build a new symmetric-diffeomorphic HAMMER registration algorithm, called as S-HAMMER. The performance of S-HAMMER has been extensively compared with 14 state-of-the-art nonrigid registration algorithms evaluated in (Klein et al., [2009]: NeuroImage 46:786-802) by using real brain images in LPBA40, IBSR18, CUMC12, and MGH10 datasets. In addition, the registration performance of S-HAMMER, by comparison with other methods, is also demonstrated on both elderly MR brain images (>70 years old) and the simulated brain images with ground-truth deformation fields. In all experiments, our proposed method achieves the best registration performance over all other registration methods, indicating the high applicability of our method in future neuroscience and clinical applications. Copyright © 2013 Wiley Periodicals, Inc.

Digital subtraction in gadolinium-enhanced MR imaging of the brain: a method to reduce contrast dosage

International Nuclear Information System (INIS)

Chan, J.H.M.; Tsui, E.Y.K.; Chan, C.Y.; Lai, K.F.; Cheung, Y.K.; Wong, K.P.C.; Yuen, M.K.; Chau, L.F.; Fong, D.; Mok, C.K.

2002-01-01

The aim of the study was to investigate the feasibility of using digital subtraction in contrast-enhanced MR imaging of the brain to reduce the MR contrast dosage without jeopardizing patient care. Fifty-two patients with intracranial lesions, either intra-axial or extra-axial, detected by computerized tomography were selected for contrast-enhanced MR imaging with half-dose and full-dose of gadopentetate dimeglumine. The half-dose unsubtracted, full-dose unsubtracted, and half-dose subtracted MR images were visually assessed by counting the number of enhancing brain lesions in the images and quantitatively analyzed by computing their lesion contrast-to-background ratios (CBR). The visual conspicuity of the half-dose subtracted MR images was comparable to that of the full-dose unsubtracted MR images (p>0.05), whereas the CBR of the half-dose subtracted images was approximately two to three times higher than that of the full-dose unsubtracted images. The half-dose subtracted T1-weighted spin-echo images might be able to replace the conventional standard-dose T1-weighted spin-echo images in MR imaging of the brain. (orig.)

Deep Convolutional Neural Networks for Multi-Modality Isointense Infant Brain Image Segmentation

Science.gov (United States)

Zhang, Wenlu; Li, Rongjian; Deng, Houtao; Wang, Li; Lin, Weili; Ji, Shuiwang; Shen, Dinggang

2015-01-01

The segmentation of infant brain tissue images into white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) plays an important role in studying early brain development in health and disease. In the isointense stage (approximately 6–8 months of age), WM and GM exhibit similar levels of intensity in both T1 and T2 MR images, making the tissue segmentation very challenging. Only a small number of existing methods have been designed for tissue segmentation in this isointense stage; however, they only used a single T1 or T2 images, or the combination of T1 and T2 images. In this paper, we propose to use deep convolutional neural networks (CNNs) for segmenting isointense stage brain tissues using multi-modality MR images. CNNs are a type of deep models in which trainable filters and local neighborhood pooling operations are applied alternatingly on the raw input images, resulting in a hierarchy of increasingly complex features. Specifically, we used multimodality information from T1, T2, and fractional anisotropy (FA) images as inputs and then generated the segmentation maps as outputs. The multiple intermediate layers applied convolution, pooling, normalization, and other operations to capture the highly nonlinear mappings between inputs and outputs. We compared the performance of our approach with that of the commonly used segmentation methods on a set of manually segmented isointense stage brain images. Results showed that our proposed model significantly outperformed prior methods on infant brain tissue segmentation. In addition, our results indicated that integration of multi-modality images led to significant performance improvement. PMID:25562829

Brain water mapping with MR imaging

International Nuclear Information System (INIS)

Laine, F.J.; Fatouros, P.P.; Kraft, K.A.

1990-01-01

This paper reports on a recently developed MR imaging technique to determine the spatial distribution of brain water to healthy volunteers. A noninvasive MR imaging technique to obtain absolute measurements of brain water has been developed and validated with phantom and animal studies. Patient confirmation was obtained from independent gravimetric measurements of brain tissue samples harvested by biopsy. This approach entails the production of accurate T1 maps from multiple inversion recovery images of a selected anatomic section and their subsequent conversion into an absolute water image by means of a previously determined calibration curve. Twenty healthy volunteers were studied and their water distribution was determined in a standard section. The following brain water values means and SD grams of water per gram of tissue) were obtained for selected brain regions; white matter, 68.9% ± 1.0; corpus callosum, 67.4% ± 1.1; thalamus, 75.3% ± 1.4; and caudate nucleus, 80.3% ± 1.4. MR imaging water mapping is a valid means of determining water content in a variety of brain tissues

A methodology for generating normal and pathological brain perfusion SPECT images for evaluation of MRI/SPECT fusion methods: application in epilepsy

Energy Technology Data Exchange (ETDEWEB)

Grova, C [Laboratoire IDM, Faculte de Medecine, Universite de Rennes 1, Rennes (France); Jannin, P [Laboratoire IDM, Faculte de Medecine, Universite de Rennes 1, Rennes (France); Biraben, A [Laboratoire IDM, Faculte de Medecine, Universite de Rennes 1, Rennes (France); Buvat, I [INSERM U494, CHU Pitie Salpetriere, Paris (France); Benali, H [INSERM U494, CHU Pitie Salpetriere, Paris (France); Bernard, A M [Service de Medecine Nucleaire, Centre Eugene Marquis, Rennes (France); Scarabin, J M [Laboratoire IDM, Faculte de Medecine, Universite de Rennes 1, Rennes (France); Gibaud, B [Laboratoire IDM, Faculte de Medecine, Universite de Rennes 1, Rennes (France)

2003-12-21

Quantitative evaluation of brain MRI/SPECT fusion methods for normal and in particular pathological datasets is difficult, due to the frequent lack of relevant ground truth. We propose a methodology to generate MRI and SPECT datasets dedicated to the evaluation of MRI/SPECT fusion methods and illustrate the method when dealing with ictal SPECT. The method consists in generating normal or pathological SPECT data perfectly aligned with a high-resolution 3D T1-weighted MRI using realistic Monte Carlo simulations that closely reproduce the response of a SPECT imaging system. Anatomical input data for the SPECT simulations are obtained from this 3D T1-weighted MRI, while functional input data result from an inter-individual analysis of anatomically standardized SPECT data. The method makes it possible to control the 'brain perfusion' function by proposing a theoretical model of brain perfusion from measurements performed on real SPECT images. Our method provides an absolute gold standard for assessing MRI/SPECT registration method accuracy since, by construction, the SPECT data are perfectly registered with the MRI data. The proposed methodology has been applied to create a theoretical model of normal brain perfusion and ictal brain perfusion characteristic of mesial temporal lobe epilepsy. To approach realistic and unbiased perfusion models, real SPECT data were corrected for uniform attenuation, scatter and partial volume effect. An anatomic standardization was used to account for anatomic variability between subjects. Realistic simulations of normal and ictal SPECT deduced from these perfusion models are presented. The comparison of real and simulated SPECT images showed relative differences in regional activity concentration of less than 20% in most anatomical structures, for both normal and ictal data, suggesting realistic models of perfusion distributions for evaluation purposes. Inter-hemispheric asymmetry coefficients measured on simulated data were

Mapping fetal brain development in utero using magnetic resonance imaging: the Big Bang of brain mapping.

Science.gov (United States)

Studholme, Colin

2011-08-15

The development of tools to construct and investigate probabilistic maps of the adult human brain from magnetic resonance imaging (MRI) has led to advances in both basic neuroscience and clinical diagnosis. These tools are increasingly being applied to brain development in adolescence and childhood, and even to neonatal and premature neonatal imaging. Even earlier in development, parallel advances in clinical fetal MRI have led to its growing use as a tool in challenging medical conditions. This has motivated new engineering developments encompassing optimal fast MRI scans and techniques derived from computer vision, the combination of which allows full 3D imaging of the moving fetal brain in utero without sedation. These promise to provide a new and unprecedented window into early human brain growth. This article reviews the developments that have led us to this point, examines the current state of the art in the fields of fast fetal imaging and motion correction, and describes the tools to analyze dynamically changing fetal brain structure. New methods to deal with developmental tissue segmentation and the construction of spatiotemporal atlases are examined, together with techniques to map fetal brain growth patterns.

Brain imaging

International Nuclear Information System (INIS)

Greenfield, L.D.; Bennett, L.R.

1976-01-01

Imaging with radionuclides should be used in a complementary fashion with other neuroradiologic techniques. It is useful in the early detection and evaluation of intracranial neoplasm, cerebrovascular accident and abscess, and in postsurgical follow-up. Cisternography yields useful information about the functional status of cerebrospinal fluid pathways. Computerized axial tomography is a new technique of great promise that produced a cross-sectional image of the brain

Diffusion weighted imaging by MR method

International Nuclear Information System (INIS)

Horikawa, Yoshiharu; Naruse, Shoji; Ebisu, Toshihiko; Tokumitsu, Takuaki; Ueda, Satoshi; Tanaka, Chuzo; Higuchi, Toshihiro; Umeda, Masahiro.

1993-01-01

Diffusion weighted magnetic resonance imaging is a recently developed technique used to examine the micromovement of water molecules in vivo. We have applied this technique to examine various kinds of brain diseases, both experimentally and clinically. The calculated apparent diffusion coefficient (ADC) in vivo showed reliable values. In experimentally induced brain edema in rats, the pathophysiological difference of the type of edema (such as cytotoxic, and vasogenic) could be differentiated on the diffusion weighted MR images. Cytotoxic brain edema showed high intensity (slower diffusion) on the diffusion weighted images. On the other hand, vasogenic brain edema showed a low intensity image (faster diffusion). Diffusion anisotropy was demonstrated according to the direction of myelinated fibers and applied motion proving gradient (MPG). This anisotropy was also demonstrated in human brain tissue along the course of the corpus callosum, pyramidal tract and optic radiation. In brain ischemia cases, lesions were detected as high signal intensity areas, even one hour after the onset of ischemia. Diffusion was faster in brain tumor compared with normal brain. Histological differences were not clearly reflected by the ADC value. In epidermoid tumor cases, the intensity was characteristically high, was demonstrated, and the cerebrospinal fluid border was clearly demonstrated. New clinical information obtainable with this molecular diffusion method will prove to be useful in various clinical studies. (author)

Brain Injury Lesion Imaging Using Preconditioned Quantitative Susceptibility Mapping without Skull Stripping.

Science.gov (United States)

Soman, S; Liu, Z; Kim, G; Nemec, U; Holdsworth, S J; Main, K; Lee, B; Kolakowsky-Hayner, S; Selim, M; Furst, A J; Massaband, P; Yesavage, J; Adamson, M M; Spincemallie, P; Moseley, M; Wang, Y

2018-04-01

Identifying cerebral microhemorrhage burden can aid in the diagnosis and management of traumatic brain injury, stroke, hypertension, and cerebral amyloid angiopathy. MR imaging susceptibility-based methods are more sensitive than CT for detecting cerebral microhemorrhage, but methods other than quantitative susceptibility mapping provide results that vary with field strength and TE, require additional phase maps to distinguish blood from calcification, and depict cerebral microhemorrhages as bloom artifacts. Quantitative susceptibility mapping provides universal quantification of tissue magnetic property without these constraints but traditionally requires a mask generated by skull-stripping, which can pose challenges at tissue interphases. We evaluated the preconditioned quantitative susceptibility mapping MR imaging method, which does not require skull-stripping, for improved depiction of brain parenchyma and pathology. Fifty-six subjects underwent brain MR imaging with a 3D multiecho gradient recalled echo acquisition. Mask-based quantitative susceptibility mapping images were created using a commonly used mask-based quantitative susceptibility mapping method, and preconditioned quantitative susceptibility images were made using precondition-based total field inversion. All images were reviewed by a neuroradiologist and a radiology resident. Ten subjects (18%), all with traumatic brain injury, demonstrated blood products on 3D gradient recalled echo imaging. All lesions were visible on preconditioned quantitative susceptibility mapping, while 6 were not visible on mask-based quantitative susceptibility mapping. Thirty-one subjects (55%) demonstrated brain parenchyma and/or lesions that were visible on preconditioned quantitative susceptibility mapping but not on mask-based quantitative susceptibility mapping. Six subjects (11%) demonstrated pons artifacts on preconditioned quantitative susceptibility mapping and mask-based quantitative susceptibility mapping

Brain imaging during seizure: ictal brain SPECT

International Nuclear Information System (INIS)

Kottamasu, Sambasiva Rao

1997-01-01

The role of single photon computed tomography (SPECT) in presurgical localization of medically intractable complex partial epilepsy (CPE) in children is reviewed. 99m Technetium neurolite, a newer lipophylic agent with a high first pass brain extraction and little or no redistribution is injected during a seizure, while the child is monitored with a video recording and continuous EEG and SPECT imaging is performed in the next 1-3 hours with the images representing regional cerebral profusion at the time of injection. On SPECT studies performed with radiopharmaceutical injected during a seizure, ictal focus is generally hypervascular. Other findings on ictal brain SPECT include hypoperfusion of adjacent cerebral cortex and white matter, hyperperfusion of contralateral motor cortex, hyperperfusion of ipsilateral basal ganglia and thalamus, brain stem and contralateral cerebellum. Ictal brain SPECT is non-invasive, cost effective and highly sensitive for localization of epileptic focus in patients with intractable CPE. (author)

Computerized detection method for asymptomatic white matter lesions in brain screening MR images using a clustering technique

International Nuclear Information System (INIS)

Kunieda, Takuya; Uchiyama, Yoshikazu; Hara, Takeshi

2008-01-01

Asymptomatic white matter lesions are frequently identified by the screening system known as Brain Dock, which is intended for the detection of asymptomatic brain diseases. The detection of asymptomatic white matter lesions is important because their presence is associated with an increased risk of stroke. Therefore, we have developed a computerized method for the detection of asymptomatic white matter lesions in order to assist radiologists in image interpretation as a ''second opinion''. Our database consisted of T 1 - and T 2 -weighted images obtained from 73 patients. The locations of the white matter lesions were determined by an experienced neuroradiologist. In order to restrict the area to be searched for white matter lesions, we first segmented the cerebral region in T 1 -weighted images by applying thresholding and region-growing techniques. To identify the initial candidate lesions, k-means clustering with pixel values in T 1 - and T 2 -weighted images was applied to the segmented cerebral region. To eliminate false positives (FPs), we determined the features, such as location, size, and circularity, of each of the initial candidate lesions. Finally, a rule-based scheme and a quadratic discriminant analysis with these features were employed to distinguish between white matter lesions and FPs. The results showed that the sensitivity for the detection of white matter lesions was 93.2%, with 4.3 FPs per image, suggesting that our computerized method may be useful for the detection of asymptomatic white matter lesions in T 1 - and T 2 -weighted images. (author)

FLAIR images of brain diseases

International Nuclear Information System (INIS)

Segawa, Fuminori; Kinoshita, Masao; Kishibayashi, Jun; Kamada, Kazuhiko; Sunohara, Nobuhiko.

1994-01-01

The present study was designed to assess the usefulness of fluid-attenuated inversion recovery (FLAIR) images in diagnosing brain diseases. The subjects were 20 patients with multiple cerebral infarction, multiple sclerosis, temporal epilepsy, or brain trauma, and 20 other healthy adults. FLAIR images, with a long repetitive time of 6000 msec and a long inversion time of 1400-1600 msec, showed low signal intensity in the cerebrospinal fluid in the lateral ventricles and the cerebral sulci, and high signal intensity in brain tissues. Signal intensity on FLAIR images correlated well with T2 relaxation times under 100 msec. For multiple sclerosis and cerebral infarction, cystic lesions, which were shown on T2-weighted images with long relaxation times over 100 msec, appeared as low-signal areas; and the lesions surrounding the cystic lesions appeared as high-signal areas. For temporal lobe epilepsy, the hippocampus was visualized as a high-signal area. Hippocampal lesions were demonstrated better with FLAIR images than with conventional T2-weighted and proton-density images. In a patient with cerebral trauma, FLAIR images revealed the lobulated structure with the residual cortex shown as a high signal area. The lesions surrounding the cystic change were imaged as high signal areas. These structural changes were demonstrated better with FLAIR images than with conventional T2-weighted sequences. FLAIR images were useful in detecting white matter lesions surrounding the lateral ventricles and cortical and subcortical lesions near the brain surface, which were unclear on conventional T2-weighted and proton-density images. (N.K.)

In Vivo H MR spectroscopic imaging of human brain

International Nuclear Information System (INIS)

Choe, Bo Young; Suh, Tae Suk; Choi, Kyo Ho; Bahk, Yong Whee; Shinn, Kyung Sub

1994-01-01

To evaluate the spatial distribution of various proton metabolites in the human brain with use of water-suppressed in vivo H MR spectroscopic imaging (MRSI) technique. All of water-suppressed in vivo H MRSI were performed on 1.5 T whole-body MRI/MRS system using Stimulated Echo Acquisition Method (STEAM) Chemical Shift Imaging (CSI) pulse sequence. T1-weighted MR images were used for CSI field of view (FOV; 24 cm). Voxel size of 1.5 cm 3 was designated from the periphery of the brain which was divided by 1024 X 16 X 16 data points. Metabolite images of N-acetylaspartate (NAA), creatine/ phosphocreatine (Cr) + choline/phosphocholine (Cho), and complex of γ-aminobutyric acid (GABA) + glutamate (Glu) were obtained on the human brain. Our preliminary study suggests that in vivo H MRSI could provide the metabolite imaging to compensate for hypermetabolism on Positron Emission Tomography (PET) scans on the basis of the metabolic informations on brain tissues. The unique ability of in vivo H MRSI to offer noninvasive information about tissue biochemistry in disease states will stimulate on clinical research and disease diagnosis

Classification of MR brain images by combination of multi-CNNs for AD diagnosis

Science.gov (United States)

Cheng, Danni; Liu, Manhua; Fu, Jianliang; Wang, Yaping

2017-07-01

Alzheimer's disease (AD) is an irreversible neurodegenerative disorder with progressive impairment of memory and cognitive functions. Its early diagnosis is crucial for development of future treatment. Magnetic resonance images (MRI) play important role to help understand the brain anatomical changes related to AD. Conventional methods extract the hand-crafted features such as gray matter volumes and cortical thickness and train a classifier to distinguish AD from other groups. Different from these methods, this paper proposes to construct multiple deep 3D convolutional neural networks (3D-CNNs) to learn the various features from local brain images which are combined to make the final classification for AD diagnosis. First, a number of local image patches are extracted from the whole brain image and a 3D-CNN is built upon each local patch to transform the local image into more compact high-level features. Then, the upper convolution and fully connected layers are fine-tuned to combine the multiple 3D-CNNs for image classification. The proposed method can automatically learn the generic features from imaging data for classification. Our method is evaluated using T1-weighted structural MR brain images on 428 subjects including 199 AD patients and 229 normal controls (NC) from Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Experimental results show that the proposed method achieves an accuracy of 87.15% and an AUC (area under the ROC curve) of 92.26% for AD classification, demonstrating the promising classification performances.

Diffusion Tensor Imaging: Application to the Study of the Developing Brain

Science.gov (United States)

Cascio, Carissa J.; Gerig, Guido; Piven, Joseph

2007-01-01

Objective: To provide an overview of diffusion tensor imaging (DTI) and its application to the study of white matter in the developing brain in both healthy and clinical samples. Method: The development of DTI and its application to brain imaging of white matter tracts is discussed. Forty-eight studies using DTI to examine diffusion properties of…

Neuroimaging of the Injured Pediatric Brain: Methods and New Lessons.

Science.gov (United States)

Dennis, Emily L; Babikian, Talin; Giza, Christopher C; Thompson, Paul M; Asarnow, Robert F

2018-02-01

Traumatic brain injury (TBI) is a significant public health problem in the United States, especially for children and adolescents. Current epidemiological data estimate over 600,000 patients younger than 20 years are treated for TBI in emergency rooms annually. While many patients experience a full recovery, for others there can be long-lasting cognitive, neurological, psychological, and behavioral disruptions. TBI in youth can disrupt ongoing brain development and create added family stress during a formative period. The neuroimaging methods used to assess brain injury improve each year, providing researchers a more detailed characterization of the injury and recovery process. In this review, we cover current imaging methods used to quantify brain disruption post-injury, including structural magnetic resonance imaging (MRI), diffusion MRI, functional MRI, resting state fMRI, and magnetic resonance spectroscopy (MRS), with brief coverage of other methods, including electroencephalography (EEG), single-photon emission computed tomography (SPECT), and positron emission tomography (PET). We include studies focusing on pediatric moderate-severe TBI from 2 months post-injury and beyond. While the morbidity of pediatric TBI is considerable, continuing advances in imaging methods have the potential to identify new treatment targets that can lead to significant improvements in outcome.

The brain, a choice subject for radioisotopic functional imaging

International Nuclear Information System (INIS)

Maziere, B.

1996-01-01

Progresses realized in the use of radioisotopes and in tomographic imaging techniques have permitted to access to the visualization of the human body functions. The application of this radioisotopic functional imaging (or emission tomography functional imaging) has been particularly fruitful in the study of brain functioning. This method is the only exploratory method for the biochemical aspects of the cerebral functioning and is used both by the physiologist and the therapist. (J.S.)

PET imaging for brain function

International Nuclear Information System (INIS)

Fukuda, Hiroshi

2003-01-01

Described are the principle of PET and its characteristics, imaging of human brain function, mapping of detailed human cerebral functions and PET imaging of nerve transmission. Following compounds labeled by positron emitters are used for PET imaging of brain functions: for blood flow and oxygen metabolism, 15 O-O 2 gas, water and carbon dioxide; for energy metabolism, 18 F-fluorodeoxyglucose; and for nerve transmission functions in receptor binding, transporter, transmitter synthesis and enzyme, 11 C- or 18 F-dopamine, serotonin and their analogues, and acetylcholine analogues. For brain mapping, examples of cognition tasks, results and their statistics are presented with images for blood flow. Nerve transmissions in schizophrenia and Alzheimer disease are imaged with labeled analogues of dopamine and acetylcholine, respectively. PET is becoming more and more important in the field of psychiatric science particularly in the coming society of increasing aged people. (N.I.)

Colorization and automated segmentation of human T2 MR brain images for characterization of soft tissues.

Directory of Open Access Journals (Sweden)

Muhammad Attique

Full Text Available Characterization of tissues like brain by using magnetic resonance (MR images and colorization of the gray scale image has been reported in the literature, along with the advantages and drawbacks. Here, we present two independent methods; (i a novel colorization method to underscore the variability in brain MR images, indicative of the underlying physical density of bio tissue, (ii a segmentation method (both hard and soft segmentation to characterize gray brain MR images. The segmented images are then transformed into color using the above-mentioned colorization method, yielding promising results for manual tracing. Our color transformation incorporates the voxel classification by matching the luminance of voxels of the source MR image and provided color image by measuring the distance between them. The segmentation method is based on single-phase clustering for 2D and 3D image segmentation with a new auto centroid selection method, which divides the image into three distinct regions (gray matter (GM, white matter (WM, and cerebrospinal fluid (CSF using prior anatomical knowledge. Results have been successfully validated on human T2-weighted (T2 brain MR images. The proposed method can be potentially applied to gray-scale images from other imaging modalities, in bringing out additional diagnostic tissue information contained in the colorized image processing approach as described.

Multimodal Imaging Brain Connectivity Analysis (MIBCA toolbox

Directory of Open Access Journals (Sweden)

Andre Santos Ribeiro

2015-07-01

Full Text Available Aim. In recent years, connectivity studies using neuroimaging data have increased the understanding of the organization of large-scale structural and functional brain networks. However, data analysis is time consuming as rigorous procedures must be assured, from structuring data and pre-processing to modality specific data procedures. Until now, no single toolbox was able to perform such investigations on truly multimodal image data from beginning to end, including the combination of different connectivity analyses. Thus, we have developed the Multimodal Imaging Brain Connectivity Analysis (MIBCA toolbox with the goal of diminishing time waste in data processing and to allow an innovative and comprehensive approach to brain connectivity.Materials and Methods. The MIBCA toolbox is a fully automated all-in-one connectivity toolbox that offers pre-processing, connectivity and graph theoretical analyses of multimodal image data such as diffusion-weighted imaging, functional magnetic resonance imaging (fMRI and positron emission tomography (PET. It was developed in MATLAB environment and pipelines well-known neuroimaging softwares such as Freesurfer, SPM, FSL, and Diffusion Toolkit. It further implements routines for the construction of structural, functional and effective or combined connectivity matrices, as well as, routines for the extraction and calculation of imaging and graph-theory metrics, the latter using also functions from the Brain Connectivity Toolbox. Finally, the toolbox performs group statistical analysis and enables data visualization in the form of matrices, 3D brain graphs and connectograms. In this paper the MIBCA toolbox is presented by illustrating its capabilities using multimodal image data from a group of 35 healthy subjects (19–73 years old with volumetric T1-weighted, diffusion tensor imaging, and resting state fMRI data, and 10 subjets with 18F-Altanserin PET data also.Results. It was observed both a high inter

Medical Imaging and the Human Brain: Being Warped is Not Always a Bad Thing

International Nuclear Information System (INIS)

Patterson, James C. II

2005-01-01

The capacity to look inside the living human brain and image its function has been present since the early 1980s. There are some clinicians who use functional brain imaging for diagnostic or prognostic purposes, but much of the work done still relates to research evaluation of brain function. There is a striking dichotomy in the use of functional brain imaging between these two fields. Clinical evaluation of a brain PET or SPECT scan is subjective; that is, a Nuclear Medicine physician examines the brain image, and states whether the brain image looks normal or abnormal. On the other hand, modern research evaluation of functional brain images is almost always objective. Brain images are processed and analyzed with advanced software tools, and a mathematical result that relates to regional changes in brain activity is provided. The potential for this research methodology to provide a more accurate and reliable answer to clinical questions about brain function and pathology are immense, but there are still obstacles to overcome. Foremost in this regard is the use of a standardized normal control database for comparison of patient scan data. The tools and methods used in objective analysis of functional imaging data, as well as potential clinical applications will be the focus of my presentation

Pathological Brain Detection by a Novel Image Feature—Fractional Fourier Entropy

Directory of Open Access Journals (Sweden)

Shuihua Wang

2015-12-01

Full Text Available Aim: To detect pathological brain conditions early is a core procedure for patients so as to have enough time for treatment. Traditional manual detection is either cumbersome, or expensive, or time-consuming. We aim to offer a system that can automatically identify pathological brain images in this paper. Method: We propose a novel image feature, viz., Fractional Fourier Entropy (FRFE, which is based on the combination of Fractional Fourier Transform (FRFT and Shannon entropy. Afterwards, the Welch’s t-test (WTT and Mahalanobis distance (MD were harnessed to select distinguishing features. Finally, we introduced an advanced classifier: twin support vector machine (TSVM. Results: A 10 × K-fold stratified cross validation test showed that this proposed “FRFE + WTT + TSVM” yielded an accuracy of 100.00%, 100.00%, and 99.57% on datasets that contained 66, 160, and 255 brain images, respectively. Conclusions: The proposed “FRFE + WTT + TSVM” method is superior to 20 state-of-the-art methods.

Appearance of normal brain maturation on 1.5-T MR images

International Nuclear Information System (INIS)

Barkovich, A.J.; Kjos, B.; Jackson, D.E. Jr.; Norman, D.

1987-01-01

To investigate the pattern of normal white-matter maturation as demonstrated by high-field-strength MR imaging, 82 normal infants were examined using a 1.5-T unit with spin-echo T1-weighted and T2-weighted pulse sequences. The infants ranged in age from 4 days to 2 years. The scans were assessed for qualitative changes of white matter relative to gray matter and correlated with the patient's age in 14 anatomic areas of the brain. The MR images showed that changes of brain maturation occur in an orderly manner, commencing in the brain stem and progressing to the cerebellum and the cerebrum. Changes from brain myelination were seen earlier on T1-weighted images than on T2-weighted images, possibly because of T1 shortening by the components of the developing myelin sheaths. The later changes on the T2-weighted images correlated best with the development of myelination, as demonstrated by histochemical methods. T1-weighted images were most useful to monitor normal brain development in the first 6 to 8 months of life; T2-weighted images were more useful after 6 months. The milestones in the MR appearance of normal maturation of the brain are presented. The milestones in the MR appearance of normal maturation of the brain are presented. Persistent areas of long T2 relaxation times are seen superior and dorsal to the ventricular trigone in all infants examined and should not be mistaken for ischemic change

Advantages in functional imaging of the brain.

Science.gov (United States)

Mier, Walter; Mier, Daniela

2015-01-01

As neuronal pathologies cause only minor morphological alterations, molecular imaging techniques are a prerequisite for the study of diseases of the brain. The development of molecular probes that specifically bind biochemical markers and the advances of instrumentation have revolutionized the possibilities to gain insight into the human brain organization and beyond this-visualize structure-function and brain-behavior relationships. The review describes the development and current applications of functional brain imaging techniques with a focus on applications in psychiatry. A historical overview of the development of functional imaging is followed by the portrayal of the principles and applications of positron emission tomography (PET) and functional magnetic resonance imaging (fMRI), two key molecular imaging techniques that have revolutionized the ability to image molecular processes in the brain. We conclude that the juxtaposition of PET and fMRI in hybrid PET/MRI scanners enhances the significance of both modalities for research in neurology and psychiatry and might pave the way for a new area of personalized medicine.

Auto-Context Convolutional Neural Network (Auto-Net) for Brain Extraction in Magnetic Resonance Imaging.

Science.gov (United States)

Mohseni Salehi, Seyed Sadegh; Erdogmus, Deniz; Gholipour, Ali

2017-11-01

resonance imaging (MRI) data sets. In this application, our voxelwise auto-context CNN performed much better than the other methods (Dice coefficient: 95.97%), where the other methods performed poorly due to the non-standard orientation and geometry of the fetal brain in MRI. Through training, our method can provide accurate brain extraction in challenging applications. This, in turn, may reduce the problems associated with image registration in segmentation tasks.

MEG source imaging method using fast L1 minimum-norm and its applications to signals with brain noise and human resting-state source amplitude images.

Science.gov (United States)

Huang, Ming-Xiong; Huang, Charles W; Robb, Ashley; Angeles, AnneMarie; Nichols, Sharon L; Baker, Dewleen G; Song, Tao; Harrington, Deborah L; Theilmann, Rebecca J; Srinivasan, Ramesh; Heister, David; Diwakar, Mithun; Canive, Jose M; Edgar, J Christopher; Chen, Yu-Han; Ji, Zhengwei; Shen, Max; El-Gabalawy, Fady; Levy, Michael; McLay, Robert; Webb-Murphy, Jennifer; Liu, Thomas T; Drake, Angela; Lee, Roland R

2014-01-01

The present study developed a fast MEG source imaging technique based on Fast Vector-based Spatio-Temporal Analysis using a L1-minimum-norm (Fast-VESTAL) and then used the method to obtain the source amplitude images of resting-state magnetoencephalography (MEG) signals for different frequency bands. The Fast-VESTAL technique consists of two steps. First, L1-minimum-norm MEG source images were obtained for the dominant spatial modes of sensor-waveform covariance matrix. Next, accurate source time-courses with millisecond temporal resolution were obtained using an inverse operator constructed from the spatial source images of Step 1. Using simulations, Fast-VESTAL's performance was assessed for its 1) ability to localize multiple correlated sources; 2) ability to faithfully recover source time-courses; 3) robustness to different SNR conditions including SNR with negative dB levels; 4) capability to handle correlated brain noise; and 5) statistical maps of MEG source images. An objective pre-whitening method was also developed and integrated with Fast-VESTAL to remove correlated brain noise. Fast-VESTAL's performance was then examined in the analysis of human median-nerve MEG responses. The results demonstrated that this method easily distinguished sources in the entire somatosensory network. Next, Fast-VESTAL was applied to obtain the first whole-head MEG source-amplitude images from resting-state signals in 41 healthy control subjects, for all standard frequency bands. Comparisons between resting-state MEG sources images and known neurophysiology were provided. Additionally, in simulations and cases with MEG human responses, the results obtained from using conventional beamformer technique were compared with those from Fast-VESTAL, which highlighted the beamformer's problems of signal leaking and distorted source time-courses. © 2013.

4D segmentation of brain MR images with constrained cortical thickness variation.

Directory of Open Access Journals (Sweden)

Li Wang

Full Text Available Segmentation of brain MR images plays an important role in longitudinal investigation of developmental, aging, disease progression changes in the cerebral cortex. However, most existing brain segmentation methods consider multiple time-point images individually and thus cannot achieve longitudinal consistency. For example, cortical thickness measured from the segmented image will contain unnecessary temporal variations, which will affect the time related change pattern and eventually reduce the statistical power of analysis. In this paper, we propose a 4D segmentation framework for the adult brain MR images with the constraint of cortical thickness variations. Specifically, we utilize local intensity information to address the intensity inhomogeneity, spatial cortical thickness constraint to maintain the cortical thickness being within a reasonable range, and temporal cortical thickness variation constraint in neighboring time-points to suppress the artificial variations. The proposed method has been tested on BLSA dataset and ADNI dataset with promising results. Both qualitative and quantitative experimental results demonstrate the advantage of the proposed method, in comparison to other state-of-the-art 4D segmentation methods.

Geometry Processing of Conventionally Produced Mouse Brain Slice Images.

Science.gov (United States)

Agarwal, Nitin; Xu, Xiangmin; Gopi, M

2018-04-21

Brain mapping research in most neuroanatomical laboratories relies on conventional processing techniques, which often introduce histological artifacts such as tissue tears and tissue loss. In this paper we present techniques and algorithms for automatic registration and 3D reconstruction of conventionally produced mouse brain slices in a standardized atlas space. This is achieved first by constructing a virtual 3D mouse brain model from annotated slices of Allen Reference Atlas (ARA). Virtual re-slicing of the reconstructed model generates ARA-based slice images corresponding to the microscopic images of histological brain sections. These image pairs are aligned using a geometric approach through contour images. Histological artifacts in the microscopic images are detected and removed using Constrained Delaunay Triangulation before performing global alignment. Finally, non-linear registration is performed by solving Laplace's equation with Dirichlet boundary conditions. Our methods provide significant improvements over previously reported registration techniques for the tested slices in 3D space, especially on slices with significant histological artifacts. Further, as one of the application we count the number of neurons in various anatomical regions using a dataset of 51 microscopic slices from a single mouse brain. To the best of our knowledge the presented work is the first that automatically registers both clean as well as highly damaged high-resolutions histological slices of mouse brain to a 3D annotated reference atlas space. This work represents a significant contribution to this subfield of neuroscience as it provides tools to neuroanatomist for analyzing and processing histological data. Copyright © 2018 Elsevier B.V. All rights reserved.

A novel algorithm for segmentation of brain MR images

International Nuclear Information System (INIS)

Sial, M.Y.; Yu, L.; Chowdhry, B.S.; Rajput, A.Q.K.; Bhatti, M.I.

2006-01-01

Accurate and fully automatic segmentation of brain from magnetic resonance (MR) scans is a challenging problem that has received an enormous amount of . attention lately. Many researchers have applied various techniques however a standard fuzzy c-means algorithm has produced better results compared to other methods. In this paper, we present a modified fuzzy c-means (FCM) based algorithm for segmentation of brain MR images. Our algorithm is formulated by modifying the objective function of the standard FCM and uses a special spread method to get a smooth and slow varying bias field This method has the advantage that it can be applied at an early stage in an automated data analysis before a tissue model is available. The results on MRI images show that this method provides better results compared to standard FCM algorithms. (author)

Quantifying structural alterations in Alzheimer's disease brains using quantitative phase imaging (Conference Presentation)

Science.gov (United States)

Lee, Moosung; Lee, Eeksung; Jung, JaeHwang; Yu, Hyeonseung; Kim, Kyoohyun; Yoon, Jonghee; Lee, Shinhwa; Jeong, Yong; Park, YongKeun

2017-02-01

Imaging brain tissues is an essential part of neuroscience because understanding brain structure provides relevant information about brain functions and alterations associated with diseases. Magnetic resonance imaging and positron emission tomography exemplify conventional brain imaging tools, but these techniques suffer from low spatial resolution around 100 μm. As a complementary method, histopathology has been utilized with the development of optical microscopy. The traditional method provides the structural information about biological tissues to cellular scales, but relies on labor-intensive staining procedures. With the advances of illumination sources, label-free imaging techniques based on nonlinear interactions, such as multiphoton excitations and Raman scattering, have been applied to molecule-specific histopathology. Nevertheless, these techniques provide limited qualitative information and require a pulsed laser, which is difficult to use for pathologists with no laser training. Here, we present a label-free optical imaging of mouse brain tissues for addressing structural alteration in Alzheimer's disease. To achieve the mesoscopic, unlabeled tissue images with high contrast and sub-micrometer lateral resolution, we employed holographic microscopy and an automated scanning platform. From the acquired hologram of the brain tissues, we could retrieve scattering coefficients and anisotropies according to the modified scattering-phase theorem. This label-free imaging technique enabled direct access to structural information throughout the tissues with a sub-micrometer lateral resolution and presented a unique means to investigate the structural changes in the optical properties of biological tissues.

Content-based image retrieval using spatial layout information in brain tumor T1-weighted contrast-enhanced MR images.

Science.gov (United States)

Huang, Meiyan; Yang, Wei; Wu, Yao; Jiang, Jun; Gao, Yang; Chen, Yang; Feng, Qianjin; Chen, Wufan; Lu, Zhentai

2014-01-01

This study aims to develop content-based image retrieval (CBIR) system for the retrieval of T1-weighted contrast-enhanced MR (CE-MR) images of brain tumors. When a tumor region is fed to the CBIR system as a query, the system attempts to retrieve tumors of the same pathological category. The bag-of-visual-words (BoVW) model with partition learning is incorporated into the system to extract informative features for representing the image contents. Furthermore, a distance metric learning algorithm called the Rank Error-based Metric Learning (REML) is proposed to reduce the semantic gap between low-level visual features and high-level semantic concepts. The effectiveness of the proposed method is evaluated on a brain T1-weighted CE-MR dataset with three types of brain tumors (i.e., meningioma, glioma, and pituitary tumor). Using the BoVW model with partition learning, the mean average precision (mAP) of retrieval increases beyond 4.6% with the learned distance metrics compared with the spatial pyramid BoVW method. The distance metric learned by REML significantly outperforms three other existing distance metric learning methods in terms of mAP. The mAP of the CBIR system is as high as 91.8% using the proposed method, and the precision can reach 93.1% when the top 10 images are returned by the system. These preliminary results demonstrate that the proposed method is effective and feasible for the retrieval of brain tumors in T1-weighted CE-MR Images.

Content-based image retrieval using spatial layout information in brain tumor T1-weighted contrast-enhanced MR images.

Directory of Open Access Journals (Sweden)

Meiyan Huang

Full Text Available This study aims to develop content-based image retrieval (CBIR system for the retrieval of T1-weighted contrast-enhanced MR (CE-MR images of brain tumors. When a tumor region is fed to the CBIR system as a query, the system attempts to retrieve tumors of the same pathological category. The bag-of-visual-words (BoVW model with partition learning is incorporated into the system to extract informative features for representing the image contents. Furthermore, a distance metric learning algorithm called the Rank Error-based Metric Learning (REML is proposed to reduce the semantic gap between low-level visual features and high-level semantic concepts. The effectiveness of the proposed method is evaluated on a brain T1-weighted CE-MR dataset with three types of brain tumors (i.e., meningioma, glioma, and pituitary tumor. Using the BoVW model with partition learning, the mean average precision (mAP of retrieval increases beyond 4.6% with the learned distance metrics compared with the spatial pyramid BoVW method. The distance metric learned by REML significantly outperforms three other existing distance metric learning methods in terms of mAP. The mAP of the CBIR system is as high as 91.8% using the proposed method, and the precision can reach 93.1% when the top 10 images are returned by the system. These preliminary results demonstrate that the proposed method is effective and feasible for the retrieval of brain tumors in T1-weighted CE-MR Images.

Automated, non-linear registration between 3-dimensional brain map and medical head image

International Nuclear Information System (INIS)

Mizuta, Shinobu; Urayama, Shin-ichi; Zoroofi, R.A.; Uyama, Chikao

1998-01-01

In this paper, we propose an automated, non-linear registration method between 3-dimensional medical head image and brain map in order to efficiently extract the regions of interest. In our method, input 3-dimensional image is registered into a reference image extracted from a brain map. The problems to be solved are automated, non-linear image matching procedure, and cost function which represents the similarity between two images. Non-linear matching is carried out by dividing the input image into connected partial regions, transforming the partial regions preserving connectivity among the adjacent images, evaluating the image similarity between the transformed regions of the input image and the correspondent regions of the reference image, and iteratively searching the optimal transformation of the partial regions. In order to measure the voxelwise similarity of multi-modal images, a cost function is introduced, which is based on the mutual information. Some experiments using MR images presented the effectiveness of the proposed method. (author)

Brain morphology imaging by 3D microscopy and fluorescent Nissl staining.

Science.gov (United States)

Lazutkin, A A; Komissarova, N V; Toptunov, D M; Anokhin, K V

2013-07-01

Modern optical methods (multiphoton and light-sheet fluorescent microscopy) allow 3D imaging of large specimens of the brain with cell resolution. It is therefore essential to refer the resultant 3D pictures of expression of transgene, protein, and other markers in the brain to the corresponding structures in the atlas. This implies counterstaining of specimens with morphological dyes. However, there are no methods for contrasting large samples of the brain without their preliminary slicing. We have developed a method for fluorescent Nissl staining of whole brain samples. 3D reconstructions of specimens of the hippocampus, olfactory bulbs, and cortex were created. The method can be used for morphological control and evaluation of the effects of various factors on the brain using 3D microscopy technique.

Brain Image Motion Correction

DEFF Research Database (Denmark)

Jensen, Rasmus Ramsbøl; Benjaminsen, Claus; Larsen, Rasmus

2015-01-01

The application of motion tracking is wide, including: industrial production lines, motion interaction in gaming, computer-aided surgery and motion correction in medical brain imaging. Several devices for motion tracking exist using a variety of different methodologies. In order to use such devices...... offset and tracking noise in medical brain imaging. The data are generated from a phantom mounted on a rotary stage and have been collected using a Siemens High Resolution Research Tomograph for positron emission tomography. During acquisition the phantom was tracked with our latest tracking prototype...

Structural imaging of mild traumatic brain injury may not be enough: overview of functional and metabolic imaging of mild traumatic brain injury.

Science.gov (United States)

Shin, Samuel S; Bales, James W; Edward Dixon, C; Hwang, Misun

2017-04-01

A majority of patients with traumatic brain injury (TBI) present as mild injury with no findings on conventional clinical imaging methods. Due to this difficulty of imaging assessment on mild TBI patients, there has been much emphasis on the development of diffusion imaging modalities such as diffusion tensor imaging (DTI). However, basic science research in TBI shows that many of the functional and metabolic abnormalities in TBI may be present even in the absence of structural damage. Moreover, structural damage may be present at a microscopic and molecular level that is not detectable by structural imaging modality. The use of functional and metabolic imaging modalities can provide information on pathological changes in mild TBI patients that may not be detected by structural imaging. Although there are various differences in protocols of positron emission tomography (PET), single photon emission computed tomography (SPECT), functional magnetic resonance imaging (fMRI), electroencephalography (EEG), and magnetoencephalography (MEG) methods, these may be important modalities to be used in conjunction with structural imaging in the future in order to detect and understand the pathophysiology of mild TBI. In this review, studies of mild TBI patients using these modalities that detect functional and metabolic state of the brain are discussed. Each modality's advantages and disadvantages are compared, and potential future applications of using combined modalities are explored.

Imaging of brain function based on the analysis of functional ...

African Journals Online (AJOL)

Objective: This Study observed the relevant brain areas activated by acupuncture at the Taichong acupoint (LR3) and analyzed the functional connectivity among brain areas using resting state functional magnetic resonance imaging (fMRI) to explore the acupoint specificity of the Taichong acupoint. Methods: A total of 45 ...

Diffuse optical systems and methods to image physiological changes of the brain in response to focal TBI (Conference Presentation)

Science.gov (United States)

Abookasis, David; Volkov, Boris; Kofman, Itamar

2017-02-01

During the last four decades, various optical techniques have been proposed and intensively used for biomedical diagnosis and therapy both in animal model and in human. These techniques have several advantages over the traditional existing methods: simplicity in structure, low-cost, easy to handle, portable, can be used repeatedly over time near the patient bedside for continues monitoring, and offer high spatiotemporal resolution. In this work, we demonstrate the use of two optical imaging modalities namely, spatially modulated illumination and dual-wavelength laser speckle to image the changes in brain tissue chromophores, morphology, and metabolic before, during, and after the onset of focal traumatic brain injury in intact mouse head (n=15). Injury was applied in anesthetized mice by weight-drop apparatus using 50gram metal rod striking the mouse's head. Following data analysis, we show a series of hemodynamic and structural changes over time including higher deoxyhemoglobin, reduction in oxygen saturation and blood flow, cell swelling, etc., in comparison with baseline measurements. In addition, to validate the monitoring of cerebral blood flow by the imaging system, measurements with laser Doppler flowmetry were also performed (n=5), which confirmed reduction in blood flow following injury. Overall, our result demonstrates the capability of diffuse optical modalities to monitor and map brain tissue optical and physiological properties following brain trauma.

Brain MR image segmentation based on an improved active contour model.

Directory of Open Access Journals (Sweden)

Xiangrui Meng

Full Text Available It is often a difficult task to accurately segment brain magnetic resonance (MR images with intensity in-homogeneity and noise. This paper introduces a novel level set method for simultaneous brain MR image segmentation and intensity inhomogeneity correction. To reduce the effect of noise, novel anisotropic spatial information, which can preserve more details of edges and corners, is proposed by incorporating the inner relationships among the neighbor pixels. Then the proposed energy function uses the multivariate Student's t-distribution to fit the distribution of the intensities of each tissue. Furthermore, the proposed model utilizes Hidden Markov random fields to model the spatial correlation between neigh-boring pixels/voxels. The means of the multivariate Student's t-distribution can be adaptively estimated by multiplying a bias field to reduce the effect of intensity inhomogeneity. In the end, we reconstructed the energy function to be convex and calculated it by using the Split Bregman method, which allows our framework for random initialization, thereby allowing fully automated applications. Our method can obtain the final result in less than 1 second for 2D image with size 256 × 256 and less than 300 seconds for 3D image with size 256 × 256 × 171. The proposed method was compared to other state-of-the-art segmentation methods using both synthetic and clinical brain MR images and increased the accuracies of the results more than 3%.

Towards real-time diffuse optical tomography for imaging brain functions cooperated with Kalman estimator

Science.gov (United States)

Wang, Bingyuan; Zhang, Yao; Liu, Dongyuan; Ding, Xuemei; Dan, Mai; Pan, Tiantian; Wang, Yihan; Li, Jiao; Zhou, Zhongxing; Zhang, Limin; Zhao, Huijuan; Gao, Feng

2018-02-01

Functional near-infrared spectroscopy (fNIRS) is a non-invasive neuroimaging method to monitor the cerebral hemodynamic through the optical changes measured at the scalp surface. It has played a more and more important role in psychology and medical imaging communities. Real-time imaging of brain function using NIRS makes it possible to explore some sophisticated human brain functions unexplored before. Kalman estimator has been frequently used in combination with modified Beer-Lamber Law (MBLL) based optical topology (OT), for real-time brain function imaging. However, the spatial resolution of the OT is low, hampering the application of OT in exploring some complicated brain functions. In this paper, we develop a real-time imaging method combining diffuse optical tomography (DOT) and Kalman estimator, much improving the spatial resolution. Instead of only presenting one spatially distributed image indicating the changes of the absorption coefficients at each time point during the recording process, one real-time updated image using the Kalman estimator is provided. Its each voxel represents the amplitude of the hemodynamic response function (HRF) associated with this voxel. We evaluate this method using some simulation experiments, demonstrating that this method can obtain more reliable spatial resolution images. Furthermore, a statistical analysis is also conducted to help to decide whether a voxel in the field of view is activated or not.

Optimising imaging parameters for post mortem MR imaging of the human brain

Energy Technology Data Exchange (ETDEWEB)

Blamire, A.M.; Rowe, J.G.; Styles, P. [MRC Magnetic Resonance Spectroscopy Unit, Dept. of Biochemistry, Univ. of Oxford (United Kingdom); McDonald, B. [MRC Schizophrenia Research Group, Dept. of Neuropathology, Radcliffe Infirmary, Oxford (United Kingdom)

1999-11-01

Purpose: MR imaging of post mortem brains has the potential to yield volumetric information and define the extent of structural changes prior to pathological examination. Although standard T2-weighted clinical imaging sequences have been used for the examination of formalin-fixed brains, these protocols may not yield optimum contrast. We examined the effect of varying durations of formalin fixation on the transverse relaxation time (T2) and the tissue spin density. Material and Methods: Three post mortem brains were examined weekly during formalin fixation from the unfixed state to 35 days fixation. Standard MR spin-echo imaging was used at 5 echo times (20-100 ms) to calculate transverse relaxation time (T2) and spin density. Results: T2 decreased significantly (ANOVA, p<0.001) in both grey and white matter by 7 days fixation and there was a further (but non-significant) trend towards lower values between7 and 35 days. Grey and white matter T2 times converged with fixation. Conversely, the grey to white matter spin density ratio increased from 1.19{+-}0.01 to 1.54{+-}0.06 over five weeks of fixation. Conclusion: Our results suggest that spin density-weighted imaging sequences would provide improved grey to white matter contrast over T2-weighted sequences. (orig.)

MRI Brain Tumor Segmentation Methods- A Review

OpenAIRE

Gursangeet, Kaur; Jyoti, Rani

2016-01-01

Medical image processing and its segmentation is an active and interesting area for researchers. It has reached at the tremendous place in diagnosing tumors after the discovery of CT and MRI. MRI is an useful tool to detect the brain tumor and segmentation is performed to carry out the useful portion from an image. The purpose of this paper is to provide an overview of different image segmentation methods like watershed algorithm, morphological operations, neutrosophic sets, thresholding, K-...

Brain MR imaging in dietarily treated phenylketonuria

Energy Technology Data Exchange (ETDEWEB)

Breysem, L. [Dept. of Radiology, University Hospitals, Leuven (Belgium); Smet, M.H. [Dept. of Radiology, University Hospitals, Leuven (Belgium); Johannik, K. [Dept. of Radiology, University Hospitals, Leuven (Belgium); Hecke, P. van [Dept. of Radiology, University Hospitals, Leuven (Belgium); Francois, B. [L. Willems Inst., Diepenbeek (Belgium); Wilms, G. [Dept. of Radiology, University Hospitals, Leuven (Belgium); Bosmans, H. [Dept. of Radiology, University Hospitals, Leuven (Belgium); Marchal, G. [Dept. of Radiology, University Hospitals, Leuven (Belgium); Jaeken, J. [Dept. of Pediatrics, University Hospitals, Leuven (Belgium); Demaerel, P. [Dept. of Radiology, University Hospitals, Leuven (Belgium)

1994-08-01

Magnetic resonance imaging is the most efficient imaging modality to evaluate brain gray and white matter of patients with metabolic diseases. The main purpose of our study was to investigate the relation between brain MRI abnormalities and the phenylalanine (phe) and tyrosine (tyr) blood levels in 38 phenylketonuria (PKU) patients. Increased periventricular white matter intensity on T2-weighted brain images was the only pathologic finding in 24 patients. Brain MRI abnormalities were scored (4) and correlated with the individual mean phe and phe/tyr levels during 1 year preceding MR examination and with phe tolerance. The residual activity of phenylalanine hydroxylase was defined for each patient by an oral phe tolerance. The appearance of MRI abnormalities on brain T2-weighted images correlates with a threshold mean phe level (averaged over the year preceding the examination). (orig.)

Brain MR imaging in dietarily treated phenylketonuria

International Nuclear Information System (INIS)

Breysem, L.; Smet, M.H.; Johannik, K.; Hecke, P. van; Francois, B.; Wilms, G.; Bosmans, H.; Marchal, G.; Jaeken, J.; Demaerel, P.

1994-01-01

Magnetic resonance imaging is the most efficient imaging modality to evaluate brain gray and white matter of patients with metabolic diseases. The main purpose of our study was to investigate the relation between brain MRI abnormalities and the phenylalanine (phe) and tyrosine (tyr) blood levels in 38 phenylketonuria (PKU) patients. Increased periventricular white matter intensity on T2-weighted brain images was the only pathologic finding in 24 patients. Brain MRI abnormalities were scored (4) and correlated with the individual mean phe and phe/tyr levels during 1 year preceding MR examination and with phe tolerance. The residual activity of phenylalanine hydroxylase was defined for each patient by an oral phe tolerance. The appearance of MRI abnormalities on brain T2-weighted images correlates with a threshold mean phe level (averaged over the year preceding the examination). (orig.)

Spatial Mapping of Structural and Connectional Imaging Data for the Developing Human Brain with Diffusion Tensor Imaging

Science.gov (United States)

Ouyang, Austin; Jeon, Tina; Sunkin, Susan M.; Pletikos, Mihovil; Sedmak, Goran; Sestan, Nenad; Lein, Ed S.; Huang, Hao

2014-01-01

During human brain development from fetal stage to adulthood, the white matter (WM) tracts undergo dramatic changes. Diffusion tensor imaging (DTI), a widely used magnetic resonance imaging (MRI) modality, offers insight into the dynamic changes of WM fibers as these fibers can be noninvasively traced and three-dimensionally (3D) reconstructed with DTI tractography. The DTI and conventional T1 weighted MRI images also provide sufficient cortical anatomical details for mapping the cortical regions of interests (ROIs). In this paper, we described basic concepts and methods of DTI techniques that can be used to trace major WM tracts noninvasively from fetal brain of 14 postconceptional weeks (pcw) to adult brain. We applied these techniques to acquire DTI data and trace, reconstruct and visualize major WM tracts during development. After categorizing major WM fiber bundles into five unique functional tract groups, namely limbic, brain stem, projection, commissural and association tracts, we revealed formation and maturation of these 3D reconstructed WM tracts of the developing human brain. The structural and connectional imaging data offered by DTI provides the anatomical backbone of transcriptional atlas of the developing human brain. PMID:25448302

Spatial mapping of structural and connectional imaging data for the developing human brain with diffusion tensor imaging.

Science.gov (United States)

Ouyang, Austin; Jeon, Tina; Sunkin, Susan M; Pletikos, Mihovil; Sedmak, Goran; Sestan, Nenad; Lein, Ed S; Huang, Hao

2015-02-01

During human brain development from fetal stage to adulthood, the white matter (WM) tracts undergo dramatic changes. Diffusion tensor imaging (DTI), a widely used magnetic resonance imaging (MRI) modality, offers insight into the dynamic changes of WM fibers as these fibers can be noninvasively traced and three-dimensionally (3D) reconstructed with DTI tractography. The DTI and conventional T1 weighted MRI images also provide sufficient cortical anatomical details for mapping the cortical regions of interests (ROIs). In this paper, we described basic concepts and methods of DTI techniques that can be used to trace major WM tracts noninvasively from fetal brain of 14 postconceptional weeks (pcw) to adult brain. We applied these techniques to acquire DTI data and trace, reconstruct and visualize major WM tracts during development. After categorizing major WM fiber bundles into five unique functional tract groups, namely limbic, brain stem, projection, commissural and association tracts, we revealed formation and maturation of these 3D reconstructed WM tracts of the developing human brain. The structural and connectional imaging data offered by DTI provides the anatomical backbone of transcriptional atlas of the developing human brain. Copyright © 2014 Elsevier Inc. All rights reserved.

Quantification of brain perfusion SPECT with N-isopropyl-p-iodoamphetamine using noninvasive microsphere method. Estimation of arterial input by dynamic imaging

International Nuclear Information System (INIS)

Yonekura, Yoshiharu; Sugihara, Hideki; Taniguchi, Yoshimitsu; Aoki, Etsuo; Furuichi, Kenji; Miyazaki, Yoshiharu.

1997-01-01

We have developed a noninvasive method to quantify brain perfusion SPECT with 123 I-N-isopropyl-p-iodoamphetamine (IMP) using serial dynamic planar imaging of the initial transit phase. The method is based on the microsphere model, but does not require arterial sampling. Serial dynamic planar imaging was performed for 6 min after the bolus injection of IMP (167 MBq in 1.5 ml), followed by additional planar imaging at 20 min and SPECT scan thereafter. The total arterial input to the brain during the initial 5 min after injection was estimated by the injected dose, with the correction of the lung retention, divided by cardiac output (CO). CO was estimated from the initial transit of IMP in the right heart. Cardiac output index (COI), obtained from the integral of the first transit of IMP in the right heart divided by the injected dose, was calibrated by CO measured by Doppler ultrasonography. Regional cerebral blood flow (rCBF) obtained by this method in normal subjects was acceptable. However, the results may be influenced by the injection technique, and careful attention should be considered for clinical application of this method. (author)

Improved frame-based estimation of head motion in PET brain imaging

International Nuclear Information System (INIS)

Mukherjee, J. M.; Lindsay, C.; King, M. A.; Licho, R.; Mukherjee, A.; Olivier, P.; Shao, L.

2016-01-01

Purpose: Head motion during PET brain imaging can cause significant degradation of image quality. Several authors have proposed ways to compensate for PET brain motion to restore image quality and improve quantitation. Head restraints can reduce movement but are unreliable; thus the need for alternative strategies such as data-driven motion estimation or external motion tracking. Herein, the authors present a data-driven motion estimation method using a preprocessing technique that allows the usage of very short duration frames, thus reducing the intraframe motion problem commonly observed in the multiple frame acquisition method. Methods: The list mode data for PET acquisition is uniformly divided into 5-s frames and images are reconstructed without attenuation correction. Interframe motion is estimated using a 3D multiresolution registration algorithm and subsequently compensated for. For this study, the authors used 8 PET brain studies that used F-18 FDG as the tracer and contained minor or no initial motion. After reconstruction and prior to motion estimation, known motion was introduced to each frame to simulate head motion during a PET acquisition. To investigate the trade-off in motion estimation and compensation with respect to frames of different length, the authors summed 5-s frames accordingly to produce 10 and 60 s frames. Summed images generated from the motion-compensated reconstructed frames were then compared to the original PET image reconstruction without motion compensation. Results: The authors found that our method is able to compensate for both gradual and step-like motions using frame times as short as 5 s with a spatial accuracy of 0.2 mm on average. Complex volunteer motion involving all six degrees of freedom was estimated with lower accuracy (0.3 mm on average) than the other types investigated. Preprocessing of 5-s images was necessary for successful image registration. Since their method utilizes nonattenuation corrected frames, it is

Improved frame-based estimation of head motion in PET brain imaging

Energy Technology Data Exchange (ETDEWEB)

Mukherjee, J. M., E-mail: joyeeta.mitra@umassmed.edu; Lindsay, C.; King, M. A.; Licho, R. [Department of Radiology, University of Massachusetts Medical School, Worcester, Massachusetts 01655 (United States); Mukherjee, A. [Aware, Inc., Bedford, Massachusetts 01730 (United States); Olivier, P. [Philips Medical Systems, Cleveland, Ohio 44143 (United States); Shao, L. [ViewRay, Oakwood Village, Ohio 44146 (United States)

2016-05-15

Purpose: Head motion during PET brain imaging can cause significant degradation of image quality. Several authors have proposed ways to compensate for PET brain motion to restore image quality and improve quantitation. Head restraints can reduce movement but are unreliable; thus the need for alternative strategies such as data-driven motion estimation or external motion tracking. Herein, the authors present a data-driven motion estimation method using a preprocessing technique that allows the usage of very short duration frames, thus reducing the intraframe motion problem commonly observed in the multiple frame acquisition method. Methods: The list mode data for PET acquisition is uniformly divided into 5-s frames and images are reconstructed without attenuation correction. Interframe motion is estimated using a 3D multiresolution registration algorithm and subsequently compensated for. For this study, the authors used 8 PET brain studies that used F-18 FDG as the tracer and contained minor or no initial motion. After reconstruction and prior to motion estimation, known motion was introduced to each frame to simulate head motion during a PET acquisition. To investigate the trade-off in motion estimation and compensation with respect to frames of different length, the authors summed 5-s frames accordingly to produce 10 and 60 s frames. Summed images generated from the motion-compensated reconstructed frames were then compared to the original PET image reconstruction without motion compensation. Results: The authors found that our method is able to compensate for both gradual and step-like motions using frame times as short as 5 s with a spatial accuracy of 0.2 mm on average. Complex volunteer motion involving all six degrees of freedom was estimated with lower accuracy (0.3 mm on average) than the other types investigated. Preprocessing of 5-s images was necessary for successful image registration. Since their method utilizes nonattenuation corrected frames, it is

Brain hypoxia imaging

Energy Technology Data Exchange (ETDEWEB)

Song, Ho Chun [Chonnam National University Medical School, Gwangju (Korea, Republic of)

2007-04-15

The measurement of pathologically low levels of tissue pO{sub 2} is an important diagnostic goal for determining the prognosis of many clinically important diseases including cardiovascular insufficiency, stroke and cancer. The target tissues nowadays have mostly been tumors or the myocardium, with less attention centered on the brain. Radiolabelled nitroimidazole or derivatives may be useful in identifying the hypoxic cells in cerebrovascular disease or traumatic brain injury, and hypoxic-ischemic encephalopathy. In acute stroke, the target of therapy is the severely hypoxic but salvageable tissue. {sup 18}F-MISO PET and {sup 99m}Tc-EC-metronidazole SPECT in patients with acute ischemic stroke identified hypoxic tissues and ischemic penumbra, and predicted its outcome. A study using {sup 123}I-IAZA in patient with closed head injury detected the hypoxic tissues after head injury. Up till now these radiopharmaceuticals have drawbacks due to its relatively low concentration with hypoxic tissues associated with/without low blood-brain barrier permeability and the necessity to wait a long time to achieve acceptable target to background ratios for imaging in acute ischemic stroke. It is needed to develop new hypoxic marker exhibiting more rapid localization in the hypoxic region in the brain. And then, the hypoxic brain imaging with imidazoles or non-imidazoles may be very useful in detecting the hypoxic tissues, determining therapeutic strategies and developing therapeutic drugs in several neurological disease, especially, in acute ischemic stroke.

Diffuse Optical Tomography for Brain Imaging: Continuous Wave Instrumentation and Linear Analysis Methods

Science.gov (United States)

Giacometti, Paolo; Diamond, Solomon G.

Diffuse optical tomography (DOT) is a functional brain imaging technique that measures cerebral blood oxygenation and blood volume changes. This technique is particularly useful in human neuroimaging measurements because of the coupling between neural and hemodynamic activity in the brain. DOT is a multichannel imaging extension of near-infrared spectroscopy (NIRS). NIRS uses laser sources and light detectors on the scalp to obtain noninvasive hemodynamic measurements from spectroscopic analysis of the remitted light. This review explains how NIRS data analysis is performed using a combination of the modified Beer-Lambert law (MBLL) and the diffusion approximation to the radiative transport equation (RTE). Laser diodes, photodiode detectors, and optical terminals that contact the scalp are the main components in most NIRS systems. Placing multiple sources and detectors over the surface of the scalp allows for tomographic reconstructions that extend the individual measurements of NIRS into DOT. Mathematically arranging the DOT measurements into a linear system of equations that can be inverted provides a way to obtain tomographic reconstructions of hemodynamics in the brain.

Ribbon scanning confocal for high-speed high-resolution volume imaging of brain.

Directory of Open Access Journals (Sweden)

Alan M Watson

Full Text Available Whole-brain imaging is becoming a fundamental means of experimental insight; however, achieving subcellular resolution imagery in a reasonable time window has not been possible. We describe the first application of multicolor ribbon scanning confocal methods to collect high-resolution volume images of chemically cleared brains. We demonstrate that ribbon scanning collects images over ten times faster than conventional high speed confocal systems but with equivalent spectral and spatial resolution. Further, using this technology, we reconstruct large volumes of mouse brain infected with encephalitic alphaviruses and demonstrate that regions of the brain with abundant viral replication were inaccessible to vascular perfusion. This reveals that the destruction or collapse of large regions of brain micro vasculature may contribute to the severe disease caused by Venezuelan equine encephalitis virus. Visualization of this fundamental impact of infection would not be possible without sampling at subcellular resolution within large brain volumes.

Magnetic Resonance Imaging (MRI): Brain (For Parents)

Science.gov (United States)

... Staying Safe Videos for Educators Search English Español Magnetic Resonance Imaging (MRI): Brain KidsHealth / For Parents / Magnetic Resonance Imaging (MRI): Brain What's in this article? What ...

Synchrotron radiation imaging is a powerful tool to image brain microvasculature

International Nuclear Information System (INIS)

Zhang, Mengqi; Sun, Danni; Xie, Yuanyuan; Xia, Jian; Long, Hongyu; Hu, Kai; Xiao, Bo; Peng, Guanyun

2014-01-01

Synchrotron radiation (SR) imaging is a powerful experimental tool for micrometer-scale imaging of microcirculation in vivo. This review discusses recent methodological advances and findings from morphological investigations of cerebral vascular networks during several neurovascular pathologies. In particular, it describes recent developments in SR microangiography for real-time assessment of the brain microvasculature under various pathological conditions in small animal models. It also covers studies that employed SR-based phase-contrast imaging to acquire 3D brain images and provide detailed maps of brain vasculature. In addition, a brief introduction of SR technology and current limitations of SR sources are described in this review. In the near future, SR imaging could transform into a common and informative imaging modality to resolve subtle details of cerebrovascular function

Synchrotron radiation imaging is a powerful tool to image brain microvasculature

Energy Technology Data Exchange (ETDEWEB)

Zhang, Mengqi; Sun, Danni; Xie, Yuanyuan; Xia, Jian; Long, Hongyu; Hu, Kai; Xiao, Bo, E-mail: csuxiaobo123456@163.com [Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008 (China); Peng, Guanyun [Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800 (China)

2014-03-15

Synchrotron radiation (SR) imaging is a powerful experimental tool for micrometer-scale imaging of microcirculation in vivo. This review discusses recent methodological advances and findings from morphological investigations of cerebral vascular networks during several neurovascular pathologies. In particular, it describes recent developments in SR microangiography for real-time assessment of the brain microvasculature under various pathological conditions in small animal models. It also covers studies that employed SR-based phase-contrast imaging to acquire 3D brain images and provide detailed maps of brain vasculature. In addition, a brief introduction of SR technology and current limitations of SR sources are described in this review. In the near future, SR imaging could transform into a common and informative imaging modality to resolve subtle details of cerebrovascular function.

Segmentation of Brain MRI Using SOM-FCM-Based Method and 3D Statistical Descriptors

Directory of Open Access Journals (Sweden)

Andrés Ortiz

2013-01-01

Full Text Available Current medical imaging systems provide excellent spatial resolution, high tissue contrast, and up to 65535 intensity levels. Thus, image processing techniques which aim to exploit the information contained in the images are necessary for using these images in computer-aided diagnosis (CAD systems. Image segmentation may be defined as the process of parcelling the image to delimit different neuroanatomical tissues present on the brain. In this paper we propose a segmentation technique using 3D statistical features extracted from the volume image. In addition, the presented method is based on unsupervised vector quantization and fuzzy clustering techniques and does not use any a priori information. The resulting fuzzy segmentation method addresses the problem of partial volume effect (PVE and has been assessed using real brain images from the Internet Brain Image Repository (IBSR.

The role of image registration in brain mapping

Science.gov (United States)

Toga, A.W.; Thompson, P.M.

2008-01-01

Image registration is a key step in a great variety of biomedical imaging applications. It provides the ability to geometrically align one dataset with another, and is a prerequisite for all imaging applications that compare datasets across subjects, imaging modalities, or across time. Registration algorithms also enable the pooling and comparison of experimental findings across laboratories, the construction of population-based brain atlases, and the creation of systems to detect group patterns in structural and functional imaging data. We review the major types of registration approaches used in brain imaging today. We focus on their conceptual basis, the underlying mathematics, and their strengths and weaknesses in different contexts. We describe the major goals of registration, including data fusion, quantification of change, automated image segmentation and labeling, shape measurement, and pathology detection. We indicate that registration algorithms have great potential when used in conjunction with a digital brain atlas, which acts as a reference system in which brain images can be compared for statistical analysis. The resulting armory of registration approaches is fundamental to medical image analysis, and in a brain mapping context provides a means to elucidate clinical, demographic, or functional trends in the anatomy or physiology of the brain. PMID:19890483

Brain imaging for oxidative stress and mitochondrial dysfunction in neurodegenerative diseases

International Nuclear Information System (INIS)

Okazawa, H.; Tsujikawa, T.; Kiyono, Y.; Ikawa, M.; Yoneda, M.

2014-01-01

Oxidative stress, one of the most probable molecular mechanisms for neuronal impairment, is reported to occur in the affected brain regions of various neurodegenerative diseases. Recently, many studies showed evidence of a link between oxidative stress or mitochondrial damage and neuronal degeneration. Basic in vitro experiments and postmortem studies demonstrated that biomarkers for oxidative damage can be observed in the pathogenic regions of the brain and the affected neurons. Model animal studies also showed oxidative damage associated with neuronal degeneration. The molecular imaging method with positron emission tomography (PET) is expected to delineate oxidatively stressed microenvironments to elucidate pathophysiological changes of the in vivo brain; however, only a few studies have successfully demonstrated enhanced stress in patients. Radioisotope copper labeled diacetyl-bis(N4-methylthiosemicarbazone) (Cu-ATSM) may be the most promising candidate for this oxidative stress imaging. The tracer is usually known as a hypoxic tissue imaging PET probe, but the accumulation mechanism is based on the electron rich environment induced by mitochondrial impairment and/or microsomal over-reduction, and thus it is considered to represent the oxidative stress state correlated with the degree of disease severity. In this review, Cu-ATSM PET is introduced in detail from the basics to practical methods in clinical studies, as well as recent clinical studies on cerebrovascular diseases and neurodegenerative diseases. Several other PET probes are also introduced from the point of view of neuronal oxidative stress imaging. These molecular imaging methods should be promising tools to reveal oxidative injuries in various brain diseases

Improving Brain Magnetic Resonance Image (MRI Segmentation via a Novel Algorithm based on Genetic and Regional Growth

Directory of Open Access Journals (Sweden)

Javadpour A.

2016-06-01

Full Text Available Background: Regarding the importance of right diagnosis in medical applications, various methods have been exploited for processing medical images solar. The method of segmentation is used to analyze anal to miscall structures in medical imaging. Objective: This study describes a new method for brain Magnetic Resonance Image (MRI segmentation via a novel algorithm based on genetic and regional growth. Methods: Among medical imaging methods, brains MRI segmentation is important due to high contrast of non-intrusive soft tissue and high spatial resolution. Size variations of brain tissues are often accompanied by various diseases such as Alzheimer’s disease. As our knowledge about the relation between various brain diseases and deviation of brain anatomy increases, MRI segmentation is exploited as the first step in early diagnosis. In this paper, regional growth method and auto-mate selection of initial points by genetic algorithm is used to introduce a new method for MRI segmentation. Primary pixels and similarity criterion are automatically by genetic algorithms to maximize the accuracy and validity in image segmentation. Results: By using genetic algorithms and defining the fixed function of image segmentation, the initial points for the algorithm were found. The proposed algorithms are applied to the images and results are manually selected by regional growth in which the initial points were compared. The results showed that the proposed algorithm could reduce segmentation error effectively. Conclusion: The study concluded that the proposed algorithm could reduce segmentation error effectively and help us to diagnose brain diseases.

Parallel imaging: is GRAPPA a useful acquisition tool for MR imaging intended for volumetric brain analysis?

Directory of Open Access Journals (Sweden)

Frank Anders

2009-08-01

Full Text Available Abstract Background The work presented here investigates parallel imaging applied to T1-weighted high resolution imaging for use in longitudinal volumetric clinical studies involving Alzheimer's disease (AD and Mild Cognitive Impairment (MCI patients. This was in an effort to shorten acquisition times to minimise the risk of motion artefacts caused by patient discomfort and disorientation. The principle question is, "Can parallel imaging be used to acquire images at 1.5 T of sufficient quality to allow volumetric analysis of patient brains?" Methods Optimisation studies were performed on a young healthy volunteer and the selected protocol (including the use of two different parallel imaging acceleration factors was then tested on a cohort of 15 elderly volunteers including MCI and AD patients. In addition to automatic brain segmentation, hippocampus volumes were manually outlined and measured in all patients. The 15 patients were scanned on a second occasion approximately one week later using the same protocol and evaluated in the same manner to test repeatability of measurement using images acquired with the GRAPPA parallel imaging technique applied to the MPRAGE sequence. Results Intraclass correlation tests show that almost perfect agreement between repeated measurements of both segmented brain parenchyma fraction and regional measurement of hippocampi. The protocol is suitable for both global and regional volumetric measurement dementia patients. Conclusion In summary, these results indicate that parallel imaging can be used without detrimental effect to brain tissue segmentation and volumetric measurement and should be considered for both clinical and research studies where longitudinal measurements of brain tissue volumes are of interest.

Novel active contour model based on multi-variate local Gaussian distribution for local segmentation of MR brain images

Science.gov (United States)

Zheng, Qiang; Li, Honglun; Fan, Baode; Wu, Shuanhu; Xu, Jindong

2017-12-01

Active contour model (ACM) has been one of the most widely utilized methods in magnetic resonance (MR) brain image segmentation because of its ability of capturing topology changes. However, most of the existing ACMs only consider single-slice information in MR brain image data, i.e., the information used in ACMs based segmentation method is extracted only from one slice of MR brain image, which cannot take full advantage of the adjacent slice images' information, and cannot satisfy the local segmentation of MR brain images. In this paper, a novel ACM is proposed to solve the problem discussed above, which is based on multi-variate local Gaussian distribution and combines the adjacent slice images' information in MR brain image data to satisfy segmentation. The segmentation is finally achieved through maximizing the likelihood estimation. Experiments demonstrate the advantages of the proposed ACM over the single-slice ACM in local segmentation of MR brain image series.

Nuclear magnetic resonance imaging and brain functional exploration

International Nuclear Information System (INIS)

Le Bihan, D.; CEA, 91 - Orsay

1997-01-01

The utilization of nuclear magnetic resonance imaging for functional analysis of the brain is presented: the oxygenated and deoxygenated blood flowing in the brain do not have the same effect on NMR images; the oxygenated blood, related to brain activity, may be detected and the corresponding activity zone in the brain, identified; functional NMR imaging could be used to gain a better understanding of functional troubles linked to neurological or psychiatric diseases

MR imaging of brain surface structures

International Nuclear Information System (INIS)

Katada, Kazuhiro; Anno, Hirofumi; Takesita, Gen; Koga, Sukehiko; Kanno, Tetuo; Sakakibara, Tatuo; Yamada, Kazuhiro; Suzuki, Hirokazu; Saito, Sigeki.

1989-01-01

An imaging technique that permits direct and non-invasive visualization of brain surface structures was proposed. This technique (Surface anatomy scanning, SAS) consists of long TE-long TR spin echo sequence, thick slice and surface coil. Initial clinical trials in 31 patients with various cerebral pathology showed excellent visualization of sulci, gyri and major cortical veins on the lateral surface of the brain together with cortical and subcortical lesions. Our preliminary results indicate that the SAS is an effective method for the diagnosis and localization of cortical and subcortical pathology, and the possible application of SAS to the surgical and the radiation therapy planning is sugessted. (author)

Brain diagnosis with imaging methods: Psychical changes made visible

International Nuclear Information System (INIS)

Anon.

1988-01-01

The First International Symposium on Imaging Methods in Psychiatry, held in May 1988 in Wuerzburg, very impressively has shown that imaging methods are on advance not only in medical diagnostics, but also in psychiatric diagnostics, where they already proved to be a valuable tool. (orig./MG) [de

Enterobacter sakazakii brain abscess in the neonate: the importance of neuroradiologic imaging

International Nuclear Information System (INIS)

Burdette, J.H.; Santos, C.

2000-01-01

Background. Enterobacter sakazakii is a rare but important cause of life-threatening neonatal sepsis and meningitis complicated by the development of brain abscess. Objective. Given the neurotropic qualities of this organism, early diagnosis and treatment are crucial as a poor prognosis follows brain abscess formation. Materials and methods. Cross-sectional imaging (CT and MRI) play an important role in the diagnostic work-up. Conclusion. A biopsy-proven case of E. sakazakii brain abscess, which was diagnosed on MR images, is presented, and the importance of prompt radiologic imaging of the central nervous system in the work-up of patients with this life-threatening disease is discussed. (orig.)

Characterization of a sequential pipeline approach to automatic tissue segmentation from brain MR Images

International Nuclear Information System (INIS)

Hou, Zujun; Huang, Su

2008-01-01

Quantitative analysis of gray matter and white matter in brain magnetic resonance imaging (MRI) is valuable for neuroradiology and clinical practice. Submission of large collections of MRI scans to pipeline processing is increasingly important. We characterized this process and suggest several improvements. To investigate tissue segmentation from brain MR images through a sequential approach, a pipeline that consecutively executes denoising, skull/scalp removal, intensity inhomogeneity correction and intensity-based classification was developed. The denoising phase employs a 3D-extension of the Bayes-Shrink method. The inhomogeneity is corrected by an improvement of the Dawant et al.'s method with automatic generation of reference points. The N3 method has also been evaluated. Subsequently the brain tissue is segmented into cerebrospinal fluid, gray matter and white matter by a generalized Otsu thresholding technique. Intensive comparisons with other sequential or iterative methods have been carried out using simulated and real images. The sequential approach with judicious selection on the algorithm selection in each stage is not only advantageous in speed, but also can attain at least as accurate segmentation as iterative methods under a variety of noise or inhomogeneity levels. A sequential approach to tissue segmentation, which consecutively executes the wavelet shrinkage denoising, scalp/skull removal, inhomogeneity correction and intensity-based classification was developed to automatically segment the brain tissue into CSF, GM and WM from brain MR images. This approach is advantageous in several common applications, compared with other pipeline methods. (orig.)

Bjork-Shiley convexoconcave valves: Susceptibility artifacts at brain MR imaging and mechanical valve fractures

NARCIS (Netherlands)

van Gorp, Maarten J.; van der Graaf, Yolanda; de Mol, Bas A. J. M.; Bakker, Chris J. G.; Witkamp, Theo D.; Ramos, Lino M. P.; Mali, Willem P. T. M.

2004-01-01

PURPOSE: To assess the relationship between heart valve history and susceptibility artifacts at magnetic resonance (MR) imaging of the brain in patients with Bjork-Shiley convexoconcave (BSCC) valves. MATERIALS AND METHODS: MR images of the brain were obtained in 58 patients with prosthetic heart

Imaging brain activity during seizures in freely behaving rats using a miniature multi-modal imaging system.

Science.gov (United States)

Sigal, Iliya; Koletar, Margaret M; Ringuette, Dene; Gad, Raanan; Jeffrey, Melanie; Carlen, Peter L; Stefanovic, Bojana; Levi, Ofer

2016-09-01

We report on a miniature label-free imaging system for monitoring brain blood flow and blood oxygenation changes in awake, freely behaving rats. The device, weighing 15 grams, enables imaging in a ∼ 2 × 2 mm field of view with 4.4 μm lateral resolution and 1 - 8 Hz temporal sampling rate. The imaging is performed through a chronically-implanted cranial window that remains optically clear between 2 to > 6 weeks after the craniotomy. This imaging method is well suited for longitudinal studies of chronic models of brain diseases and disorders. In this work, it is applied to monitoring neurovascular coupling during drug-induced absence-like seizures 6 weeks following the craniotomy.

Clinical application of synthesized brain surface imaging for preoperative simulation of brain biopsy under local anesthesia

International Nuclear Information System (INIS)

Ogura, Yuko; Katada, Kazuhiro; Imai, Fumihiro; Fujisawa, Kazuhisa; Takeshita, Gen; Kanno, Tetsuo; Koga, Sukehiko

1994-01-01

Surface anatomy scanning (SAS) is the technique which permits the direct visualization of brain surface structures, including cortical sulci, guri, subcortical lesions as well as skin markings for craniotomy. A synthesized brain surface image is a technique that combines MR angiography (MRA) with SAS, and it proposed by us for detecting cerebral superficial veins with these surface structures on the same image. The purpose of this report is to present the result of applying the synthesized brain surface image to the preoperative simulation of biopsy under local anesthesia in 2 cases of multiple metastatic brain tumors. The parameters for SAS were TR/TE=50/40 msec, flip angle=60deg by the fast T 2 technique using refocused FID in steady-state (STERF technique). SAS images were processed by gray scale reversal. The MRA data were acquired with two-dimensional time of flight (TOF) sequence after intravenous administration of Gd-DTPA. Before imaging, the water-filled plastic tubes were placed on the patients scalp as markings for craniotomy. Their positions were planned by the neurosurgeons. On SAS, the markings for burr-hole appeared located above the tumors. However on the synthesized brain surface images, the positions of burr-hole were considered to be inadequate, since superficial cerebral vein and sinus were also visualized in the area of the markings. From these results, the positions of burr-hole were reset to avoid the venous structures, and so as to include the lesions in operations. The biopsies were performed successfully and safely because the venous structure could be excluded from the operative field. By this technique it was easy to confirm the relationships among lesions, skin markings and venous structures. The technique described appears to be a useful method for preoperative simulation of biopsies for multiple metastatic brain tumors under local anesthesia. (author)

Brain Imaging Using Hyperpolarized 129Xe Magnetic Resonance Imaging.

Science.gov (United States)

Chahal, Simrun; Prete, Braedan R J; Wade, Alanna; Hane, Francis T; Albert, Mitchell S

2018-01-01

Hyperpolarized (HP) 129 Xe magnetic resonance imaging (MRI) is a novel iteration of traditional MRI that relies on detecting the spins of 1 H. Since 129 Xe is a gaseous signal source, it can be used for lung imaging. Additionally, 129 Xe dissolves in the blood stream and can therefore be detectable in the brain parenchyma and vasculature. In this work, we provide detailed information on the protocols that we have developed to image 129 Xe within the brains of both rodents and human subjects. © 2018 Elsevier Inc. All rights reserved.

Primary Dystonia: Conceptualizing the Disorder through a Structural Brain Imaging Lens

Directory of Open Access Journals (Sweden)

Kristina Simonyan

2013-06-01

Full Text Available Background: Dystonia is a hyperkinetic movement disorder of involuntary, twisting repetitive movements. The anatomical structures and pathways implicated in its pathogenesis as well as their relationship to the neurophysiological paradigm of abnormal surround inhibition, maladaptive plasticity and impaired sensorimotor integration remain not well delineated. Objective: We review the use of high-resolution structural brain imaging using voxel-based morphometry (VBM and diffusion tensor imaging (DTI techniques for evaluation of brain changes in primary torsion dystonia and their relationships to the pathophysiology of this disorder. Methods: A search in PubMed was conducted to identify the relevant literature. Discussion: Structural imaging has enhanced our understanding of the pathophysiological mechanisms of dystonia. In particular, VBM and DTI data have revealed microstructural disturbances in the basal ganglia, sensorimotor cortices and cerebellum along with aberrations in the cortico-striato-pallido-thalamic and cerebello-thalamo-cortical pathways.  When combined with functional brain imaging and neurophysiological modalities, a structure-function relationship can be established in the dystonia brain network at the sensorimotor, plasticity, cortical disinhibition and cerebellar outflow connectivity levels. Structural imaging highlighted new anatomical substrates and, with a combined structural-functional approach, has offered new opportunities for investigation of the neurodevelopmental, environmental and/or genetic interplay in the brain networks of dystonia patients. 

Brain MRI Tumor Detection using Active Contour Model and Local Image Fitting Energy

Science.gov (United States)

Nabizadeh, Nooshin; John, Nigel

2014-03-01

Automatic abnormality detection in Magnetic Resonance Imaging (MRI) is an important issue in many diagnostic and therapeutic applications. Here an automatic brain tumor detection method is introduced that uses T1-weighted images and K. Zhang et. al.'s active contour model driven by local image fitting (LIF) energy. Local image fitting energy obtains the local image information, which enables the algorithm to segment images with intensity inhomogeneities. Advantage of this method is that the LIF energy functional has less computational complexity than the local binary fitting (LBF) energy functional; moreover, it maintains the sub-pixel accuracy and boundary regularization properties. In Zhang's algorithm, a new level set method based on Gaussian filtering is used to implement the variational formulation, which is not only vigorous to prevent the energy functional from being trapped into local minimum, but also effective in keeping the level set function regular. Experiments show that the proposed method achieves high accuracy brain tumor segmentation results.

MR imaging of brain tissue changes in acute and chronic solvent intoxication

International Nuclear Information System (INIS)

Rinck, P.A.; Nilsen, G.; Kvaerness, J.

1988-01-01

Acute and chronic intoxication with solvents is found both as an occupational hazard and as self-inflicted in addicts to solvent. Objective demonstration of such brain tissue changes is difficult with conventional imaging methods, and in most cases findings are negative. In a preliminary study, the brains of eight patients (aged 28-62 years) exposed to aggressive solvents for 1-27 years were examined with magnetic resonance imaging. All of the patients showed brain atrophy of varying extent, and seven of eight patients (all except the youngest and least exposed) had brain lesions that somewhat resembled dymyelinating changes (focal and confluent periventricular and deep white matter lesions, brain stem and cerebellar lesions); one patient showed cloudy, poorly defined lesions

Evaluation of MLACF based calculated attenuation brain PET imaging for FDG patient studies

Science.gov (United States)

Bal, Harshali; Panin, Vladimir Y.; Platsch, Guenther; Defrise, Michel; Hayden, Charles; Hutton, Chloe; Serrano, Benjamin; Paulmier, Benoit; Casey, Michael E.

2017-04-01

Calculating attenuation correction for brain PET imaging rather than using CT presents opportunities for low radiation dose applications such as pediatric imaging and serial scans to monitor disease progression. Our goal is to evaluate the iterative time-of-flight based maximum-likelihood activity and attenuation correction factors estimation (MLACF) method for clinical FDG brain PET imaging. FDG PET/CT brain studies were performed in 57 patients using the Biograph mCT (Siemens) four-ring scanner. The time-of-flight PET sinograms were acquired using the standard clinical protocol consisting of a CT scan followed by 10 min of single-bed PET acquisition. Images were reconstructed using CT-based attenuation correction (CTAC) and used as a gold standard for comparison. Two methods were compared with respect to CTAC: a calculated brain attenuation correction (CBAC) and MLACF based PET reconstruction. Plane-by-plane scaling was performed for MLACF images in order to fix the variable axial scaling observed. The noise structure of the MLACF images was different compared to those obtained using CTAC and the reconstruction required a higher number of iterations to obtain comparable image quality. To analyze the pooled data, each dataset was registered to a standard template and standard regions of interest were extracted. An SUVr analysis of the brain regions of interest showed that CBAC and MLACF were each well correlated with CTAC SUVrs. A plane-by-plane error analysis indicated that there were local differences for both CBAC and MLACF images with respect to CTAC. Mean relative error in the standard regions of interest was less than 5% for both methods and the mean absolute relative errors for both methods were similar (3.4%  ±  3.1% for CBAC and 3.5%  ±  3.1% for MLACF). However, the MLACF method recovered activity adjoining the frontal sinus regions more accurately than CBAC method. The use of plane-by-plane scaling of MLACF images was found to be a

Thin-Section Diffusion-Weighted Magnetic Resonance Imaging of the Brain with Parallel Imaging

International Nuclear Information System (INIS)

Oner, A.Y.; Celik, H.; Tali, T.; Akpek, S.; Tokgoz, N.

2007-01-01

Background: Thin-section diffusion-weighted imaging (DWI) is known to improve lesion detectability, with long imaging time as a drawback. Parallel imaging (PI) is a technique that takes advantage of spatial sensitivity information inherent in an array of multiple-receiver surface coils to partially replace time-consuming spatial encoding and reduce imaging time. Purpose: To prospectively evaluate a 3-mm-thin-section DWI technique combined with PI by means of qualitative and quantitative measurements. Material and Methods: 30 patients underwent conventional echo-planar (EPI) DWI (5-mm section thickness, 1-mm intersection gap) without parallel imaging, and thin-section EPI-DWI with PI (3-mm section thickness, 0-mm intersection gap) for a b value of 1000 s/mm 2 , with an imaging time of 40 and 80 s, respectively. Signal-to-noise ratio (SNR), relative signal intensity (rSI), and apparent diffusion coefficient (ADC) values were measured over a lesion-free cerebral region on both series by two radiologists. A quality score was assigned for each set of images to assess the image quality. When a brain lesion was present, contrast-to-noise ratio (CNR) and corresponding ADC were also measured. Student t-tests were used for statistical analysis. Results: Mean SNR values of the normal brain were 33.61±4.35 and 32.98±7.19 for conventional and thin-slice DWI (P>0.05), respectively. Relative signal intensities were significantly higher on thin-section DWI (P 0.05). Quality scores and overall lesion CNR were found to be higher in thin-section DWI with parallel imaging. Conclusion: A thin-section technique combined with PI improves rSI, CNR, and image quality without compromising SNR and ADC measurements in an acceptable imaging time. Keywords: Brain; DWI; parallel imaging; thin section

Imaging brain plasticity after trauma

Institute of Scientific and Technical Information of China (English)

Zhifeng Kou; Armin Iraji

2014-01-01

The brain is highly plastic after stroke or epilepsy;however, there is a paucity of brain plasticity investigation after traumatic brain injury (TBI). This mini review summarizes the most recent evidence of brain plasticity in human TBI patients from the perspective of advanced magnetic resonance imaging. Similar to other forms of acquired brain injury, TBI patients also demonstrat-ed both structural reorganization as well as functional compensation by the recruitment of other brain regions. However, the large scale brain network alterations after TBI are still unknown, and the ifeld is still short of proper means on how to guide the choice of TBI rehabilitation or treat-ment plan to promote brain plasticity. The authors also point out the new direction of brain plas-ticity investigation.

Automated delineation of stroke lesions using brain CT images

Directory of Open Access Journals (Sweden)

Céline R. Gillebert

2014-01-01

Full Text Available Computed tomographic (CT images are widely used for the identification of abnormal brain tissue following infarct and hemorrhage in stroke. Manual lesion delineation is currently the standard approach, but is both time-consuming and operator-dependent. To address these issues, we present a method that can automatically delineate infarct and hemorrhage in stroke CT images. The key elements of this method are the accurate normalization of CT images from stroke patients into template space and the subsequent voxelwise comparison with a group of control CT images for defining areas with hypo- or hyper-intense signals. Our validation, using simulated and actual lesions, shows that our approach is effective in reconstructing lesions resulting from both infarct and hemorrhage and yields lesion maps spatially consistent with those produced manually by expert operators. A limitation is that, relative to manual delineation, there is reduced sensitivity of the automated method in regions close to the ventricles and the brain contours. However, the automated method presents a number of benefits in terms of offering significant time savings and the elimination of the inter-operator differences inherent to manual tracing approaches. These factors are relevant for the creation of large-scale lesion databases for neuropsychological research. The automated delineation of stroke lesions from CT scans may also enable longitudinal studies to quantify changes in damaged tissue in an objective and reproducible manner.

Imaging of cerebral blood flow in patients with severe traumatic brain injury in the neurointensive care.

Directory of Open Access Journals (Sweden)

Elham eRostami

2014-07-01

Full Text Available Ischemia is a common and deleterious secondary injury following traumatic brain injury (TBI. A great challenge for the treatment of TBI patients in the neurointensive care unit (NICU is to detect early signs of ischemia in order to prevent further advancement and deterioration of the brain tissue. Today, several imaging techniques are available to monitor cerebral blood flow (CBF in the injured brain such as Positron emission tomography (PET, Single-photon emission computed tomography (SPECT, Xenon-CT, perfusion weighted magnetic resonance imaging (MRI and CT perfusion scan. An ideal imaging technique would enable continuous noninvasive measurement of blood flow and metabolism across the whole brain. Unfortunately, no current imaging method meets all these criteria. These techniques offer snapshots of the CBF. MRI may also provide some information about the metabolic state of the brain. PET provides images with high resolution and quantitative measurements of CBF and metabolism however it is a complex and costly method limited to few TBI centres. All of these methods except mobile Xenon-CT require transfer of TBI patients to the radiological department. Mobile Xenon-CT emerges as a feasible technique to monitor CBF in the NICU, with lower risk of adverse effects. Promising results have been demonstrated with Xenon-CT in predicting outcome in TBI patients. This review covers available imaging methods used to monitor CBF in patients with severe TBI.

Label-free imaging of brain and brain tumor specimens with combined two-photon excited fluorescence and second harmonic generation microscopy

Science.gov (United States)

Jiang, Liwei; Wang, Xingfu; Wu, Zanyi; Du, Huiping; Wang, Shu; Li, Lianhuang; Fang, Na; Lin, Peihua; Chen, Jianxin; Kang, Dezhi; Zhuo, Shuangmu

2017-10-01

Label-free imaging techniques are gaining acceptance within the medical imaging field, including brain imaging, because they have the potential to be applied to intraoperative in situ identifications of pathological conditions. In this paper, we describe the use of two-photon excited fluorescence (TPEF) and second harmonic generation (SHG) microscopy in combination for the label-free detection of brain and brain tumor specimens; gliomas. Two independently detecting channels were chosen to subsequently collect TPEF/SHG signals from the specimen to increase TPEF/SHG image contrasts. Our results indicate that the combined TPEF/SHG microscopic techniques can provide similar rat brain structural information and produce a similar resolution like conventional H&E staining in neuropathology; including meninges, cerebral cortex, white-matter structure corpus callosum, choroid plexus, hippocampus, striatum, and cerebellar cortex. It can simultaneously detect infiltrating human brain tumor cells, the extracellular matrix collagen fiber of connective stroma within brain vessels and collagen depostion in tumor microenvironments. The nuclear-to-cytoplasmic ratio and collagen content can be extracted as quantitative indicators for differentiating brain gliomas from healthy brain tissues. With the development of two-photon fiberscopes and microendoscope probes and their clinical applications, the combined TPEF and SHG microcopy may become an important multimodal, nonlinear optical imaging approach for real-time intraoperative histological diagnostics of residual brain tumors. These occur in various brain regions during ongoing surgeries through the method of simultaneously identifying tumor cells, and the change of tumor microenvironments, without the need for the removal biopsies and without the need for tissue labelling or fluorescent markers.

Heuristically improved Bayesian segmentation of brain MR images ...

African Journals Online (AJOL)

Heuristically improved Bayesian segmentation of brain MR images. ... or even the most prevalent task in medical image processing is image segmentation. Among them, brain MR images suffer ... show that our algorithm performs well in comparison with the one implemented in SPM. It can be concluded that incorporating ...

Do brain image databanks support understanding of normal ageing brain structure? A systematic review

International Nuclear Information System (INIS)

Dickie, David Alexander; Job, Dominic E.; Wardlaw, Joanna M.; Poole, Ian; Ahearn, Trevor S.; Staff, Roger T.; Murray, Alison D.

2012-01-01

To document accessible magnetic resonance (MR) brain images, metadata and statistical results from normal older subjects that may be used to improve diagnoses of dementia. We systematically reviewed published brain image databanks (print literature and Internet) concerned with normal ageing brain structure. From nine eligible databanks, there appeared to be 944 normal subjects aged ≥60 years. However, many subjects were in more than one databank and not all were fully representative of normal ageing clinical characteristics. Therefore, there were approximately 343 subjects aged ≥60 years with metadata representative of normal ageing, but only 98 subjects were openly accessible. No databank had the range of MR image sequences, e.g. T2*, fluid-attenuated inversion recovery (FLAIR), required to effectively characterise the features of brain ageing. No databank supported random subject retrieval; therefore, manual selection bias and errors may occur in studies that use these subjects as controls. Finally, no databank stored results from statistical analyses of its brain image and metadata that may be validated with analyses of further data. Brain image databanks require open access, more subjects, metadata, MR image sequences, searchability and statistical results to improve understanding of normal ageing brain structure and diagnoses of dementia. (orig.)

Prediction of tumor-brain adhesion in intracranial meningiomas by MR imaging and DSA

International Nuclear Information System (INIS)

Takeguchi, Takashi; Miki, Hitoshi; Shimizu, Teruhiko; Kikuchi, Keiichi; Mochizuki, Teruhito; Ohue, Shiro; Ohnishi, Takanori

2003-01-01

The purpose of this study was to evaluate the usefulness of MRI (magnetic resonance imaging) and DSA (digital subtraction angiography) by using preoperative MRI and DSA findings in the examination of meningiomas before excision. In particular, we focused on their usefulness in predicting tumor-brain adhesion during surgery. The subjects were 36 patients with intracranial meningioma who underwent tumor excision at which time neurosurgeons examined the tumor-brain adhesion. Two neurosurgeons evaluated the degree of tumor-brain adhesion from operation records and videotapes recorded during surgery. Two neuroradiologists retrospectively evaluated the preoperative MRI findings including tumor diameter, signal intensity of the tumor parenchyma obtained with T 2 -weighted imaging (T 2 WI), characteristics of the tumor-brain interface, and degree of peritumoral brain edema. The vascular supply was also evaluated from the preoperative DSA findings. The relationship between these MRI and DSA findings and the degree of tumor-brain adhesion during surgery as classified by the neurosurgeons was statistically analyzed. The degree of peritumoral brain edema and the shapes and characteristics of the tumor-brain interface, including the findings of FLAIR (fluid-attenuated inversion recovery) imaging and vascular supply observed by DSA, were significantly correlated with tumor-brain adhesion. In particular, the shapes and characteristics of the tumor-brain interface as observed by T 1 -weighted imaging (T 1 WI), T2WI, and FLAIR, respectively, as well as the vascular supply observed by DSA, were closely correlated with the degree of tumor-brain adhesion encountered during surgery. According to these results, we developed a method of predicting tumor-brain adhesion that considers the shape of the tumor-brain interface revealed by MRI and the vascular supply revealed by DSA. We retrospectively examined the findings of MRI and DSA performed before excision of meningioma and clarified

Differential diagnostic value of diffusion weighted imaging on brain abscess and necrotic or cystic brain tumors

International Nuclear Information System (INIS)

Zhang Xiaoya; Yin Jie; Wang Kunpeng; Zhang Jiandang; Liang Biling

2009-01-01

Objective: To investigate the value of diffusion weighted imaging (DWI)on brain abscess and necrotic or cystic brain tumors. Methods: 27 cases with brain abscesses and 33 cases with necrotic or cystic brain tumors (gliomas or metastases) were performed conventional MRI and DWI. Apparent diffusion coefficient (ADC) of region of interest (ROI) was measured and statistically tested. Sensitivity and specificity were calculated and compared with conventional MR and DWI. Results: Hyperintensity signal was seen on most brain abscesses. All necrotic or cystic brain tumors showed hypointensity signal on DWI. There was statistical significance on ADC of them. The sensitivity and specificity of conventional MRI was lower than that of DWI. Conclusion: DWI and ADC were useful in distinguishing brain abscessed from necrotic or cystic brain tumors, which was important in addition to conventional MRI. (authors)

Brain MR imaging in child abuse

International Nuclear Information System (INIS)

Sato, Y.; Ellerbroek, C.J.; Alexander, R.; Kao, S.C.S.; Yuh, W.T.C.; Smith, W.L.

1988-01-01

Intracranial injuries represent the most severe manifestation of child abuse. CT of the brain is the current standard for evaluation of these infants; however, MR imaging offers several potential advantages. MR imaging and CT were performed in ten infants who suffered intracranial trauma owing to child abuse. CT was slightly better at demonstrating subarachnoid hemorrhage and had definite advantages for defining fractures. MR imaging was superior in the demonstration of subacute extraaxial hemorrhage, deep brain injuries owing to shearing effects from shaking, and anoxic injuries. MR imaging has a definite complementary role in the evaluation of acute intracranial trauma in child abuse victims

Assessing paedophilia based on the haemodynamic brain response to face images

DEFF Research Database (Denmark)

Ponseti, Jorge; Granert, Oliver; Van Eimeren, Thilo

2016-01-01

that human face processing is tuned to sexual age preferences. This observation prompted us to test whether paedophilia can be inferred based on the haemodynamic brain responses to adult and child faces. METHODS: Twenty-four men sexually attracted to prepubescent boys or girls (paedophiles) and 32 men......OBJECTIVES: Objective assessment of sexual preferences may be of relevance in the treatment and prognosis of child sexual offenders. Previous research has indicated that this can be achieved by pattern classification of brain responses to sexual child and adult images. Our recent research showed...... sexually attracted to men or women (teleiophiles) were exposed to images of child and adult, male and female faces during a functional magnetic resonance imaging (fMRI) session. RESULTS: A cross-validated, automatic pattern classification algorithm of brain responses to facial stimuli yielded four...

Mechanism of Chronic Pain in Rodent Brain Imaging

Science.gov (United States)

Chang, Pei-Ching

Chronic pain is a significant health problem that greatly impacts the quality of life of individuals and imparts high costs to society. Despite intense research effort in understanding of the mechanism of pain, chronic pain remains a clinical problem that has few effective therapies. The advent of human brain imaging research in recent years has changed the way that chronic pain is viewed. To further extend the use of human brain imaging techniques for better therapies, the adoption of imaging technique onto the animal pain models is essential, in which underlying brain mechanisms can be systematically studied using various combination of imaging and invasive techniques. The general goal of this thesis is to addresses how brain develops and maintains chronic pain in an animal model using fMRI. We demonstrate that nucleus accumbens, the central component of mesolimbic circuitry, is essential in development of chronic pain. To advance our imaging technique, we develop an innovative methodology to carry out fMRI in awake, conscious rat. Using this cutting-edge technique, we show that allodynia is assoicated with shift brain response toward neural circuits associated nucleus accumbens and prefrontal cortex that regulate affective and cognitive component of pain. Taken together, this thesis provides a deeper understanding of how brain mediates pain. It builds on the existing body of knowledge through maximizing the depth of insight into brain imaging of chronic pain.

Brain imaging and autism

International Nuclear Information System (INIS)

Zilbovicius, M.

2006-01-01

Autism is a neuro-developmental disorder with a range of clinical presentations, from mild to severe, referred to as autism spectrum disorders (ASD). The most common clinical ASD sign is social interaction impairment, which is associated with verbal and non-verbal communication deficits and stereotyped and obsessive behaviors. Thanks to recent brain imaging studies, scientists are getting a better idea of the neural circuits involved in ASD. Indeed, functional brain imaging, such as positron emission tomography (PET), single positron emission tomograph y (SPECT) and functional MRI (fMRI) have opened a new perspective to study normal and pathological brain functions. Three independent studies have found anatomical and rest functional temporal abnormalities. These anomalies are localized in the superior temporal sulcus bilaterally which are critical for perception of key social stimuli. In addition, functional studies have shown hypo-activation of most areas implicated in social perception (face and voice perception) and social cognition (theory of mind). These data suggest an abnormal functioning of the social brain network. The understanding of such crucial abnormal mechanism may drive the elaboration of new and more adequate social re-educative strategies in autism. (author)

Brain imaging and autism

Energy Technology Data Exchange (ETDEWEB)

Zilbovicius, M [Service Hospitalier Frederic Joliot (CEA/DSV/DRM), INSERM CEA 0205, 91 - Orsay (France)

2006-07-01

Autism is a neuro-developmental disorder with a range of clinical presentations, from mild to severe, referred to as autism spectrum disorders (ASD). The most common clinical ASD sign is social interaction impairment, which is associated with verbal and non-verbal communication deficits and stereotyped and obsessive behaviors. Thanks to recent brain imaging studies, scientists are getting a better idea of the neural circuits involved in ASD. Indeed, functional brain imaging, such as positron emission tomography (PET), single positron emission tomograph y (SPECT) and functional MRI (fMRI) have opened a new perspective to study normal and pathological brain functions. Three independent studies have found anatomical and rest functional temporal abnormalities. These anomalies are localized in the superior temporal sulcus bilaterally which are critical for perception of key social stimuli. In addition, functional studies have shown hypo-activation of most areas implicated in social perception (face and voice perception) and social cognition (theory of mind). These data suggest an abnormal functioning of the social brain network. The understanding of such crucial abnormal mechanism may drive the elaboration of new and more adequate social re-educative strategies in autism. (author)

Magnetic resonance imaging of cold injury-induced brain edema in rats

International Nuclear Information System (INIS)

Houkin, Kiyohiro; Abe, Hiroshi; Hashiguchi, Yuji; Seri, Shigemi.

1996-01-01

The chronological changes of blood-brain barrier disruption, and diffusion and absorption of edema fluid were investigated in rats with cold-induced brain injury (vasogenic edema) using magnetic resonance imaging. Contrast medium was administered intravenously at 3 and 24 hours after lesioning as a tracer of edema fluid. Serial T 1 -weighted multiple-slice images were obtained for 180 minutes after contrast administration. Disruption of the blood-brain barrier was more prominent at 24 hours after lesioning than at 3 hours. Contrast medium leaked from the periphery of the injury and gradually diffused to the center of the lesion. Contrast medium diffused into the corpus callosum and the ventricular system (cerebrospinal fluid). Disruption of the blood-brain barrier induced by cold injury was most prominent at the periphery of the vasogenic edema. Edema fluid subsequently extended into the center of the lesion and was also absorbed by the ventricular system. Magnetic resonance imaging is a useful method to assess the efficacy of therapy for vasogenic edema. (author)

The study on acquisition mode and reconstruction parameters of brain FDG PET images

International Nuclear Information System (INIS)

Zuo Chuantao; Liu Yongchang; Guan Yihui; Zhao Jun; Lin Xiangtong

2001-01-01

Objective: To evaluate the effect of acquisition mode on the brain PET images. Methods: After changing conditions and parameters, the authors got brain PET images of different acquisition modes, different emission counts, different transmission times; and compared with the reference images the impacts of different acquisition modes, different acquisition conditions were assessed. Results: Compared with 2D mode, much higher background and noise were observed on the reconstruction images of 3D mode, and the bottoms of the brain structure were not well displayed. But the middle part of brain structure displayed well in 2D and 3D mode without difference; the gray/white radioactivity ratios were 2.108 +- 0.183 and 2.286 +- 0.232 under 2D and 3D mode, respectively. The gray/white radioactivity ratios with different emission counts were 2.108 +- 0.183, 2.215 +- 0.158, 2.161 +- 0.176, respectively, there was no evident difference among them. With transmission counts increasing, the segmented image outline of Hoffman phantom and brain structure became clear and integral. Conclusions: Different acquisition modes, different emission counts and different transmission times are of certain impacts on brain FDG PET images, and it should be paid more attention in clinical practice

A new method for brain tumor detection using the Bhattacharyya similarity coefficient, color conversions and neural network

Directory of Open Access Journals (Sweden)

Bahman Mansori

2015-10-01

Full Text Available Background: Magnetic resonance imaging (MRI is widely applied for examination and diagnosis of brain tumors based on its advantages of high resolution in detecting the soft tissues and especially of its harmless radiation damages to human bodies. The goal of the processing of images is automatic segmentation of brain edema and tumors, in different dimensions of the magnetic resonance images. Methods: The proposed method is based on the unsupervised method which discovers the tumor region, if there is any, by analyzing the similarities between two hemispheres and computes the image size of the goal function based on Bhattacharyya coefficient which is used in the next stage to detect the tumor region or some part of it. In this stage, for reducing the color variation, the gray brain image is segmented, then it is turned to gray again. The self-organizing map (SOM neural network is used the segmented brain image is colored and finally the tumor is detected by matching the detected region and the colored image. This method is proposed to analyze MRI images for discovering brain tumors, and done in Bu Ali Sina University, Hamedan, Iran, in 2014. Results: The results for 30 randomly selected images from data bank of MRI center in Hamedan was compared with manually segmentation of experts. The results showed that, our proposed method had the accuracy of more than 94% at Jaccard similarity index (JSI, 97% at Dice similarity score (DSS, and 98% and 99% at two measures of specificity and sensitivity. Conclusion: The experimental results showed that it was satisfactory and can be used in automatic separation of tumor from normal brain tissues and therefore it can be used in practical applications. The results showed that the use of SOM neural network to classify useful magnetic resonance imaging of the brain and demonstrated a good performance.

Fluorescent-protein stabilization and high-resolution imaging of cleared, intact mouse brains.

Directory of Open Access Journals (Sweden)

Martin K Schwarz

Full Text Available In order to observe and quantify long-range neuronal connections in intact mouse brain by light microscopy, it is first necessary to clear the brain, thus suppressing refractive-index variations. Here we describe a method that clears the brain and preserves the signal from proteinaceous fluorophores using a pH-adjusted non-aqueous index-matching medium. Successful clearing is enabled through the use of either 1-propanol or tert-butanol during dehydration whilst maintaining a basic pH. We show that high-resolution fluorescence imaging of entire, structurally intact juvenile and adult mouse brains is possible at subcellular resolution, even following many months in clearing solution. We also show that axonal long-range projections that are EGFP-labelled by modified Rabies virus can be imaged throughout the brain using a purpose-built light-sheet fluorescence microscope. To demonstrate the viability of the technique, we determined a detailed map of the monosynaptic projections onto a target cell population in the lateral entorhinal cortex. This example demonstrates that our method permits the quantification of whole-brain connectivity patterns at the subcellular level in the uncut brain.

Functional photoacoustic tomography for neonatal brain imaging: developments and challenges

Science.gov (United States)

Hariri, Ali; Tavakoli, Emytis; Adabi, Saba; Gelovani, Juri; Avanaki, Mohammad R. N.

2017-03-01

Transfontanelle ultrasound imaging (TFUSI) is a routine diagnostic brain imaging method in infants who are born prematurely, whose skull bones have not completely fused together and have openings between them, so-called fontanelles. Open fontanelles in neonates provide acoustic windows, allowing the ultrasound beam to freely pass through. TFUSI is used to rule out neurological complications of premature birth including subarachnoid hemorrhage (SAH), intraventricular (IVH), subependimal (SEPH), subdural (SDH) or intracerebral (ICH) hemorrhages, as well as hypoxic brain injuries. TFUSI is widely used in the clinic owing to its low cost, safety, accessibility, and noninvasive nature. Nevertheless, the accuracy of TFUSI is limited. To address several limitations of current clinical imaging modalities, we develop a novel transfontanelle photoacoustic imaging (TFPAI) probe, which, for the first time, should allow for non-invasive structural and functional imaging of the infant brain. In this study, we test the feasibility of TFPAI for detection of experimentally-induced intra ventricular and Intraparenchymal hemorrhage phantoms in a sheep model with a surgically-induced cranial window which will serve as a model of neonatal fontanelle. This study is towards using the probe we develop for bedside monitoring of neonates with various disease conditions and complications affecting brain perfusion and oxygenation, including apnea, asphyxia, as well as for detection of various types of intracranial hemorrhages (SAH, IVH, SEPH, SDH, ICH).

Wireless image-data transmission from an implanted image sensor through a living mouse brain by intra body communication

Science.gov (United States)

Hayami, Hajime; Takehara, Hiroaki; Nagata, Kengo; Haruta, Makito; Noda, Toshihiko; Sasagawa, Kiyotaka; Tokuda, Takashi; Ohta, Jun

2016-04-01

Intra body communication technology allows the fabrication of compact implantable biomedical sensors compared with RF wireless technology. In this paper, we report the fabrication of an implantable image sensor of 625 µm width and 830 µm length and the demonstration of wireless image-data transmission through a brain tissue of a living mouse. The sensor was designed to transmit output signals of pixel values by pulse width modulation (PWM). The PWM signals from the sensor transmitted through a brain tissue were detected by a receiver electrode. Wireless data transmission of a two-dimensional image was successfully demonstrated in a living mouse brain. The technique reported here is expected to provide useful methods of data transmission using micro sized implantable biomedical sensors.

Brain lesion analysis using three-dimensional SPECT imaging

International Nuclear Information System (INIS)

Shibata, Iekado; Onagi, Atsuo; Kuroki, Takao

1995-01-01

A three-headed gamma camera (PRISM 3000) is capable to scan the protocol of early dynamic SPECT and to analyze two radioisotopes at the same time. We have framed three-dimensional brain SPECT images for several brain diseases by using the Application Visualization System (AVS). We carried out volume measurements in brain tumors and/or AVMs by applying this methodology. Thallium-201 and/or 123I-IMP were used for brain SPECT imaging. The dynamic scan protocol was changed in accordance with the given disease. The protocol for brain tumors was derived from a preliminary comparative study with thallium-201 and 123I-IMP that had suggested a disparity in the detection of brain tumors and the differentiation between tumor tissue and normal brain. The three-dimension SPECT image represented the brain tumor or AVM in a striking fashion, and the changes with respect to tumor or AVM after radiosurgery or embolization were understood readily. (author)

The effect, identification and correction of misalignment between PET transmission and emission scans on brain PET imaging

International Nuclear Information System (INIS)

Zhang Xiangsong; He Zuoxiang; Tang Anwu; Qiao Suixian

2004-01-01

Objectives: To study the effect of misalignment between PET transmission and emission scans of brain on brain PET imaging, and the Methods to identify and correct it. Methods: 18F-FDG PET imaging was performed on 8 volunteers. The emission images were reconstructed with attenuation correction after some translations and rotations in the x-axis and transverse plane were given, 1 mm and 1 degree each step, respectively. The 3-D volume fusion of PET emission and transmission scans was used to identify the suspected misalignment on 10 18F-FDG PET brain imaging. Three Methods were used to correct the misalignment. First, to quantitate the amount of the misalignment by 3-D volume registration of PET emission and transmission scans, the emission images were reconstructed with corrected translations and rotations in x-direction and transverse plane. Second, the emission images were reconstructed with mathematic calculation of brain attenuation. Third, 18F-FDG PET brain imaging was redone with careful application of laser alignment. Results: The translations greater than 3 mm in x-direction and the rotations greater than 8 degrees in transverse plane could lead to visible artifacts, which were presented with decreasing radioactivity uptake in the cortex of half cerebrum and in the frontal cortex at the side in the translating or rotating direction, respectively. The 3-D volume fusion of PET emission and transmission scans could identify and quantitate the amount of misalignment between PET emission and transmission scans of brain. The PET emission images reconstructed with corrected misalignment and mathematic calculation of brain attenuation were consistent with redone PET brain imaging. Conclusions: The misalignment between PET transmission and emission scans of brain can lead to visible artifacts. The 3-D volume fusion of PET emission and transmission scans can identify and quantitate the amount of the misalignment. The visible artifacts caused by the misalignment can be

Visualization of brain surface structures by weighted summation technique using multislice MR images

International Nuclear Information System (INIS)

Machida, Yoshio; Hatanaka, Masahiko; Hagiwara, Masayuki; Sugimoto, Hiroshi; Yoshida, Tadatoki; Katada, Kazuhiro.

1991-01-01

Surface anatomy scanning (SAS) technique which visualizes brain surface structures has been developed since 1987. In this paper, we propose a modified method called 'multislice SAS', which also generates such surface structure images, and has several advantages compared with conventional SAS technique. The conventional SAS technique uses a very long echo time sequence (e.g. SE(3000, 250)) with a thick slice and a surface coil to enhance CSF on the brain surface. Our modified technique also uses a long echo time sequence. But, added multislice images, each appropriately weighted, are used in stead of a thick slice and a surface coil. Our basic studies have shown that this modified method has the following advantage: Several surface images with slightly different summation directions are obtained, and they are used for stereographic display and cine display. This is very useful for visualizing the spatial relationship of brain surface structures. By choosing appropriate weighting, we can obtain clinically legible surface images. This technique dose not require a surface coil. It means that flexibility of selecting imaging direction is high. We can make a lot of modifications, because the original multislice images of weighted summation are arbitrary. And we also clarify some limitation or disadvantage of this modified method. In conclusion, we think that this technique is one of the practical approaches for surface anatomy imaging. (author)

Prenatal Brain MR Imaging: Reference Linear Biometric Centiles between 20 and 24 Gestational Weeks.

Science.gov (United States)

Conte, G; Milani, S; Palumbo, G; Talenti, G; Boito, S; Rustico, M; Triulzi, F; Righini, A; Izzo, G; Doneda, C; Zolin, A; Parazzini, C

2018-05-01

Evaluation of biometry is a fundamental step in prenatal brain MR imaging. While different studies have reported reference centiles for MR imaging biometric data of fetuses in the late second and third trimesters of gestation, no one has reported them in fetuses in the early second trimester. We report centiles of normal MR imaging linear biometric data of a large cohort of fetal brains within 24 weeks of gestation. From the data bases of 2 referral centers of fetal medicine, accounting for 3850 examinations, we retrospectively collected 169 prenatal brain MR imaging examinations of singleton pregnancies, between 20 and 24 weeks of gestational age, with normal brain anatomy at MR imaging and normal postnatal neurologic development. To trace the reference centiles, we used the CG-LMS method. Reference biometric centiles for the developing structures of the cerebrum, cerebellum, brain stem, and theca were obtained. The overall interassessor agreement was adequate for all measurements. Reference biometric centiles of the brain structures in fetuses between 20 and 24 weeks of gestational age may be a reliable tool in assessing fetal brain development. © 2018 by American Journal of Neuroradiology.

The brain imaging study of the organophosphorus pesticides poisoning

International Nuclear Information System (INIS)

Yang Yanmei; Liu Huaijun; Li Shuling; Wang Yongsheng; Huang Boyuan; Chi Cen; Shi Zhenyang; Cui Caixia; Zhou Lixia; Liu Runtian

2004-01-01

Objective: To summarize the CT and MR imaging findings in acute organophosphorus pesticides poisoning patients, and to improve the early diagnostic ability. Methods: The imaging of 34 patients of organophosphorus pesticides poisoning was analyzed, the poisons were all taken orally. The pesticides included methamidophos (12 cases), omethoate (15 cases), DDV (3 cases), and methylparathion (4 cases). According to the diagnosis and classification diagnosis criterion of acute organophosphorus pesticides poisoning, the patients were divided into two groups: mild or moderate grade group (24 cases) and severe grade group (10 cases). The relationship between the clinic grade and CT and MRI findings was studied. Results: in the severe grade group, 4 patients showed brain edema, presenting as sulcus and fissure flattened or disappeared, and ventricles and cisterns narrowed or closed 2-3 days after poisoning. In 3 patients 3 days to 3 months after poisoning, bilateral basal ganglion and cerebral cortex showed prolonged T 1 and T 2 signals, and high signal intensity was detected on FLAIR, and bilateral basal ganglion low density was revealed on CT. T 1 relaxation was shortened, T 2 WI and FLAIR imaging showed high signal intensity in 1 patient. The imaging of 1 patient 6 months after poisoning showed the cerebral sulcus, fissure and ventricle were enlarged. CT and MRI in the mild or moderate group were normal. By the Fisher's exact probabilities test, the imaging exhibition difference between the severe grade and mild or moderate grade patients was significant. Conclusion: The CT and MRI can reflect the brain injury after poisoning, and the imaging exhibitions were various. The imaging information can provide credible foundation for the therapy for lightening the brain edema and nourishing the brain cell

99Tcm-Neurolite brain SPECT imaging as an outcome predictor after brain trauma: initial experience

International Nuclear Information System (INIS)

Howarth, D.M.; Lan, L.; Booth, G.; Christie, J.; Bookalil, A.; Pollack, M.; Pacey, D.

1999-01-01

Full text: The aim of this study was to use semi-quantitative 99 Tc m -ethylene cysteine dimer (Neurolite) cerebral blood flow (CBF) SPET brain imaging to assess its role in predicting outcome after brain trauma. Twelve adult patients (9 males, 3 females) who sustained moderate to severe brain trauma were studied by CBF/SPET within 4 weeks of the injury (scan A) and again after 1 year (scan B). Clinical assessment was also performed at these times and included extensive neuropsychometric testing. Patients received 800-850 MBq 99 Tc m -Neurolite intravenously, and were imaged using a triple-headed gamma camera with LEUHR fan beam collimators. Processing, filtering, reconstruction and data set selection were identical for scans A and B. Semi-quantitative analysis was performed using 25 regions of interest in the cerebral cortex and deep structures in 2 coronal, 2 sagittal and 3 oblique planes. Normalized mean counts per pixel for the whole brain, and regional brain ratios were calculated. Scans A and B were compared and correlated to the clinical outcome data. Two patients with minimal CBF abnormalities made full recoveries. The remaining 10 had moderate to severe focal CBF defects, which showed no significant improvement at 12 months. Of these patients, 2 had moderate disability, 3 had severe to moderate disability and 2 had severe disability at 12 months. Patients with persisting focal abnormal CBF showed persisting neurological deficits. Neurolite brain CBF imaging is a useful method of predicting outcome after moderate to severe head injury

Histogram-based normalization technique on human brain magnetic resonance images from different acquisitions.

Science.gov (United States)

Sun, Xiaofei; Shi, Lin; Luo, Yishan; Yang, Wei; Li, Hongpeng; Liang, Peipeng; Li, Kuncheng; Mok, Vincent C T; Chu, Winnie C W; Wang, Defeng

2015-07-28

Intensity normalization is an important preprocessing step in brain magnetic resonance image (MRI) analysis. During MR image acquisition, different scanners or parameters would be used for scanning different subjects or the same subject at a different time, which may result in large intensity variations. This intensity variation will greatly undermine the performance of subsequent MRI processing and population analysis, such as image registration, segmentation, and tissue volume measurement. In this work, we proposed a new histogram normalization method to reduce the intensity variation between MRIs obtained from different acquisitions. In our experiment, we scanned each subject twice on two different scanners using different imaging parameters. With noise estimation, the image with lower noise level was determined and treated as the high-quality reference image. Then the histogram of the low-quality image was normalized to the histogram of the high-quality image. The normalization algorithm includes two main steps: (1) intensity scaling (IS), where, for the high-quality reference image, the intensities of the image are first rescaled to a range between the low intensity region (LIR) value and the high intensity region (HIR) value; and (2) histogram normalization (HN),where the histogram of low-quality image as input image is stretched to match the histogram of the reference image, so that the intensity range in the normalized image will also lie between LIR and HIR. We performed three sets of experiments to evaluate the proposed method, i.e., image registration, segmentation, and tissue volume measurement, and compared this with the existing intensity normalization method. It is then possible to validate that our histogram normalization framework can achieve better results in all the experiments. It is also demonstrated that the brain template with normalization preprocessing is of higher quality than the template with no normalization processing. We have proposed

IMAGING BRAIN SIGNAL TRANSDUCTION AND METABOLISM VIA ARACHIDONIC AND DOCOSAHEXAENOIC ACID IN ANIMALS AND HUMANS

Science.gov (United States)

Basselin, Mireille; Ramadan, Epolia; Rapoport, Stanley I.

2012-01-01

The polyunsaturated fatty acids (PUFAs), arachidonic acid (AA, 20:4n-6) and docosahexaenoic acid (DHA, 22:6n-3), important second messengers in brain, are released from membrane phospholipid following receptor-mediated activation of specific phospholipase A2 (PLA2) enzymes. We developed an in vivo method in rodents using quantitative autoradiography to image PUFA incorporation into brain from plasma, and showed that their incorporation rates equal their rates of metabolic consumption by brain. Thus, quantitative imaging of unesterified plasma AA or DHA incorporation into brain can be used as a biomarker of brain PUFA metabolism and neurotransmission. We have employed our method to image and quantify effects of mood stabilizers on brain AA/DHA incorporation during neurotransmission by muscarinic M1,3,5, serotonergic 5-HT2A/2C, dopaminergic D2-like (D2, D3, D4) or glutamatergic N-methyl-D-aspartic acid (NMDA) receptors, and effects of inhibition of acetylcholinesterase, of selective serotonin and dopamine reuptake transporter inhibitors, of neuroinflammation (HIV-1 and lipopolysaccharide) and excitotoxicity, and in genetically modified rodents. The method has been extended for the use with positron emission tomography (PET), and can be employed to determine how human brain AA/DHA signaling and consumption are influenced by diet, aging, disease and genetics. PMID:22178644

Brain Perfusion SPECT Imaging in Sturge - Weber Syndrome : Comparison with MR Imaging

International Nuclear Information System (INIS)

Ryu, Jin Sook; Choi, Yun Young; Moon, Dae Hyuk; Yang, Seoung Oh; Ko, Tae Sung; Yoo, Shi Joon; Lee, Hee Kyung

1996-01-01

The purpose of this study was evaluate the characteristic perfusion changes in patients with Sturge-Weber syndrome by comparison of the findings of brain MR images and perfusion SPECT images. 99m Tc-HMPAO or 99m Tc-ECD interictal brain SPECTs were performed on 5 pediatric patients with Struge-Weber syndrome within 2 weeks after MR imaging. Brain SPECTs of three patients without calcification showed diminished perfusion in the affected area on MR image. A 3 month-old patient without brain atrophy or calcification demonstrated paradoxical hyperperfusion in the affected hemisphere, and follow-up perfusion SPECT revealed decreased perfusion in the same area. The other patient with advanced calcified lesion and atrophy on MR image showed diffusely decreased perfusion in the affected hemisphere, but a focal area of increased perfusion was also noted in the ipsilateral temporal lobe on SPECT. In conclusion, brain perfusion of the affected area of Sturge-Weber syndrome patients was usually diminished, but early or advanced patients may show paradoxical diffuse or focal hyperperfusion in the affected hemisphere. Further studies are needed for better understanding of these perfusion changes and pathophysiology of Struge-Weber syndrome.

Mesoscale brain explorer, a flexible python-based image analysis and visualization tool.

Science.gov (United States)

Haupt, Dirk; Vanni, Matthieu P; Bolanos, Federico; Mitelut, Catalin; LeDue, Jeffrey M; Murphy, Tim H

2017-07-01

Imaging of mesoscale brain activity is used to map interactions between brain regions. This work has benefited from the pioneering studies of Grinvald et al., who employed optical methods to image brain function by exploiting the properties of intrinsic optical signals and small molecule voltage-sensitive dyes. Mesoscale interareal brain imaging techniques have been advanced by cell targeted and selective recombinant indicators of neuronal activity. Spontaneous resting state activity is often collected during mesoscale imaging to provide the basis for mapping of connectivity relationships using correlation. However, the information content of mesoscale datasets is vast and is only superficially presented in manuscripts given the need to constrain measurements to a fixed set of frequencies, regions of interest, and other parameters. We describe a new open source tool written in python, termed mesoscale brain explorer (MBE), which provides an interface to process and explore these large datasets. The platform supports automated image processing pipelines with the ability to assess multiple trials and combine data from different animals. The tool provides functions for temporal filtering, averaging, and visualization of functional connectivity relations using time-dependent correlation. Here, we describe the tool and show applications, where previously published datasets were reanalyzed using MBE.

Electrophysiological Source Imaging: A Noninvasive Window to Brain Dynamics.

Science.gov (United States)

He, Bin; Sohrabpour, Abbas; Brown, Emery; Liu, Zhongming

2018-06-04

Brain activity and connectivity are distributed in the three-dimensional space and evolve in time. It is important to image brain dynamics with high spatial and temporal resolution. Electroencephalography (EEG) and magnetoencephalography (MEG) are noninvasive measurements associated with complex neural activations and interactions that encode brain functions. Electrophysiological source imaging estimates the underlying brain electrical sources from EEG and MEG measurements. It offers increasingly improved spatial resolution and intrinsically high temporal resolution for imaging large-scale brain activity and connectivity on a wide range of timescales. Integration of electrophysiological source imaging and functional magnetic resonance imaging could further enhance spatiotemporal resolution and specificity to an extent that is not attainable with either technique alone. We review methodological developments in electrophysiological source imaging over the past three decades and envision its future advancement into a powerful functional neuroimaging technology for basic and clinical neuroscience applications.

Actinomycotic brain infection: registered diffusion, perfusion MR imaging and MR spectroscopy

International Nuclear Information System (INIS)

Wang, Sumei; Wolf, Ronald L.; Woo, John H.; Melhem, Elias R.; Poptani, Harish; Wang, Jiongjiong; O'Rourke, Donald M.; Roy, Subhojit

2006-01-01

Introduction: Actinomycotic brain infection is caused by an organism of the Actinomyces genus. We report here one such case. Methods: The methods used included coregistered diffusion, perfusion and spectroscopic magnetic resonance (MR) imaging. Decreased apparent diffusion coefficient, markedly elevated fractional anisotropy (FA) and reduced cerebral blood flow were observed. MR spectroscopy demonstrated elevated amino acids, acetate and succinate. Elevated FA values may be due to the microstructure of this special brain infection. (orig.)

Optimization of Butterworth filter for brain SPECT imaging

International Nuclear Information System (INIS)

Minoshima, Satoshi; Maruno, Hirotaka; Yui, Nobuharu

1993-01-01

A method has been described to optimize the cutoff frequency of the Butterworth filter for brain SPECT imaging. Since a computer simulation study has demonstrated that separation between an object signal and the random noise in projection images in a spatial-frequency domain is influenced by the total number of counts, the cutoff frequency of the Butterworth filter should be optimized for individual subjects according to total counts in a study. To reveal the relationship between the optimal cutoff frequencies and total counts in brain SPECT study, we used a normal volunteer and 99m Tc hexamethyl-propyleneamine oxime (HMPAO) to obtain projection sets with different total counts. High quality images were created from a projection set with an acquisition time of 300-seconds per projection. The filter was optimized by calculating mean square errors from high quality images visually inspecting filtered reconstructed images. Dependence between total counts and optimal cutoff frequencies was clearly demonstrated in a nomogram. Using this nomogram, the optimal cutoff frequency for each study can be estimated from total counts, maximizing visual image quality. The results suggest that the cutoff frequency of Butterworth filter should be determined by referring to total counts in each study. (author)

Quantitative SPECT brain imaging: Effects of attenuation and detector response

International Nuclear Information System (INIS)

Gilland, D.R.; Jaszczak, R.J.; Bowsher, J.E.; Turkington, T.G.; Liang, Z.; Greer, K.L.; Coleman, R.E.

1993-01-01

Two physical factors that substantially degrade quantitative accuracy in SPECT imaging of the brain are attenuation and detector response. In addition to the physical factors, random noise in the reconstructed image can greatly affect the quantitative measurement. The purpose of this work was to implement two reconstruction methods that compensate for attenuation and detector response, a 3D maximum likelihood-EM method (ML) and a filtered backprojection method (FB) with Metz filter and Chang attenuation compensation, and compare the methods in terms of quantitative accuracy and image noise. The methods were tested on simulated data of the 3D Hoffman brain phantom. The simulation incorporated attenuation and distance-dependent detector response. Bias and standard deviation of reconstructed voxel intensities were measured in the gray and white matter regions. The results with ML showed that in both the gray and white matter regions as the number of iterations increased, bias decreased and standard deviation increased. Similar results were observed with FB as the Metz filter power increased. In both regions, ML had smaller standard deviation than FB for a given bias. Reconstruction times for the ML method have been greatly reduced through efficient coding, limited source support, and by computing attenuation factors only along rays perpendicular to the detector

[Brain imaging in autism spectrum disorders. A review].

Science.gov (United States)

Dziobek, I; Köhne, S

2011-05-01

In the past two decades, an increasing number of functional and structural brain imaging studies has provided insights into the neurobiological basis of autism spectrum disorders (ASD). This article summarizes pertinent functional brain imaging studies addressing the neuronal underpinnings of ASD symptomatology (impairments in social interaction and communication, repetitive and restrictive behavior) and associated neuropsychological deficits (theory of mind, executive functions, central coherence), complemented by relevant structural imaging findings. The results of these studies show that although cognitive functions in ASD are generally mediated by the same brain regions as in typically developed individuals, the degree and especially the patterns of brain activation often differ. Therefore, a hypothesis of aberrant network connectivity has increasingly been favored over one of focal brain dysfunction.

Contrast enhancement in EIT imaging of the brain

International Nuclear Information System (INIS)

Nissinen, A; Kaipio, J P; Vauhkonen, M; Kolehmainen, V

2016-01-01

We consider electrical impedance tomography (EIT) imaging of the brain. The brain is surrounded by the poorly conducting skull which has low conductivity compared to the brain. The skull layer causes a partial shielding effect which leads to weak sensitivity for the imaging of the brain tissue. In this paper we propose an approach based on the Bayesian approximation error approach, to enhance the contrast in brain imaging. With this approach, both the (uninteresting) geometry and the conductivity of the skull are embedded in the approximation error statistics, which leads to a computationally efficient algorithm that is able to detect features such as internal haemorrhage with significantly increased sensitivity and specificity. We evaluate the approach with simulations and phantom data. (paper)

Contrast enhancement in EIT imaging of the brain.

Science.gov (United States)

Nissinen, A; Kaipio, J P; Vauhkonen, M; Kolehmainen, V

2016-01-01

We consider electrical impedance tomography (EIT) imaging of the brain. The brain is surrounded by the poorly conducting skull which has low conductivity compared to the brain. The skull layer causes a partial shielding effect which leads to weak sensitivity for the imaging of the brain tissue. In this paper we propose an approach based on the Bayesian approximation error approach, to enhance the contrast in brain imaging. With this approach, both the (uninteresting) geometry and the conductivity of the skull are embedded in the approximation error statistics, which leads to a computationally efficient algorithm that is able to detect features such as internal haemorrhage with significantly increased sensitivity and specificity. We evaluate the approach with simulations and phantom data.

2-d spectroscopic imaging of brain tumours

International Nuclear Information System (INIS)

Ferris, N.J.; Brotchie, P.R.

2002-01-01

Full text: This poster illustrates the use of two-dimensional spectroscopic imaging (2-D SI) in the characterisation of brain tumours, and the monitoring of subsequent treatment. After conventional contrast-enhanced MR imaging of patients with known or suspected brain tumours, 2-D SI is performed at a single axial level. The level is chosen to include the maximum volume of abnormal enhancement, or, in non-enhancing lesions. The most extensive T2 signal abnormality. Two different MR systems have been used (Marconi Edge and GE Signa LX); at each site, a PRESS localisation sequence is employed with TE 128-144 ms. Automated software is used to generate spectral arrays, metabolite maps, and metabolite ratio maps from the spectroscopic data. Colour overlays of the maps onto anatomical images are produced using manufacturer software or the Medex imaging data analysis package. High grade gliomas showed choline levels higher than those in apparently normal brain, with decreases in NAA and creatine. Some lesions showed spectral abnormality extending into otherwise normal appearing brain. This was also seen in a case of CNS lymphoma. Lowgrade lesions showed choline levels similar to normal brain, but with decreased NAA. Only a small number of metastases have been studied, but to date no metastasis has shown spectral abnormality beyond the margins suggested by conventional imaging. Follow-up studies generally show spectral heterogeneity. Regions with choline levels higher than those in normal-appearing brain are considered to represent recurrent high-grade tumour. Some regions show choline to be the dominant metabolite, but its level is not greater than that seen in normal brain. These regions are considered suspicious for residual / recurrent tumour when the choline / creatine ratio exceeds 2 (lower ratios may represent treatment effect). 2-D SI improves the initial assessment of brain tumours, and has potential for influencing the radiotherapy treatment strategy. 2-D SI also

Look again: effects of brain images and mind-brain dualism on lay evaluations of research.

Science.gov (United States)

Hook, Cayce J; Farah, Martha J

2013-09-01

Brain scans have frequently been credited with uniquely seductive and persuasive qualities, leading to claims that fMRI research receives a disproportionate share of public attention and funding. It has been suggested that functional brain images are fascinating because they contradict dualist beliefs regarding the relationship between the body and the mind. Although previous research has indicated that brain images can increase judgments of an article's scientific reasoning, the hypotheses that brain scans make research appear more interesting, surprising, or worthy of funding have not been tested. Neither has the relation between the allure of brain imaging and dualism. In the following three studies, laypersons rated both fictional research descriptions and real science news articles accompanied by brain scans, bar charts, or photographs. Across 988 participants, we found little evidence of neuroimaging's seductive allure or of its relation to self-professed dualistic beliefs. These results, taken together with other recent null findings, suggest that brain images are less powerful than has been argued.

Postmortem magnetic resonance images of the injured brain: effective evidence in the courtroom.

Science.gov (United States)

Harris, L S

1991-09-01

Magnetic resonance images (MRI) of the whole, formalin-fixed brain produce details of pathologic changes deep within brain substance not apparent on external examination. Photographs of these radiographic images present pathologic features in a black-and-white, 2-dimensional format which has proven particularly effective in court before judge and jury. This pathologist has noted acceptance of such photographs in explaining to jurors the details of his testimony in selected cases where brain trauma resulted in a wrongful death. Penetrating missile wounds and blunt impact injuries are particularly well documented by this method.

A simple rapid process for semi-automated brain extraction from magnetic resonance images of the whole mouse head.

Science.gov (United States)

Delora, Adam; Gonzales, Aaron; Medina, Christopher S; Mitchell, Adam; Mohed, Abdul Faheem; Jacobs, Russell E; Bearer, Elaine L

2016-01-15

Magnetic resonance imaging (MRI) is a well-developed technique in neuroscience. Limitations in applying MRI to rodent models of neuropsychiatric disorders include the large number of animals required to achieve statistical significance, and the paucity of automation tools for the critical early step in processing, brain extraction, which prepares brain images for alignment and voxel-wise statistics. This novel timesaving automation of template-based brain extraction ("skull-stripping") is capable of quickly and reliably extracting the brain from large numbers of whole head images in a single step. The method is simple to install and requires minimal user interaction. This method is equally applicable to different types of MR images. Results were evaluated with Dice and Jacquard similarity indices and compared in 3D surface projections with other stripping approaches. Statistical comparisons demonstrate that individual variation of brain volumes are preserved. A downloadable software package not otherwise available for extraction of brains from whole head images is included here. This software tool increases speed, can be used with an atlas or a template from within the dataset, and produces masks that need little further refinement. Our new automation can be applied to any MR dataset, since the starting point is a template mask generated specifically for that dataset. The method reliably and rapidly extracts brain images from whole head images, rendering them useable for subsequent analytical processing. This software tool will accelerate the exploitation of mouse models for the investigation of human brain disorders by MRI. Copyright © 2015 Elsevier B.V. All rights reserved.

Magnetic resonance imaging acquisition techniques intended to decrease movement artefact in paediatric brain imaging: a systematic review

International Nuclear Information System (INIS)

Woodfield, Julie; Kealey, Susan

2015-01-01

Attaining paediatric brain images of diagnostic quality can be difficult because of young age or neurological impairment. The use of anaesthesia to reduce movement in MRI increases clinical risk and cost, while CT, though faster, exposes children to potentially harmful ionising radiation. MRI acquisition techniques that aim to decrease movement artefact may allow diagnostic paediatric brain imaging without sedation or anaesthesia. We conducted a systematic review to establish the evidence base for ultra-fast sequences and sequences using oversampling of k-space in paediatric brain MR imaging. Techniques were assessed for imaging time, occurrence of movement artefact, the need for sedation, and either image quality or diagnostic accuracy. We identified 24 relevant studies. We found that ultra-fast techniques had shorter imaging acquisition times compared to standard MRI. Techniques using oversampling of k-space required equal or longer imaging times than standard MRI. Both ultra-fast sequences and those using oversampling of k-space reduced movement artefact compared with standard MRI in unsedated children. Assessment of overall diagnostic accuracy was difficult because of the heterogeneous patient populations, imaging indications, and reporting methods of the studies. In children with shunt-treated hydrocephalus there is evidence that ultra-fast MRI is sufficient for the assessment of ventricular size. (orig.)

Magnetic resonance imaging acquisition techniques intended to decrease movement artefact in paediatric brain imaging: a systematic review

Energy Technology Data Exchange (ETDEWEB)

Woodfield, Julie [University of Edinburgh, Child Life and Health, Edinburgh (United Kingdom); Kealey, Susan [Western General Hospital, Department of Neuroradiology, Edinburgh (United Kingdom)

2015-08-15

Attaining paediatric brain images of diagnostic quality can be difficult because of young age or neurological impairment. The use of anaesthesia to reduce movement in MRI increases clinical risk and cost, while CT, though faster, exposes children to potentially harmful ionising radiation. MRI acquisition techniques that aim to decrease movement artefact may allow diagnostic paediatric brain imaging without sedation or anaesthesia. We conducted a systematic review to establish the evidence base for ultra-fast sequences and sequences using oversampling of k-space in paediatric brain MR imaging. Techniques were assessed for imaging time, occurrence of movement artefact, the need for sedation, and either image quality or diagnostic accuracy. We identified 24 relevant studies. We found that ultra-fast techniques had shorter imaging acquisition times compared to standard MRI. Techniques using oversampling of k-space required equal or longer imaging times than standard MRI. Both ultra-fast sequences and those using oversampling of k-space reduced movement artefact compared with standard MRI in unsedated children. Assessment of overall diagnostic accuracy was difficult because of the heterogeneous patient populations, imaging indications, and reporting methods of the studies. In children with shunt-treated hydrocephalus there is evidence that ultra-fast MRI is sufficient for the assessment of ventricular size. (orig.)

Impact of metal artefacts due to EEG electrodes in brain PET/CT imaging

International Nuclear Information System (INIS)

Lemmens, Catherine; Nuyts, Johan; Dupont, Patrick; Montandon, Marie-Louise; Ratib, Osman; Zaidi, Habib

2008-01-01

The goal of this study is to investigate the impact of electroencephalogram (EEG) electrodes on the visual quality and quantification of 18 F-FDG PET images in neurological PET/CT examinations. For this purpose, the scans of 20 epilepsy patients with EEG monitoring were used. The CT data were reconstructed with filtered backprojection (FBP) and with a metal artefact reduction (MAR) algorithm. Both data sets were used for CT-based attenuation correction (AC) of the PET data. Also, a calculated AC (CALC) technique was considered. A volume of interest (VOI)-based analysis and a voxel-based quantitative analysis were performed to compare the different AC methods. Images were also evaluated visually by two observers. It was shown with simulations and phantom measurements that from the considered AC methods, the MAR-AC can be used as the reference in this setting. The visual assessment of PET images showed local hot spots outside the brain corresponding to the locations of the electrodes when using FBP-AC. In the brain, no abnormalities were observed. The quantitative analysis showed a very good correlation between PET-FBP-AC and PET-MAR-AC, with a statistically significant positive bias in the PET-FBP-AC images of about 5-7% in most brain voxels. There was also good correlation between PET-CALC-AC and PET-MAR-AC, but in the PET-CALC-AC images, regions with both a significant positive and negative bias were observed. EEG electrodes give rise to local hot spots outside the brain and a positive quantification bias in the brain. However, when diagnosis is made by mere visual assessment, the presence of EEG electrodes does not seem to alter the diagnosis. When quantification is performed, the bias becomes an issue especially when comparing brain images with and without EEG monitoring

Impact of metal artefacts due to EEG electrodes in brain PET/CT imaging

Energy Technology Data Exchange (ETDEWEB)

Lemmens, Catherine; Nuyts, Johan; Dupont, Patrick [Department of Nuclear Medicine and Medical Imaging Center, University Hospital Gasthuisberg and Katholieke Universiteit Leuven, Leuven (Belgium); Montandon, Marie-Louise; Ratib, Osman; Zaidi, Habib [Division of Nuclear Medicine, Geneva University Hospital, CH-1211 Geneva (Switzerland)], E-mail: catherine.lemmens@uz.kuleuven.be

2008-08-21

The goal of this study is to investigate the impact of electroencephalogram (EEG) electrodes on the visual quality and quantification of {sup 18}F-FDG PET images in neurological PET/CT examinations. For this purpose, the scans of 20 epilepsy patients with EEG monitoring were used. The CT data were reconstructed with filtered backprojection (FBP) and with a metal artefact reduction (MAR) algorithm. Both data sets were used for CT-based attenuation correction (AC) of the PET data. Also, a calculated AC (CALC) technique was considered. A volume of interest (VOI)-based analysis and a voxel-based quantitative analysis were performed to compare the different AC methods. Images were also evaluated visually by two observers. It was shown with simulations and phantom measurements that from the considered AC methods, the MAR-AC can be used as the reference in this setting. The visual assessment of PET images showed local hot spots outside the brain corresponding to the locations of the electrodes when using FBP-AC. In the brain, no abnormalities were observed. The quantitative analysis showed a very good correlation between PET-FBP-AC and PET-MAR-AC, with a statistically significant positive bias in the PET-FBP-AC images of about 5-7% in most brain voxels. There was also good correlation between PET-CALC-AC and PET-MAR-AC, but in the PET-CALC-AC images, regions with both a significant positive and negative bias were observed. EEG electrodes give rise to local hot spots outside the brain and a positive quantification bias in the brain. However, when diagnosis is made by mere visual assessment, the presence of EEG electrodes does not seem to alter the diagnosis. When quantification is performed, the bias becomes an issue especially when comparing brain images with and without EEG monitoring.

Magnetic resonance imaging in brain-stem tumors

International Nuclear Information System (INIS)

Nomura, Mikio; Saito, Hisazumi; Akino, Minoru; Abe, Hiroshi.

1988-01-01

Four patients with brain-stem tumors underwent magnetic resonance imaging (MRI) before and after radiotherapy. The brain-stem tumors were seen as a low signal intensity on T1-weighted images and as a high signal intensity on T2-weighted images. A tumor and its anatomic involvement were more clearly visualized on MRI than on cuncurrently performed CT. Changes in tumor before and after radiotherapy could be determined by measuring the diameter of tumor on sagittal and coronal images. This allowed quantitative evaluation of the reduction of tumor in association with improvement of symptoms. The mean T1 value in the central part of tumors was shortened in all patients after radiotherapy. The results indicate that MRI may assist in determining the effect of radiotherapy for brain-stem tumors. (Namekawa, K)

Imaging biomarkers in primary brain tumours

Energy Technology Data Exchange (ETDEWEB)

Lopci, Egesta; Chiti, Arturo [Humanitas Clinical and Research Center, Nuclear Medicine Department, Rozzano, MI (Italy); Franzese, Ciro; Navarria, Pierina; Scorsetti, Marta [Humanitas Clinical and Research Center, Radiosurgery and Radiotherapy, Rozzano, MI (Italy); Grimaldi, Marco [Humanitas Clinical and Research Center, Radiology, Rozzano, MI (Italy); Zucali, Paolo Andrea; Simonelli, Matteo [Humanitas Clinical and Research Center, Medical Oncology, Rozzano, MI (Italy); Bello, Lorenzo [Humanitas Clinical and Research Center, Neurosurgery, Rozzano, MI (Italy)

2015-04-01

We are getting used to referring to instrumentally detectable biological features in medical language as ''imaging biomarkers''. These two terms combined reflect the evolution of medical imaging during recent decades, and conceptually comprise the principle of noninvasive detection of internal processes that can become targets for supplementary therapeutic strategies. These targets in oncology include those biological pathways that are associated with several tumour features including independence from growth and growth-inhibitory signals, avoidance of apoptosis and immune system control, unlimited potential for replication, self-sufficiency in vascular supply and neoangiogenesis, acquired tissue invasiveness and metastatic diffusion. Concerning brain tumours, there have been major improvements in neurosurgical techniques and radiotherapy planning, and developments of novel target drugs, thus increasing the need for reproducible, noninvasive, quantitative imaging biomarkers. However, in this context, conventional radiological criteria may be inappropriate to determine the best therapeutic option and subsequently to assess response to therapy. Integration of molecular imaging for the evaluation of brain tumours has for this reason become necessary, and an important role in this setting is played by imaging biomarkers in PET and MRI. In the current review, we describe most relevant techniques and biomarkers used for imaging primary brain tumours in clinical practice, and discuss potential future developments from the experimental context. (orig.)

A pilot study of three dimensional color CT images of brain diseases to improve informed consent

International Nuclear Information System (INIS)

Tanizaki, Yoshio; Akiyama, Takenori; Hiraga, Kenji; Akaji, Kazunori

2005-01-01

We have described brain diseases to patients and their family using monochrome CT images. It is thought that patients have difficulties in giving their consent to our conventional explanation because their understanding of brain diseases is based on three dimensional and color images, however, standard CT images are two dimensional and gray scale images. We have been trying to use three dimensional color CT images to improve the typical patient's comprehension of brain diseases. We also try to simulate surgery using these images. Multi-slice CT accumulates precise isotropic voxel data within a half minute. These two dimensional and monochrome data are converted to three dimensional color CT images by 3D workstation. Three dimensional color CT images of each brain structures (e.g. scalp, skull, brain, ventricles and lesions) are created separately. Then, selected structures are fused together for different purposes. These images are able to rotate around any axis. Because the methods to generate three-dimensional color images have not established, we neurosurgeons must create these images. In particular, when an operation is required, the surgeon should create the images. In this paper, we demonstrate how three-dimensional color CT images can improve informed consent. (author)

State-of-the-Art Methods for Brain Tissue Segmentation: A Review.

Science.gov (United States)

Dora, Lingraj; Agrawal, Sanjay; Panda, Rutuparna; Abraham, Ajith

2017-01-01

Brain tissue segmentation is one of the most sought after research areas in medical image processing. It provides detailed quantitative brain analysis for accurate disease diagnosis, detection, and classification of abnormalities. It plays an essential role in discriminating healthy tissues from lesion tissues. Therefore, accurate disease diagnosis and treatment planning depend merely on the performance of the segmentation method used. In this review, we have studied the recent advances in brain tissue segmentation methods and their state-of-the-art in neuroscience research. The review also highlights the major challenges faced during tissue segmentation of the brain. An effective comparison is made among state-of-the-art brain tissue segmentation methods. Moreover, a study of some of the validation measures to evaluate different segmentation methods is also discussed. The brain tissue segmentation, content in terms of methodologies, and experiments presented in this review are encouraging enough to attract researchers working in this field.

An accurate segmentation method for volumetry of brain tumor in 3D MRI

Science.gov (United States)

Wang, Jiahui; Li, Qiang; Hirai, Toshinori; Katsuragawa, Shigehiko; Li, Feng; Doi, Kunio

2008-03-01

Accurate volumetry of brain tumors in magnetic resonance imaging (MRI) is important for evaluating the interval changes in tumor volumes during and after treatment, and also for planning of radiation therapy. In this study, an automated volumetry method for brain tumors in MRI was developed by use of a new three-dimensional (3-D) image segmentation technique. First, the central location of a tumor was identified by a radiologist, and then a volume of interest (VOI) was determined automatically. To substantially simplify tumor segmentation, we transformed the 3-D image of the tumor into a two-dimensional (2-D) image by use of a "spiral-scanning" technique, in which a radial line originating from the center of the tumor scanned the 3-D image spirally from the "north pole" to the "south pole". The voxels scanned by the radial line provided a transformed 2-D image. We employed dynamic programming to delineate an "optimal" outline of the tumor in the transformed 2-D image. We then transformed the optimal outline back into 3-D image space to determine the volume of the tumor. The volumetry method was trained and evaluated by use of 16 cases with 35 brain tumors. The agreement between tumor volumes provided by computer and a radiologist was employed as a performance metric. Our method provided relatively accurate results with a mean agreement value of 88%.

A New Variational Method for Bias Correction and Its Applications to Rodent Brain Extraction.

Science.gov (United States)

Chang, Huibin; Huang, Weimin; Wu, Chunlin; Huang, Su; Guan, Cuntai; Sekar, Sakthivel; Bhakoo, Kishore Kumar; Duan, Yuping

2017-03-01

Brain extraction is an important preprocessing step for further analysis of brain MR images. Significant intensity inhomogeneity can be observed in rodent brain images due to the high-field MRI technique. Unlike most existing brain extraction methods that require bias corrected MRI, we present a high-order and L 0 regularized variational model for bias correction and brain extraction. The model is composed of a data fitting term, a piecewise constant regularization and a smooth regularization, which is constructed on a 3-D formulation for medical images with anisotropic voxel sizes. We propose an efficient multi-resolution algorithm for fast computation. At each resolution layer, we solve an alternating direction scheme, all subproblems of which have the closed-form solutions. The method is tested on three T2 weighted acquisition configurations comprising a total of 50 rodent brain volumes, which are with the acquisition field strengths of 4.7 Tesla, 9.4 Tesla and 17.6 Tesla, respectively. On one hand, we compare the results of bias correction with N3 and N4 in terms of the coefficient of variations on 20 different tissues of rodent brain. On the other hand, the results of brain extraction are compared against manually segmented gold standards, BET, BSE and 3-D PCNN based on a number of metrics. With the high accuracy and efficiency, our proposed method can facilitate automatic processing of large-scale brain studies.

Novel region of interest interrogation technique for diffusion tensor imaging analysis in the canine brain.

Science.gov (United States)

Li, Jonathan Y; Middleton, Dana M; Chen, Steven; White, Leonard; Ellinwood, N Matthew; Dickson, Patricia; Vite, Charles; Bradbury, Allison; Provenzale, James M

2017-08-01

Purpose We describe a novel technique for measuring diffusion tensor imaging metrics in the canine brain. We hypothesized that a standard method for region of interest placement could be developed that is highly reproducible, with less than 10% difference in measurements between raters. Methods Two sets of canine brains (three seven-week-old full-brains and two 17-week-old single hemispheres) were scanned ex-vivo on a 7T small-animal magnetic resonance imaging system. Strict region of interest placement criteria were developed and then used by two raters to independently measure diffusion tensor imaging metrics within four different white-matter regions within each specimen. Average values of fractional anisotropy, radial diffusivity, and the three eigenvalues (λ1, λ2, and λ3) within each region in each specimen overall and within each individual image slice were compared between raters by calculating the percentage difference between raters for each metric. Results The mean percentage difference between raters for all diffusion tensor imaging metrics when pooled by each region and specimen was 1.44% (range: 0.01-5.17%). The mean percentage difference between raters for all diffusion tensor imaging metrics when compared by individual image slice was 2.23% (range: 0.75-4.58%) per hemisphere. Conclusion Our results indicate that the technique described is highly reproducible, even when applied to canine specimens of differing age, morphology, and image resolution. We propose this technique for future studies of diffusion tensor imaging analysis in canine brains and for cross-sectional and longitudinal studies of canine brain models of human central nervous system disease.

MR imaging assisted radiation therapy planning of brain tumors

International Nuclear Information System (INIS)

Just, M.; Roesler, H.P.; Higer, H.P.; Kutzner, J.; Thelen, M.

1990-01-01

This paper reports on the improvement of the accuracy of treatment portals in radiation therapy of brain tumors with use of MR imaging. After proper processing, the parasagittal MR image showing the largest tumor size and the midline sagittal image were superimposed. With common anatomic landmarks of midline tomogram and lateral simulation radiograph, commensurate reference grids were laid over both images in identical positions. Tumor coordinates were then transferred from the synthesized MR image to the lateral radiograph. Rectangular fields or individual shielding blocks encompassing the tumor could be drawn directly. This new method was used in 17 patients, and results were compared with CT-assisted results

Cortical region of interest definition on SPECT brain images using X-ray CT registration

Energy Technology Data Exchange (ETDEWEB)

Tzourio, N.; Sutton, D. (Commissariat a l' Energie Atomique, Orsay (France). Service Hospitalier Frederic Joliot); Joliot, M. (Commissariat a l' Energie Atomique, Orsay (France). Service Hospitalier Frederic Joliot INSERM, Orsay (France)); Mazoyer, B.M. (Commissariat a l' Energie Atomique, Orsay (France). Service Hospitalier Frederic Joliot Antenne d' Information Medicale, C.H.U. Bichat, Paris (France)); Charlot, V. (Hopital Louis Mourier, Colombes (France). Service de Psychiatrie); Salamon, G. (CHU La Timone, Marseille (France). Service de Neuroradiologie)

1992-11-01

We present a method for brain single photon emission computed tomography (SPECT) analysis based on individual registration of anatomical (CT) and functional ([sup 133]Xe regional cerebral blood flow) images and on the definition of three-dimensional functional regions of interest. Registration of CT and SPECT is performed through adjustment of CT-defined cortex limits to the SPECT image. Regions are defined by sectioning a cortical ribbon on the CT images, copied over the SPECT images and pooled through slices to give 3D cortical regions of interest. The proposed method shows good intra- and interobserver reproducibility (regional intraclass correlation coefficient [approx equal]0.98), and good accuracy in terms of repositioning ([approx equal]3.5 mm) as compared to the SPECT image resolution (14 mm). The method should be particularly useful for analysing SPECT studies when variations in brain anatomy (normal or abnormal) must be accounted for. (orig.).

Indian-ink perfusion based method for reconstructing continuous vascular networks in whole mouse brain.

Directory of Open Access Journals (Sweden)

Songchao Xue

Full Text Available The topology of the cerebral vasculature, which is the energy transport corridor of the brain, can be used to study cerebral circulatory pathways. Limited by the restrictions of the vascular markers and imaging methods, studies on cerebral vascular structure now mainly focus on either observation of the macro vessels in a whole brain or imaging of the micro vessels in a small region. Simultaneous vascular studies of arteries, veins and capillaries have not been achieved in the whole brain of mammals. Here, we have combined the improved gelatin-Indian ink vessel perfusion process with Micro-Optical Sectioning Tomography for imaging the vessel network of an entire mouse brain. With 17 days of work, an integral dataset for the entire cerebral vessels was acquired. The voxel resolution is 0.35×0.4×2.0 µm(3 for the whole brain. Besides the observations of fine and complex vascular networks in the reconstructed slices and entire brain views, a representative continuous vascular tracking has been demonstrated in the deep thalamus. This study provided an effective method for studying the entire macro and micro vascular networks of mouse brain simultaneously.

Brain imaging

International Nuclear Information System (INIS)

Bradshaw, J.R.

1989-01-01

This book presents a survey of the various imaging tools with examples of the different diseases shown best with each modality. It includes 100 case presentations covering the gamut of brain diseases. These examples are grouped according to the clinical presentation of the patient: headache, acute headache, sudden unilateral weakness, unilateral weakness of gradual onset, speech disorders, seizures, pituitary and parasellar lesions, sensory disorders, posterior fossa and cranial nerve disorders, dementia, and congenital lesions

The reliability of magnetic resonance imaging in traumatic brain injury lesion detection

NARCIS (Netherlands)

Geurts, B.H.J.; Andriessen, T.M.J.C.; Goraj, B.M.; Vos, P.E.

2012-01-01

Objective: This study compares inter-rater-reliability, lesion detection and clinical relevance of T2-weighted imaging (T2WI), Fluid Attenuated Inversion Recovery (FLAIR), T2*-gradient recalled echo (T2*-GRE) and Susceptibility Weighted Imaging (SWI) in Traumatic Brain Injury (TBI). Methods: Three

Retractor-induced brain shift compensation in image-guided neurosurgery

Science.gov (United States)

Fan, Xiaoyao; Ji, Songbai; Hartov, Alex; Roberts, David; Paulsen, Keith

2013-03-01

In image-guided neurosurgery, intraoperative brain shift significantly degrades the accuracy of neuronavigation that is solely based on preoperative magnetic resonance images (pMR). To compensate for brain deformation and to maintain the accuracy in image guidance achieved at the start of surgery, biomechanical models have been developed to simulate brain deformation and to produce model-updated MR images (uMR) to compensate for brain shift. To-date, most studies have focused on shift compensation at early stages of surgery (i.e., updated images are only produced after craniotomy and durotomy). Simulating surgical events at later stages such as retraction and tissue resection are, perhaps, clinically more relevant because of the typically much larger magnitudes of brain deformation. However, these surgical events are substantially more complex in nature, thereby posing significant challenges in model-based brain shift compensation strategies. In this study, we present results from an initial investigation to simulate retractor-induced brain deformation through a biomechanical finite element (FE) model where whole-brain deformation assimilated from intraoperative data was used produce uMR for improved accuracy in image guidance. Specifically, intensity-encoded 3D surface profiles at the exposed cortical area were reconstructed from intraoperative stereovision (iSV) images before and after tissue retraction. Retractor-induced surface displacements were then derived by coregistering the surfaces and served as sparse displacement data to drive the FE model. With one patient case, we show that our technique is able to produce uMR that agrees well with the reconstructed iSV surface after retraction. The computational cost to simulate retractor-induced brain deformation was approximately 10 min. In addition, our approach introduces minimal interruption to the surgical workflow, suggesting the potential for its clinical application.

Detection of brain metastasis. Comparison of Turbo-FLAIR imaging, T2-weighted imaging and double-dose gadolinium-enhanced MR imaging

International Nuclear Information System (INIS)

Okubo, Toshiyuki; Hayashi, Naoto; Shirouzu, Ichiro; Abe, Osamu; Ohtomo, Kuni; Sasaki, Yasuhito; Aoki, Shigeki; Wada, Akihiko

1998-01-01

The purpose of this study was to compare Turbo-FLAIR imaging, T 2 -weighted imaging, and double-dose gadolinium-enhanced MR imaging in the detection of brain metastasis. Using the three sequences, 20 consecutive patients with brain metastases were prospectively studied with a 1.5-Tesla system. Three independent, blinded readers assessed the images for the presence, size, number, and location of metastatic lesions. In the detection of large lesions (>0.5 cm), Turbo-FLAIR imaging (38/48, 79%) was not significantly different from gadolinium-enhanced imaging (42/48, 88%) (p=0.273). T 2 -weighted imaging (31/48, 65%), however, was inferior to gadolinium-enhanced imaging (p<0.05). There was no difference between Turbo-FLAIR imaging and gadolinium-enhanced imaging in the accuracy of detecting solitary brain metastasis (4/4, 100%). In conclusion, Turbo-FLAIR imaging is a useful, noninvasive screening modality for brain metastasis. Its use may lead to cost savings in the diagnosis of brain metastases and may impact positively the cost-effectiveness of treatment. (author)

Obsessive-compulsive disorder: advances in brain imaging

International Nuclear Information System (INIS)

Galli, Enrique

2000-01-01

In the past twenty years functional brain imaging has advanced to the point of tackling the differential diagnosis, prognosis and therapeutic response in Neurology and Psychiatry. Psychiatric disorders were rendered 'functional' a century ago; however nowadays they can be seen by means of brain imaging. Functional images in positron emission tomography (PET) and single photon emission tomography (NEUROSPET) show in non-invasive fashion the state of brain functioning. PET does this assessing glucose metabolism and NEUROSPET by putting cerebral blood flow in images. Prevalence of OCD is clearly low (2 to 3%), but comorbidity with depression, psychoses, bipolar disorder and schizophrenia is high. Furthermore, it is not infrequent with autism, attention disorder, tichotillomany, borderline personality disorders, in pathological compulsive spending, sexual compulsion and in pathological gambling, in tics, and in Gilles de la Tourette disorder, NEUROSPET and PET show hypoperfusion in both frontal lobes, in their prefrontal dorsolateral aspects, in their inferior zone and premotor cortex, with hyperperfusion in the posterior cingulum and hypoperfusion in basal ganglia (caudate nucleus). Cummings states that hyperactivity of the limbic system might be involved in OCD. Thus, brain imaging in OCD is a diagnostic aid, allows us to see clinical imagenological evolution and therapeutic response and, possibly, it is useful predict therapeutic response (Au)

Three-dimensional reconstruction of brain surface anatomy: technique comparison between flash and diffusion-weighted imaging

International Nuclear Information System (INIS)

Sun Jianzhong; Wang Zhikang; Gong Xiangyang

2006-01-01

Objective: To compare two methods 3D flash and diffusion-weighted images (DWI) in reconstructing the brain surface anatomy, and to evaluate their displaying ability, advantages, limitations and clinical application. Methods: Thrity normal cases were prospectively examined with 3D flash sequence and echo-planar DWI. Three-dimensional images were acquired with volume-rendering on workstation. Brain surface structures were evaluated and scored by a group of doctors. Results: Main structures of brain surface were clearly displayed on three-dimensional images based on 3D flash sequence. Average scores were all above 2.50. For images based on DWI, precentral gyrus, postcentral gyrus, superior parietal lobule, superior frontal gyrus, precentral sulcus, central sulcus, postcentral sulcus, intraparietal sulcus and superior frontal sulcus were best shown with average scores between 2.60-2.75, However, supramarginal gyrus, angular gyrus, middle frontal gyrus, inferior frontal gyrus, superior temporal gyrus, lateral sulcus, inferior frontal sulcus could not be well shown, with average scores between 1.67-2.48. Middle temporal gyrus, inferior temporal gyrus, superior temporal sulcus and inferior temporal sulcus can only get scores from 0.88 to 1.27. Scores of images based on 3D flash were much higher than that based on DWI with distinct differentiations, P values were all below 0.01. Conclusion: Three-dimensional images based on 3D flash can really display brain surface structures. It is very useful for anatomic researches. Three-dimensional reconstruction of brain surface based on DWI is a worthy technique to display brain surface anatomy, especially for frontal and parietal structures. (authors)

Brain Magnetic Resonance Imaging Findings in Developmentally Delayed Children

Directory of Open Access Journals (Sweden)

Ali Akbar Momen

2011-01-01

Full Text Available Background. Developmental disorders are failure or inability to acquire various age-specific skills at expected maturational age, which affects about 5–10% of preschool children. One of the most important methods for evaluation of developmentally delayed children is neuroimaging, especially, brain magnetic resonance imaging (MRI that provides useful information regarding brain tissue structures and anomalies. Method and Material. In this study, hospital records of 580 developmentally delayed children (aged 2 months to 15 years who admitted in pediatric ward of Golestan Hospital from 1997 to 2009 were selected. Information such as age, MRI findings were collected in the questionnaire and statistically analyzed. Results. Total, 580 children including 333 males (57.4% and 247 females (42.6% were studied. Abnormal brain MRI was observed in 340 (58.6% cases (204 Males, 136 females. The finding includes nonspecific in 38 (6.6%, congenital and developmental anomalies of brain in 39 (6.7%, recognizable syndromes in 3 (0.5%, neurovascular diseases or trauma in 218 (37.6%, and metabolic or neurodegenerative diseases in 42 (7.2% cases. Conclusion. Because 60% of all study groups showed abnormal brain MRI, using this method could be effective in diagnosis, management, and almost prognosis determination processes.

Cluster imaging of multi-brain networks (CIMBN: a general framework for hyperscanning and modeling a group of interacting brains

Directory of Open Access Journals (Sweden)

Lian eDuan

2015-07-01

Full Text Available Studying the neural basis of human social interactions is a key topic in the field of social neuroscience. Brain imaging studies in this field usually focus on the neural correlates of the social interactions between two participants. However, as the participant number further increases, even by a small amount, great difficulties raise. One challenge is how to concurrently scan all the interacting brains with high ecological validity, especially for a large number of participants. The other challenge is how to effectively model the complex group interaction behaviors emerging from the intricate neural information exchange among a group of socially organized people. Confronting these challenges, we propose a new approach called Cluster Imaging of Multi-brain Networks (CIMBN. CIMBN consists of two parts. The first part is a cluster imaging technique with high ecological validity based on multiple functional near-infrared spectroscopy (fNIRS systems. Using this technique, we can easily extend the simultaneous imaging capacity of social neuroscience studies up to dozens of participants. The second part of CIMBN is a multi-brain network (MBN modeling method based on graph theory. By taking each brain as a network node and the relationship between any two brains as a network edge, one can construct a network model for a group of interacting brains. The emergent group social behaviors can then be studied using the network’s properties, such as its topological structure and information exchange efficiency. Although there is still much work to do, as a general framework for hyperscanning and modeling a group of interacting brains, CIMBN can provide new insights into the neural correlates of group social interactions, and advance social neuroscience and social psychology.

Fractal characterization of brain lesions in CT images

International Nuclear Information System (INIS)

Jauhari, Rajnish K.; Trivedi, Rashmi; Munshi, Prabhat; Sahni, Kamal

2005-01-01

Fractal Dimension (FD) is a parameter used widely for classification, analysis, and pattern recognition of images. In this work we explore the quantification of CT (computed tomography) lesions of the brain by using fractal theory. Five brain lesions, which are portions of CT images of diseased brains, are used for the study. These lesions exhibit self-similarity over a chosen range of scales, and are broadly characterized by their fractal dimensions

Functional imaging for brain tumors (perfusion, DTI and MR spectroscopy)

International Nuclear Information System (INIS)

Essig, M.; Giesel, F.; Stieltjes, B.; Weber, M.A.

2007-01-01

This contribution considers the possibilities involved with using functional methods in magnetic resonance imaging (MRI) diagnostics for brain tumors. Of the functional methods available, we discuss perfusion MRI (PWI), diffusion MRI (DWI and DTI) and MR spectroscopy (H-MRS). In cases of brain tumor, PWI aids in grading and better differentiation in diagnostics as well as for pre-therapeutic planning. In addition, the course of treatment, both after chemo- as well as radiotherapy in combination with surgical treatment, can be optimized. PWI allows better estimates of biological activity and aggressiveness in low grade brain tumors, and in the case of WHO grade II astrocytoma showing anaplastically transformed tumor areas, allows more rapid visualization and a better prediction of the course of the disease than conventional MRI diagnostics. Diffusion MRI, due to the directional dependence of the diffusion, can illustrate the course and direction of the nerve fibers, as well as reconstructing the nerve tracts in the cerebrum, pons and cerebellum 3-dimensionally. Diffusion imaging can be used for describing brain tumors, for evaluating contralateral involvement and the course of the nerve fibers near the tumor. Due to its operator dependence, DTI based fiber tracking for defining risk structures is controversial. DWI can also not differentiate accurately between cystic and necrotic brain tumors, or between metastases and brain abscesses. H-MRS provides information on cell membrane metabolism, neuronal integrity and the function of neuronal structures, energy metabolism and the formation of tumors and brain tissue necroses. Diagnostic problems such as the differentiation between neoplastic and non-neoplastic lesions, grading cerebral glioma and distinguishing between primary brain tumors and metastases can be resolved. An additional contribution will discuss the control of the course of glial tumors after radiotherapy. (orig.)

Longitudinal changes in the brain in mild cognitive impairment: a magnetic resonance imaging study using the visual rating method and tensor-based morphometry.

Science.gov (United States)

Tuokkola, Terhi; Koikkalainen, Juha; Parkkola, Riitta; Karrasch, Mira; Lötjönen, Jyrki; Rinne, Juha O

2017-01-01

Background Brain atrophy is associated with mild cognitive impairment (MCI), and by using volumetric and visual analyzing methods, it is possible to differentiate between individuals with progressive MCI (MCIp) and stable MCI (MCIs). Automated analysis methods detect degenerative changes in the brain earlier and more reliably than visual methods. Purpose To detect and evaluate structural brain changes between and within the MCIs, MCIp, and control groups during a two-year follow-up period. Material and Methods Brain magnetic resonance imaging (MRI) scans of 11 participants with MCIs, 18 participants with MCIp, and 84 controls were analyzed by the visual rating method (VRM) and tensor-based morphometry (TBM). Results At baseline, both VRM and TBM differentiated the whole MCI group (combined MCIs and MCIp) and the MCIp group from the control group, but they did not differentiate the MCIs group from the control group. At follow-up, both methods differentiated the MCIp group from the control group, but minor differences between the MCIs and control groups were only seen by TBM. Neuropsychological tests did not find differences between the MCIs and control groups at follow-up. Neither method revealed relevant signs of brain atrophy progression within or between MCI subgroups during the follow-up time. Conclusion Both methods are equally good in the evaluation of structural brain changes in MCI if the groups are sufficiently large and the disease progresses to AD. Only TBM disclosed minor atrophic changes in the MCIs group compared to controls at follow-up. The results need to be confirmed with a large patient group and longer follow-up time.

Rough Sets and Stomped Normal Distribution for Simultaneous Segmentation and Bias Field Correction in Brain MR Images.

Science.gov (United States)

Banerjee, Abhirup; Maji, Pradipta

2015-12-01

The segmentation of brain MR images into different tissue classes is an important task for automatic image analysis technique, particularly due to the presence of intensity inhomogeneity artifact in MR images. In this regard, this paper presents a novel approach for simultaneous segmentation and bias field correction in brain MR images. It integrates judiciously the concept of rough sets and the merit of a novel probability distribution, called stomped normal (SN) distribution. The intensity distribution of a tissue class is represented by SN distribution, where each tissue class consists of a crisp lower approximation and a probabilistic boundary region. The intensity distribution of brain MR image is modeled as a mixture of finite number of SN distributions and one uniform distribution. The proposed method incorporates both the expectation-maximization and hidden Markov random field frameworks to provide an accurate and robust segmentation. The performance of the proposed approach, along with a comparison with related methods, is demonstrated on a set of synthetic and real brain MR images for different bias fields and noise levels.

LINKS: learning-based multi-source IntegratioN frameworK for Segmentation of infant brain images.

Science.gov (United States)

Wang, Li; Gao, Yaozong; Shi, Feng; Li, Gang; Gilmore, John H; Lin, Weili; Shen, Dinggang

2015-03-01

Segmentation of infant brain MR images is challenging due to insufficient image quality, severe partial volume effect, and ongoing maturation and myelination processes. In the first year of life, the image contrast between white and gray matters of the infant brain undergoes dramatic changes. In particular, the image contrast is inverted around 6-8months of age, and the white and gray matter tissues are isointense in both T1- and T2-weighted MR images and thus exhibit the extremely low tissue contrast, which poses significant challenges for automated segmentation. Most previous studies used multi-atlas label fusion strategy, which has the limitation of equally treating the different available image modalities and is often computationally expensive. To cope with these limitations, in this paper, we propose a novel learning-based multi-source integration framework for segmentation of infant brain images. Specifically, we employ the random forest technique to effectively integrate features from multi-source images together for tissue segmentation. Here, the multi-source images include initially only the multi-modality (T1, T2 and FA) images and later also the iteratively estimated and refined tissue probability maps of gray matter, white matter, and cerebrospinal fluid. Experimental results on 119 infants show that the proposed method achieves better performance than other state-of-the-art automated segmentation methods. Further validation was performed on the MICCAI grand challenge and the proposed method was ranked top among all competing methods. Moreover, to alleviate the possible anatomical errors, our method can also be combined with an anatomically-constrained multi-atlas labeling approach for further improving the segmentation accuracy. Copyright © 2014 Elsevier Inc. All rights reserved.

Imaging brain microstructure with diffusion MRI

DEFF Research Database (Denmark)

Alexander, Daniel C; Dyrby, Tim B; Nilsson, Markus

2018-01-01

This article gives an overview of microstructure imaging of the brain with diffusion MRI and reviews the state of the art. The microstructure-imaging paradigm aims to estimate and map microscopic properties of tissue using a model that links these properties to the voxel scale MR signal. Imaging ...

Dynamic Glucose Enhanced (DGE) MRI for Combined Imaging of Blood Brain Barrier Break Down and Increased Blood Volume in Brain Cancer

Science.gov (United States)

Xu, Xiang; Chan, Kannie WY; Knutsson, Linda; Artemov, Dmitri; Xu, Jiadi; Liu, Guanshu; Kato, Yoshinori; Lal, Bachchu; Laterra, John; McMahon, Michael T.; van Zijl, Peter C.M.

2015-01-01

Purpose Recently, natural d-glucose was suggested as a potential biodegradable contrast agent. The feasibility of using d-glucose for dynamic perfusion imaging was explored to detect malignant brain tumors based on blood brain barrier breakdown. Methods Mice were inoculated orthotopically with human U87-EGFRvIII glioma cells. Time-resolved glucose signal changes were detected using chemical exchange saturation transfer (glucoCEST) MRI. Dynamic glucose enhanced (DGE) MRI was used to measure tissue response to an intravenous bolus of d-glucose. Results DGE images of mouse brains bearing human glioma showed two times higher and persistent changes in tumor compared to contralateral brain. Area-under-curve (AUC) analysis of DGE delineated blood vessels and tumor and had contrast comparable to the AUC determined using dynamic contrast enhanced (DCE) MRI with GdDTPA, both showing a significantly higher AUC in tumor than in brain (pblood volume and permeability with respect to normal brain. We expect DGE will provide a low-risk and less expensive alternative to DCE MRI for imaging cancer in vulnerable populations, such as children and patients with renal impairment. PMID:26404120

Treatment of malignant brain tumor. Today and tomorrow. Image-guided neurosurgery for brain tumor. A current perspective

International Nuclear Information System (INIS)

Kajita, Yasukazu; Fujii, Masazumi; Yoshida, Jun; Maesawa, Satoshi

2008-01-01

Although usefulness of the image-guided neurosurgery is well documented, there are scarce facilities having the actually operating system in Japan. Since 2006, authors' Nagoya University Hospital has had an operating room named ''Brain THEATER'', where an open MRI system APERTO (Hitachi-Medical Co.) and a navigation system Vector Vision (BrainLAB) are connected to conduct the complete image-guided neurosurgery for brain tumor by using the intraoperative MRI for continuously updating the residual tumor tissue to be dissected out. The room is pre- and intra-operatively supported by Departments of image analysis and of radiation technology in the University, and as well, is connected by net-working with another image-guided surgical room ''Brain Suite'' (Siemens 1.5 T MRI system: BrainLAB) in the neighboring facility, Nagoya Central Hospital. This paper describes the circumstances of the introduction of these systems in the Hospital, details of the image-guided surgery in the operation rooms with illustration of actual photos of the rooms and of pre-, intra- and post-operative images, outcomes of image-guided neurosurgery for brain tumor reported hitherto, image-guided neurosurgery for brain tumor's future perspectives involving robotic surgery and operation on the virtual 3D image including the net-worked one. Efforts should be made to further spread the system for performing the more non-invasive and precise surgery, and for conducting the diagnosis united with treatment. (R.T.)

The clinical use of brain SPECT imaging in neuropsychiatry

International Nuclear Information System (INIS)

Amen, Daniel G; Wu, Joseph C; Carmichael, Blake

2003-01-01

This article reviews the literature on brain SPECT imaging in brain trauma, dementia, and temporal lobe epilepsy. Brain SPECT allows clinicians the ability to view cerebral areas of healthy, low, and excessive perfusion. This information can be correlated with what is known about the function or dysfunction of each area. SPECT has a number of advantages over other imaging techniques, including wider availability, lower cost, and high quality resolution with multi-headed cameras. There are a number of issues that compromise the effective use of SPECT, including low quality of some imaging cameras, and variability of image rendering and readings (Au)

Imaging findings of the brain abnormalities in acute lymphoblastic leukemia of children during and after treatment

International Nuclear Information System (INIS)

Lee, Kyung Joo; Lee, Seung Rho; Park, Dong Woo; Joo, Kyung Bin; Kim, Jang Wook; Hahm, Chang Kok; Kim, Ki Joong; Lee, Hahng

2001-01-01

We evaluated the imaging abnormalities of the brain observed during and after treatment of acute childhood lymphoblastic leukemia. The study group consisted of 30 patients (male : female=19 : 11 ; mean age, 64 months) with acute childhood lymphoblastic leukemia during the previous ten-year period who had undergone prophylaxis of the central nervous system. Irrespective of the CNS symptoms, base-line study of the brain involving CT and follow-up CT or MRI was undertaken more than once. We retrospectively evaluated the imaging findings, methods of treatment, associated CNS symptoms, and the interval between diagnosis and the time at which brain abnormalities were revealed by imaging studies. In 15 (50% ; male : female=9 : 6 ; mean age, 77 months) of 30 patients, brain abnormalities that included brain atrophy (n=9), cerebral infarctions (n=4), intracranial hemorrhage (n=1), mineralizing microangiopathy (n=2), and periventricular leukomalacia (n=3) were seen on follow-up CT or MR images. In four of nine patients with brain atrophy, imaging abnormalities such as periventricular leukomalacia (n=2), infarction (n=1) and microangiopathy (n=1) were demonstrated. Fourteen of the 15 patients underwent similar treatment ; the one excluded had leukemic cells in the CSF. Six patients had CNS symptoms. In the 15 patients with abnormal brain imaging findings, the interval between diagnosis and the demonstration of brain abnormalities was between one month and four years. After the cessation of treatment, imaging abnormalities remained in all patients except one with brain atrophy. Various imaging abnormalities of the brain may be seen during and after the treatment of acute childhood lymphoblastic leukemia and persist for a long time. In children with this condition, the assessment of brain abnormalities requires follow-up study of the brain

Imaging findings of the brain abnormalities in acute lymphoblastic leukemia of children during and after treatment

Energy Technology Data Exchange (ETDEWEB)

Lee, Kyung Joo; Lee, Seung Rho; Park, Dong Woo; Joo, Kyung Bin; Kim, Jang Wook; Hahm, Chang Kok; Kim, Ki Joong; Lee, Hahng [College of Medicine, Hanyang Univ., Seoul (Korea, Republic of)

2001-09-01

We evaluated the imaging abnormalities of the brain observed during and after treatment of acute childhood lymphoblastic leukemia. The study group consisted of 30 patients (male : female=19 : 11 ; mean age, 64 months) with acute childhood lymphoblastic leukemia during the previous ten-year period who had undergone prophylaxis of the central nervous system. Irrespective of the CNS symptoms, base-line study of the brain involving CT and follow-up CT or MRI was undertaken more than once. We retrospectively evaluated the imaging findings, methods of treatment, associated CNS symptoms, and the interval between diagnosis and the time at which brain abnormalities were revealed by imaging studies. In 15 (50% ; male : female=9 : 6 ; mean age, 77 months) of 30 patients, brain abnormalities that included brain atrophy (n=9), cerebral infarctions (n=4), intracranial hemorrhage (n=1), mineralizing microangiopathy (n=2), and periventricular leukomalacia (n=3) were seen on follow-up CT or MR images. In four of nine patients with brain atrophy, imaging abnormalities such as periventricular leukomalacia (n=2), infarction (n=1) and microangiopathy (n=1) were demonstrated. Fourteen of the 15 patients underwent similar treatment ; the one excluded had leukemic cells in the CSF. Six patients had CNS symptoms. In the 15 patients with abnormal brain imaging findings, the interval between diagnosis and the demonstration of brain abnormalities was between one month and four years. After the cessation of treatment, imaging abnormalities remained in all patients except one with brain atrophy. Various imaging abnormalities of the brain may be seen during and after the treatment of acute childhood lymphoblastic leukemia and persist for a long time. In children with this condition, the assessment of brain abnormalities requires follow-up study of the brain.

Magnetic resonance imaging of experimental brain edema

Energy Technology Data Exchange (ETDEWEB)

Tanaka, Chuzo; Naruse, Shoji; Horikawa, Yoshiharu; Higuchi, Toshihiro; Ebisu, Toshihiko; Hirakawa, Kimiyoshi; Ohno, Yoshioki; Maki, Sou

1987-04-01

Experimental brain edema was produced by either cold injury or TET (triethyl-tin) intoxication in twenty-five Wistar rats, weighing about 250 g each, and then analyzed using MRI (magnetic resonance imaging). The MRI was carried out with a 0.1 Tesla clinical apparatus (Asahi Mark J), using a special coil (7 cm in diameter) devised for small animals in order to obtain SR, SE, IR, and calculated T/sub 1/ and T/sub 2/ images. A dose of 0.5 mmol/kg of Gd-DTPA was injected intravenously for the cold-injury edema, and MRIs of the rat brains were started immediately and obtained successively for 3 hours. MRI showed spatial resolution sufficient to differentiate the cortex from the caudate nucleus, even in such a small rat brain. Rat brains with TET intoxication (cytotoxic edema) showed a marked prolongation of T/sub 1/ and T/sub 2/ in the white matter. Consequently, the TET-intoxication images reflected these characteristic findings. Cold-induced edema showed an increased signal intensity in the injured cortex, the white matter, and the opposite white matter when compared with a normal brain. These changes correlate well with the previously reported in vitro data. When Gd-DTPA was administered to the rats with cold-induced edema, the signal intensity of the cold-injury lesion was significantly reduced. These changes were clearly demonstrated by the calculated T/sub 1/ images. To two rats we administered a dose of 0.5 mmol/kg of Gd-DTPA; The T/sub 1/ values for the cold-injury lesions, before and after the injection, were about 445 msec and about 200 msec respectively. These studies were useful not only in evaluating brain edema, but also in analysing the effect of Gd-DTPA on the brain edema.

Mapping whole-brain activity with cellular resolution by light-sheet microscopy and high-throughput image analysis (Conference Presentation)

Science.gov (United States)

Silvestri, Ludovico; Rudinskiy, Nikita; Paciscopi, Marco; Müllenbroich, Marie Caroline; Costantini, Irene; Sacconi, Leonardo; Frasconi, Paolo; Hyman, Bradley T.; Pavone, Francesco S.

2016-03-01

Mapping neuronal activity patterns across the whole brain with cellular resolution is a challenging task for state-of-the-art imaging methods. Indeed, despite a number of technological efforts, quantitative cellular-resolution activation maps of the whole brain have not yet been obtained. Many techniques are limited by coarse resolution or by a narrow field of view. High-throughput imaging methods, such as light sheet microscopy, can be used to image large specimens with high resolution and in reasonable times. However, the bottleneck is then moved from image acquisition to image analysis, since many TeraBytes of data have to be processed to extract meaningful information. Here, we present a full experimental pipeline to quantify neuronal activity in the entire mouse brain with cellular resolution, based on a combination of genetics, optics and computer science. We used a transgenic mouse strain (Arc-dVenus mouse) in which neurons which have been active in the last hours before brain fixation are fluorescently labelled. Samples were cleared with CLARITY and imaged with a custom-made confocal light sheet microscope. To perform an automatic localization of fluorescent cells on the large images produced, we used a novel computational approach called semantic deconvolution. The combined approach presented here allows quantifying the amount of Arc-expressing neurons throughout the whole mouse brain. When applied to cohorts of mice subject to different stimuli and/or environmental conditions, this method helps finding correlations in activity between different neuronal populations, opening the possibility to infer a sort of brain-wide 'functional connectivity' with cellular resolution.

Applicability of the 3D-VIBE sequence to whole brain imaging

International Nuclear Information System (INIS)

Makabe, Takeshi; Nakamura, Manami; Moriyama, Ryo

2009-01-01

The volumetric interpolated breath-hold examination (VIBE) method has been developed imaging also holds its breath in an abdomen, and to do three-dimensional T1WI in possible time in gradient echo sequence, and applied to dynamic study mainly and planning for time reduction using an interpolation and partial fourier. We considered the condition for imaging to do whole brain as high resolution image using VIBE. Even if base matrix was maintained when an interpolation and partial fourier were used too much excessively by Phantom experiment, the resolution of multiplanar reconstruction (MPR) image fell. There was a limit of the interpolation therefore to maintain the resolution as voxel. Signal-to-noise ratio (SNR) fell by flip angle (FA) increase by the applicability to the head, and peak existed in about 15 deg in contrast-to-noise ratio (CNR) of white matter and gray matter. Therefore by it's clinical and optimizing the imaging condition of VIBE, whole brain, it was imaging possible in about 3 minutes as high resolution image. (author)

Brain vascular image segmentation based on fuzzy local information C-means clustering

Science.gov (United States)

Hu, Chaoen; Liu, Xia; Liang, Xiao; Hui, Hui; Yang, Xin; Tian, Jie

2017-02-01

Light sheet fluorescence microscopy (LSFM) is a powerful optical resolution fluorescence microscopy technique which enables to observe the mouse brain vascular network in cellular resolution. However, micro-vessel structures are intensity inhomogeneity in LSFM images, which make an inconvenience for extracting line structures. In this work, we developed a vascular image segmentation method by enhancing vessel details which should be useful for estimating statistics like micro-vessel density. Since the eigenvalues of hessian matrix and its sign describes different geometric structure in images, which enable to construct vascular similarity function and enhance line signals, the main idea of our method is to cluster the pixel values of the enhanced image. Our method contained three steps: 1) calculate the multiscale gradients and the differences between eigenvalues of Hessian matrix. 2) In order to generate the enhanced microvessels structures, a feed forward neural network was trained by 2.26 million pixels for dealing with the correlations between multi-scale gradients and the differences between eigenvalues. 3) The fuzzy local information c-means clustering (FLICM) was used to cluster the pixel values in enhance line signals. To verify the feasibility and effectiveness of this method, mouse brain vascular images have been acquired by a commercial light-sheet microscope in our lab. The experiment of the segmentation method showed that dice similarity coefficient can reach up to 85%. The results illustrated that our approach extracting line structures of blood vessels dramatically improves the vascular image and enable to accurately extract blood vessels in LSFM images.

Quality assessment of brain images by Hoffman phantom

International Nuclear Information System (INIS)

Karimian, A.R.; Saddad, F.; Mosalla, B.; Moradkhani, S.; Degbankhan, R.; Pouladi, M.

2002-01-01

The purpose of this investigation is using Hoffman brain phantom for quality assessment of brian images in SPECT system. There are the following standards for quality control in nuclear medicine: American Association of Physicists in Medicine, National Electrical Manufacturers Association, International Electromechanical Commission, International Atomic Energy Agency. Each of the above standards has the following important orders: Physical inspection, Acceptance and Reference Testing, Periodic Q C tests (Daily, Weekly, Monthly, Quarterly, Annually). The above tests are simple physics measures. To more meaningful ones based on performance of some tasks related to clinical application it is better to use from organs' phantoms, such as: brain, cardiac, etc. In this research we made a comparison between normal and abnormal states of Hoffman brain phantom. Methods of Hoffman brain phantom was filled with a solution of Tc- 99 m (5 mCi) and water (1300 cc). this results: The investigation of small abnormalities strongly related to the operating conditions and deviation from best tuning state of the system

The Potential of Using Brain Images for Authentication

Directory of Open Access Journals (Sweden)

Fanglin Chen

2014-01-01

Full Text Available Biometric recognition (also known as biometrics refers to the automated recognition of individuals based on their biological or behavioral traits. Examples of biometric traits include fingerprint, palmprint, iris, and face. The brain is the most important and complex organ in the human body. Can it be used as a biometric trait? In this study, we analyze the uniqueness of the brain and try to use the brain for identity authentication. The proposed brain-based verification system operates in two stages: gray matter extraction and gray matter matching. A modified brain segmentation algorithm is implemented for extracting gray matter from an input brain image. Then, an alignment-based matching algorithm is developed for brain matching. Experimental results on two data sets show that the proposed brain recognition system meets the high accuracy requirement of identity authentication. Though currently the acquisition of the brain is still time consuming and expensive, brain images are highly unique and have the potential possibility for authentication in view of pattern recognition.

Demonstration of brain tumors by computer-aided image intensification

International Nuclear Information System (INIS)

Froeder, M.; Herbst, M.; Erlangen-Nuernberg Univ., Erlangen

1987-01-01

It is possible to distinguish cerebral tumours from brain tissue after the injection of contrast by using an X-ray-video chain. Weak contrast situated behind strongly absorbing bone can be demonstrated by a non-tomographic method by reducing the noise level and by using a special subtraction technique designed for optimal iodine contrast. For this examination, four series of images are prepared and stored (one before the administration of contrast and three subsequently). Dynamic studies of the distribution of contrast in the intra- and extra-vascular spaces of brain and tumour are produced by subtracting the stored images. The demonstration of blood-flow dynamics improves the differentiation of the tumour and, in particular, makes it possible to distinguish the tumour from cerebral oedema. The current input into the X-ray tube is low and the skin dose on the entry side is less than 0.6 R for each series. The usefulness of the method in complementing computer tomography for surgical and radiation treatment is illustrated from various types of tumour. Up to the present 35 patients have been examined by this method. (orig.) [de

IMAGING OF BRAIN FUNCTION BASED ON THE ANALYSIS OF FUNCTIONAL CONNECTIVITY - IMAGING ANALYSIS OF BRAIN FUNCTION BY FMRI AFTER ACUPUNCTURE AT LR3 IN HEALTHY INDIVIDUALS

OpenAIRE

Zheng, Yu; Wang, Yuying; Lan, Yujun; Qu, Xiaodong; Lin, Kelin; Zhang, Jiping; Qu, Shanshan; Wang, Yanjie; Tang, Chunzhi; Huang, Yong

2016-01-01

Objective: This Study observed the relevant brain areas activated by acupuncture at the Taichong acupoint (LR3) and analyzed the functional connectivity among brain areas using resting state functional magnetic resonance imaging (fMRI) to explore the acupoint specificity of the Taichong acupoint. Methods: A total of 45 healthy subjects were randomly divided into the Taichong (LR3) group, sham acupuncture group and sham acupoint group. Subjects received resting state fMRI before acupuncture, a...

A new improved method for assessing brain deformation after decompressive craniectomy.

Directory of Open Access Journals (Sweden)

Tim L Fletcher

Full Text Available Decompressive craniectomy (DC is a surgical intervention used following traumatic brain injury to prevent or alleviate raised intracranial pressure. However the clinical effectiveness of the intervention remains in doubt. The location of the craniectomy (unilateral or bifrontal might be expected to change the brain deformation associated with the operation and hence the clinical outcome. As existing methods for assessing brain deformation have several limitations, we sought to develop and validate a new improved method.Computed tomography (CT scans were taken from 27 patients who underwent DC (17 bifrontal patients and 10 unilateral patients. Pre-operative and post-operative images were processed and registered to determine the change in brain position associated with the operation. The maximum deformation in the herniated brain, the change in volume and estimates of the craniectomy area were determined from the images. Statistical comparison was made using the Pearson's correlation coefficient r and a Welch's two-tailed T-test, with statistical significance reported at the 5% level.There was a reasonable correlation between the volume increase and the maximum brain displacement (r = 0.64, a low correlation between the volume increase and the craniectomy area (r = 0.30 and no correlation between the maximum displacement and the craniectomy area (r = -0.01. The maximum deformation was significantly lower (P  = 0.023 in the bifrontal patients (mean = 22.5 mm compared with the unilateral patients (mean = 29.8 mm. Herniation volume was significantly lower (P = 0.023 in bifrontal (mean = 50.0 ml than unilateral patients (mean = 107.3 ml. Craniectomy area was not significantly different for the two craniectomy locations (P = 0.29.A method has been developed to quantify changes in brain deformation due to decompressive craniectomy from CT images and allow comparison between different craniectomy locations

High-precision surface formation and the 3-D shaded display of the brain obtained from CT images

International Nuclear Information System (INIS)

Niki, Noboru; Higuti, Kiyofumi; Takahashi, Yoshizo

1986-01-01

High-precision reconstruction of surface and 3-D shaded display of the target organ and lesions, obtained from CT images, aid in medical recognition. Firstly, this paper points out some problems of using a conventional method, in which brain surface is reconstructed from the known contour of brain slices, in 3-D shaded display of the brain in a dog. Secondly, a new high-precision technique for reconstructing complex brain surface from brain contour is proposed. The principle of the technique consists of extracting data of outline surface and fissures, smoothing of brain contour, and recomposition of the data of outline surface and fissures into a composite surface image. Finally, the validity of the method was verified by successfully reconstructing complex brain surface from the contour of dog brain slices. In addition, it was possible to cut brain surface, obtained by the newly developed technique, in any voluntary plane and to display CT values on the sections. (Namekawa, K.)

Segmentation of 3D microPET images of the rat brain via the hybrid gaussian mixture method with kernel density estimation.

Science.gov (United States)

Chen, Tai-Been; Chen, Jyh-Cheng; Lu, Henry Horng-Shing

2012-01-01

Segmentation of positron emission tomography (PET) is typically achieved using the K-Means method or other approaches. In preclinical and clinical applications, the K-Means method needs a prior estimation of parameters such as the number of clusters and appropriate initialized values. This work segments microPET images using a hybrid method combining the Gaussian mixture model (GMM) with kernel density estimation. Segmentation is crucial to registration of disordered 2-deoxy-2-fluoro-D-glucose (FDG) accumulation locations with functional diagnosis and to estimate standardized uptake values (SUVs) of region of interests (ROIs) in PET images. Therefore, simulation studies are conducted to apply spherical targets to evaluate segmentation accuracy based on Tanimoto's definition of similarity. The proposed method generates a higher degree of similarity than the K-Means method. The PET images of a rat brain are used to compare the segmented shape and area of the cerebral cortex by the K-Means method and the proposed method by volume rendering. The proposed method provides clearer and more detailed activity structures of an FDG accumulation location in the cerebral cortex than those by the K-Means method.

An MR Brain Images Classifier System via Particle Swarm Optimization and Kernel Support Vector Machine

Directory of Open Access Journals (Sweden)

Yudong Zhang

2013-01-01

Full Text Available Automated abnormal brain detection is extremely of importance for clinical diagnosis. Over last decades numerous methods had been presented. In this paper, we proposed a novel hybrid system to classify a given MR brain image as either normal or abnormal. The proposed method first employed digital wavelet transform to extract features then used principal component analysis (PCA to reduce the feature space. Afterwards, we constructed a kernel support vector machine (KSVM with RBF kernel, using particle swarm optimization (PSO to optimize the parameters C and σ. Fivefold cross-validation was utilized to avoid overfitting. In the experimental procedure, we created a 90 images dataset brain downloaded from Harvard Medical School website. The abnormal brain MR images consist of the following diseases: glioma, metastatic adenocarcinoma, metastatic bronchogenic carcinoma, meningioma, sarcoma, Alzheimer, Huntington, motor neuron disease, cerebral calcinosis, Pick’s disease, Alzheimer plus visual agnosia, multiple sclerosis, AIDS dementia, Lyme encephalopathy, herpes encephalitis, Creutzfeld-Jakob disease, and cerebral toxoplasmosis. The 5-folded cross-validation classification results showed that our method achieved 97.78% classification accuracy, higher than 86.22% by BP-NN and 91.33% by RBF-NN. For the parameter selection, we compared PSO with those of random selection method. The results showed that the PSO is more effective to build optimal KSVM.

Quantification of brain images using Korean standard templates and structural and cytoarchitectonic probabilistic maps

International Nuclear Information System (INIS)

Lee, Jae Sung; Lee, Dong Soo; Kim, Yu Kyeong

2004-01-01

Population based structural and functional maps of the brain provide effective tools for the analysis and interpretation of complex and individually variable brain data. Brain MRI and PET standard templates and statistical probabilistic maps based on image data of Korean normal volunteers have been developed and probabilistic maps based on cytoarchitectonic data have been introduced. A quantification method using these data was developed for the objective assessment of regional intensity in the brain images. Age, gender and ethnic specific anatomical and functional brain templates based on MR and PET images of Korean normal volunteers were developed. Korean structural probabilistic maps for 89 brain regions and cytoarchitectonic probabilistic maps for 13 Brodmann areas were transformed onto the standard templates. Brain FDG PET and SPGR MR images of normal volunteers were spatially normalized onto the template of each modality and gender. Regional uptake of radiotracers in PET and gray matter concentration in MR images were then quantified by averaging (or summing) regional intensities weighted using the probabilistic maps of brain regions. Regionally specific effects of aging on glucose metabolism in cingulate cortex were also examined. Quantification program could generate quantification results for single spatially normalized images per 20 seconds. Glucose metabolism change in cingulate gyrus was regionally specific: ratios of glucose metabolism in the rostral anterior cingulate vs. posterior cingulate and the caudal anterior cingulate vs. posterior cingulate were significantly decreased as the age increased. 'Rostral anterior' / 'posterior' was decreased by 3.1% per decade of age (p -11 , r=0.81) and 'caudal anterior' / 'posterior' was decreased by 1.7% (p -8 , r=0.72). Ethnic specific standard templates and probabilistic maps and quantification program developed in this study will be useful for the analysis of brain image of Korean people since the difference

Quantification of brain images using Korean standard templates and structural and cytoarchitectonic probabilistic maps

Energy Technology Data Exchange (ETDEWEB)

Lee, Jae Sung; Lee, Dong Soo; Kim, Yu Kyeong [College of Medicine, Seoul National Univ., Seoul (Korea, Republic of)] [and others

2004-06-01

Population based structural and functional maps of the brain provide effective tools for the analysis and interpretation of complex and individually variable brain data. Brain MRI and PET standard templates and statistical probabilistic maps based on image data of Korean normal volunteers have been developed and probabilistic maps based on cytoarchitectonic data have been introduced. A quantification method using these data was developed for the objective assessment of regional intensity in the brain images. Age, gender and ethnic specific anatomical and functional brain templates based on MR and PET images of Korean normal volunteers were developed. Korean structural probabilistic maps for 89 brain regions and cytoarchitectonic probabilistic maps for 13 Brodmann areas were transformed onto the standard templates. Brain FDG PET and SPGR MR images of normal volunteers were spatially normalized onto the template of each modality and gender. Regional uptake of radiotracers in PET and gray matter concentration in MR images were then quantified by averaging (or summing) regional intensities weighted using the probabilistic maps of brain regions. Regionally specific effects of aging on glucose metabolism in cingulate cortex were also examined. Quantification program could generate quantification results for single spatially normalized images per 20 seconds. Glucose metabolism change in cingulate gyrus was regionally specific: ratios of glucose metabolism in the rostral anterior cingulate vs. posterior cingulate and the caudal anterior cingulate vs. posterior cingulate were significantly decreased as the age increased. 'Rostral anterior' / 'posterior' was decreased by 3.1% per decade of age (p<10{sup -11}, r=0.81) and 'caudal anterior' / 'posterior' was decreased by 1.7% (p<10{sup -8}, r=0.72). Ethnic specific standard templates and probabilistic maps and quantification program developed in this study will be useful for the analysis

Visual image reconstruction from human brain activity: A modular decoding approach

International Nuclear Information System (INIS)

Miyawaki, Yoichi; Uchida, Hajime; Yamashita, Okito; Sato, Masa-aki; Kamitani, Yukiyasu; Morito, Yusuke; Tanabe, Hiroki C; Sadato, Norihiro

2009-01-01

Brain activity represents our perceptual experience. But the potential for reading out perceptual contents from human brain activity has not been fully explored. In this study, we demonstrate constraint-free reconstruction of visual images perceived by a subject, from the brain activity pattern. We reconstructed visual images by combining local image bases with multiple scales, whose contrasts were independently decoded from fMRI activity by automatically selecting relevant voxels and exploiting their correlated patterns. Binary-contrast, 10 x 10-patch images (2 100 possible states), were accurately reconstructed without any image prior by measuring brain activity only for several hundred random images. The results suggest that our approach provides an effective means to read out complex perceptual states from brain activity while discovering information representation in multi-voxel patterns.

An automatic extraction algorithm of three dimensional shape of brain parenchyma from MR images

International Nuclear Information System (INIS)

Matozaki, Takeshi

2000-01-01

For the simulation of surgical operations, the extraction of the selected region using MR images is useful. However, this segmentation requires a high level of skill and experience from the technicians. We have developed an unique automatic extraction algorithm for extracting three dimensional brain parenchyma using MR head images. It is named the ''three dimensional gray scale clumsy painter method''. In this method, a template having the shape of a pseudo-circle, a so called clumsy painter (CP), moves along the contour of the selected region and extracts the region surrounded by the contour. This method has advantages compared with the morphological filtering and the region growing method. Previously, this method was applied to binary images, but there were some problems in that the results of the extractions were varied by the value of the threshold level. We introduced gray level information of images to decide the threshold, and depend upon the change of image density between the brain parenchyma and CSF. We decided the threshold level by the vector of a map of templates, and changed the map according to the change of image density. As a result, the over extracted ratio was improved by 36%, and the under extracted ratio was improved by 20%. (author)

Measurement and imaging of brain function using MRI, MEG, and TMS

International Nuclear Information System (INIS)

Iramina, Keiji

2008-01-01

This paper reviews functional imaging techniques in neuroscience such as magnetic resonance imaging (MRI) functional MRI (fMRI), magnetoencephalogray (MEG), and transcranial magnetic stimulation (TMS). fMRI and MEG allow the neuronal activity of the brain to be measured non-invasively. MEG detects an electrical activity as neuronal activity, while, fMRI detects a hemodynamic response as neuronal activity. TMS is the application of a brief magnetic pulse or a train of pulses to the skull, which results in the induction of a local electric current in the underlying surface of the brain, thereby producing a localized axonal depolarization. As a non-invasive and effective method to make reversible lesions in the human brain, TMS has a long and successful history. All of these techniques have major potential for applications in the neuroscience and medicine. (author)

Accurate Learning with Few Atlases (ALFA): an algorithm for MRI neonatal brain extraction and comparison with 11 publicly available methods.

Science.gov (United States)

Serag, Ahmed; Blesa, Manuel; Moore, Emma J; Pataky, Rozalia; Sparrow, Sarah A; Wilkinson, A G; Macnaught, Gillian; Semple, Scott I; Boardman, James P

2016-03-24

Accurate whole-brain segmentation, or brain extraction, of magnetic resonance imaging (MRI) is a critical first step in most neuroimage analysis pipelines. The majority of brain extraction algorithms have been developed and evaluated for adult data and their validity for neonatal brain extraction, which presents age-specific challenges for this task, has not been established. We developed a novel method for brain extraction of multi-modal neonatal brain MR images, named ALFA (Accurate Learning with Few Atlases). The method uses a new sparsity-based atlas selection strategy that requires a very limited number of atlases 'uniformly' distributed in the low-dimensional data space, combined with a machine learning based label fusion technique. The performance of the method for brain extraction from multi-modal data of 50 newborns is evaluated and compared with results obtained using eleven publicly available brain extraction methods. ALFA outperformed the eleven compared methods providing robust and accurate brain extraction results across different modalities. As ALFA can learn from partially labelled datasets, it can be used to segment large-scale datasets efficiently. ALFA could also be applied to other imaging modalities and other stages across the life course.

Brain MR imaging of systemic lupus erythematodes

International Nuclear Information System (INIS)

Kobayashi, Satoshi; Suzuki, Masayuki; Ueda, Fumiaki; Arai, Kazunori; Kobayashi, Takeshi; Kadoya, Masumi; Matsui, Osamu; Takashima, Tsutomu

1996-01-01

Brain MR imaging of 13 patients with systemic lupus erythematodus (SLE) were reviewed. Two major findings was obtained. One was deep white matter hyperintensity (DWMH) and periventricular hyperintensity (PVH), the other was cerebral infarction. In comparison with the same age group, relatively severe brain atrophy was also observed. It was thought that these findings were induced from the vasculitis caused by SLE. However, the influence of the steroid therapy could not be excluded. No definite correlation between MR findings and clinical symptoms were seen. In conclusion, when we interpret brain MR imaging of the patients with SLE, special attention should be paid to their age. (author)

Manganese accumulation in the brain: MR imaging

Energy Technology Data Exchange (ETDEWEB)

Uchino, A.; Nomiyama, K.; Takase, Y.; Nakazono, T.; Nojiri, J.; Kudo, S. [Saga Medical School, Department of Radiology, Saga (Japan); Noguchi, T. [Kyushu University, Department of Clinical Radiology, Graduate School of Medicine, Fukuoka (Japan)

2007-09-15

Manganese (Mn) accumulation in the brain is detected as symmetrical high signal intensity in the globus pallidi on T1-weighted MR images without an abnormal signal on T2-weighted images. In this review, we present several cases of Mn accumulation in the brain due to acquired or congenital diseases of the abdomen including hepatic cirrhosis with a portosystemic shunt, congenital biliary atresia, primary biliary cirrhosis, congenital intrahepatic portosystemic shunt without liver dysfunction, Rendu-Osler-Weber syndrome with a diffuse intrahepatic portosystemic shunt, and patent ductus venosus. Other causes of Mn accumulation in the brain are Mn overload from total parenteral nutrition and welding-related Mn intoxication. (orig.)

[Getting an insight into the brain - new optical clearing techniques and imaging using light-sheet microscope].

Science.gov (United States)

Pawłowska, Monika; Legutko, Diana; Stefaniuk, Marzena

2017-01-01

One of the biggest challenges in neuroscience is to understand how brain operates. For this, it would be the best to image the whole brain with at least cellular resolution, preserving the three-dimensional structure in order to capture the connections between different areas. Most currently available high-resolution imaging techniques are based on preparing thin brain sections that are next photographed one by one and subsequently bigger structures are reconstructed. These techniques are laborious and create artifacts. Recent optical clearing methods allow to obtain literally transparent brains that can be imaged using light-sheet microscope. The present review summarizes the most popular optical clearing techniques, describing their different mechanisms and comparing advantages and disadvantages of different approaches, and presents the principle of light-sheet microscopy and its use in imaging. Finally, it gives examples of application of optical tissue clearing and light-sheet imaging in neuroscience and beyond it.

Advanced magnetic resonance imaging of the brain : MRI of the brain

African Journals Online (AJOL)

Since the development of magnetic resonance imaging by Paul. Lauterbur and ... Functional brain imaging refers to the family of techniques that aim to measure the .... left thumb, the fingers of their right hand against their right thumb, or rest.

Imaging of brain tumors with histological correlations. 2. ed.

Energy Technology Data Exchange (ETDEWEB)

Drevelegas, Antonios (ed.)

2011-07-01

This volume provides a deeper understanding of the diagnosis of brain tumors by correlating radiographic imaging features with the underlying pathological abnormalities. All modern imaging modalities are used to complete a diagnostic overview of brain tumors with emphasis on recent advances in diagnostic neuroradiology. High-quality illustrations depicting common and uncommon imaging characteristics of a wide range of brain tumors are presented and analysed, drawing attention to the ways in which these characteristics reflect different aspects of pathology. Important theoretical considerations are also discussed. Since the first edition, chapters have been revised and updated and new material has been added, including detailed information on the clinical application of functional MRI and diffusion tensor imaging. Radiologists and other clinicians interested in the current diagnostic approach to brain tumors will find this book to be an invaluable and enlightening clinical tool. (orig.)

Automated method to compute Evans index for diagnosis of idiopathic normal pressure hydrocephalus on brain CT images

Science.gov (United States)

Takahashi, Noriyuki; Kinoshita, Toshibumi; Ohmura, Tomomi; Matsuyama, Eri; Toyoshima, Hideto

2017-03-01

The early diagnosis of idiopathic normal pressure hydrocephalus (iNPH) considered as a treatable dementia is important. The iNPH causes enlargement of lateral ventricles (LVs). The degree of the enlargement of the LVs on CT or MR images is evaluated by using a diagnostic imaging criterion, Evans index. Evans index is defined as the ratio of the maximal width of frontal horns (FH) of the LVs to the maximal width of the inner skull (IS). Evans index is the most commonly used parameter for the evaluation of ventricular enlargement. However, manual measurement of Evans index is a time-consuming process. In this study, we present an automated method to compute Evans index on brain CT images. The algorithm of the method consisted of five major steps: standardization of CT data to an atlas, extraction of FH and IS regions, the search for the outmost points of bilateral FH regions, determination of the maximal widths of both the FH and the IS, and calculation of Evans index. The standardization to the atlas was performed by using linear affine transformation and non-linear wrapping techniques. The FH regions were segmented by using a three dimensional region growing technique. This scheme was applied to CT scans from 44 subjects, including 13 iNPH patients. The average difference in Evans index between the proposed method and manual measurement was 0.01 (1.6%), and the correlation coefficient of these data for the Evans index was 0.98. Therefore, this computerized method may have the potential to accurately compute Evans index for the diagnosis of iNPH on CT images.

Recent Developments in Diffusion Tensor Imaging of Brain

OpenAIRE

Parekh, Mansi Bharat; Gurjarpadhye, Abhijit Achyut; Manoukian, Martin A.C.; Dubnika, Arita; Rajadas, Jayakumar; Inayathullah, Mohammed

2015-01-01

Magnetic resonance imaging (MRI) has come to be known as a unique radiological imaging modality because of its ability to perform tomographic imaging of body without the use of any harmful ionizing radiation. The radiologists use MRI to gain insight into the anatomy of organs, including the brain, while biomedical researchers explore the modality to gain better understanding of the brain structure and function. However, due to limited resolution and contrast, the conventional MRI fails to sho...

Diffusion imaging and tractography of congenital brain malformations

International Nuclear Information System (INIS)

Wahl, Michael; Barkovich, A.J.; Mukherjee, Pratik

2010-01-01

Diffusion imaging is an MRI modality that measures the microscopic molecular motion of water in order to investigate white matter microstructure. The modality has been used extensively in recent years to investigate the neuroanatomical basis of congenital brain malformations. We review the basic principles of diffusion imaging and of specific techniques, including diffusion tensor imaging (DTI) and high angular resolution diffusion imaging (HARDI). We show how DTI and HARDI, and their application to fiber tractography, has elucidated the aberrant connectivity underlying a number of congenital brain malformations. Finally, we discuss potential uses for diffusion imaging of developmental disorders in the clinical and research realms. (orig.)

Usefulness of dynamic magnetic resonance imaging in brain tumors

International Nuclear Information System (INIS)

Joo, Yang Gu; Suh, Soo Jhi; Zeon, Seok Kil; Woo, Sung Ku; Kim, Hong; Kim, Jung Sik; Lee, Sung Moon; Lee, Hee Jung; Takahashi, Mutsumasa

1994-01-01

To investigate the usefulness of dynamic MR imaging in the differential diagnosis of brain tumors. Dynamic MR imaging was performed in 43 patients with histopathologically proved brain tumors. Serial images were sequentially obtained every 30 seconds for 3-5 minutes with use of spin-echo technique(TR 200msec/TE 15msec) after rapid injection of Gd-DTPA in a dose of 0.1mmol/kg body weight. Dynamics of contrast enhancement of the brain tumors were analyzed visually and by the sequential contrast enhancement ratio(CER). On the dynamic MR imaging, contrast enhancement pattern of the gliomas showed gradual increase in signal intensity(SI) till 180 seconds and usually had a longer time to peak of the CER. The SI of metastatic brain tumors increased steeply till 30 seconds and then rapidly or gradually decreased and the tumors had a shorter time to peak of the CER. Meningiomas showed a rapid ascent in SI till 30 to 60 seconds and then made a plateau or slight descent of the CER. Lymphomas and germinomas showed relatively rapid increase of SI till 30 seconds and usually had a longer time peak of the CER. Dynamic MR imaging with Gd-DTPA may lead to further information about the brain tumors as the sequential contrast enhancement pattern and CER parameters seem to be helpful in discriminating among the brain tumors

Errors in MR-based attenuation correction for brain imaging with PET/MR scanners

International Nuclear Information System (INIS)

Rota Kops, Elena; Herzog, Hans

2013-01-01

Aim: Attenuation correction of PET data acquired by hybrid MR/PET scanners remains a challenge, even if several methods for brain and whole-body measurements have been developed recently. A template-based attenuation correction for brain imaging proposed by our group is easy to handle and delivers reliable attenuation maps in a short time. However, some potential error sources are analyzed in this study. We investigated the choice of template reference head among all the available data (error A), and possible skull anomalies of the specific patient, such as discontinuities due to surgery (error B). Materials and methods: An anatomical MR measurement and a 2-bed-position transmission scan covering the whole head and neck region were performed in eight normal subjects (4 females, 4 males). Error A: Taking alternatively one of the eight heads as reference, eight different templates were created by nonlinearly registering the images to the reference and calculating the average. Eight patients (4 females, 4 males; 4 with brain lesions, 4 w/o brain lesions) were measured in the Siemens BrainPET/MR scanner. The eight templates were used to generate the patients' attenuation maps required for reconstruction. ROI and VOI atlas-based comparisons were performed employing all the reconstructed images. Error B: CT-based attenuation maps of two volunteers were manipulated by manually inserting several skull lesions and filling a nasal cavity. The corresponding attenuation coefficients were substituted with the water's coefficient (0.096/cm). Results: Error A: The mean SUVs over the eight templates pairs for all eight patients and all VOIs did not differ significantly one from each other. Standard deviations up to 1.24% were found. Error B: After reconstruction of the volunteers' BrainPET data with the CT-based attenuation maps without and with skull anomalies, a VOI-atlas analysis was performed revealing very little influence of the skull lesions (less than 3%), while the filled

Errors in MR-based attenuation correction for brain imaging with PET/MR scanners

Science.gov (United States)

Rota Kops, Elena; Herzog, Hans

2013-02-01

AimAttenuation correction of PET data acquired by hybrid MR/PET scanners remains a challenge, even if several methods for brain and whole-body measurements have been developed recently. A template-based attenuation correction for brain imaging proposed by our group is easy to handle and delivers reliable attenuation maps in a short time. However, some potential error sources are analyzed in this study. We investigated the choice of template reference head among all the available data (error A), and possible skull anomalies of the specific patient, such as discontinuities due to surgery (error B). Materials and methodsAn anatomical MR measurement and a 2-bed-position transmission scan covering the whole head and neck region were performed in eight normal subjects (4 females, 4 males). Error A: Taking alternatively one of the eight heads as reference, eight different templates were created by nonlinearly registering the images to the reference and calculating the average. Eight patients (4 females, 4 males; 4 with brain lesions, 4 w/o brain lesions) were measured in the Siemens BrainPET/MR scanner. The eight templates were used to generate the patients' attenuation maps required for reconstruction. ROI and VOI atlas-based comparisons were performed employing all the reconstructed images. Error B: CT-based attenuation maps of two volunteers were manipulated by manually inserting several skull lesions and filling a nasal cavity. The corresponding attenuation coefficients were substituted with the water's coefficient (0.096/cm). ResultsError A: The mean SUVs over the eight templates pairs for all eight patients and all VOIs did not differ significantly one from each other. Standard deviations up to 1.24% were found. Error B: After reconstruction of the volunteers' BrainPET data with the CT-based attenuation maps without and with skull anomalies, a VOI-atlas analysis was performed revealing very little influence of the skull lesions (less than 3%), while the filled nasal

Automated analysis for early signs of cerebral infarctions on brain X-ray CT images

International Nuclear Information System (INIS)

Oshima, Kazuki; Hara, Takeshi; Zhou, X.; Muramatsu, Chisako; Fujita, Hiroshi; Sakashita, Keiji

2010-01-01

t-PA (tissue plasminogen activator) thrombolysis is an effective clinical treatment for the acute cerebral infarction by breakdown to blood clots. However there is a risk of hemorrhage with its use. The guideline of the treatment is denying cerebral hemorrhage and widespread Early CT sign (ECS) on CT images. In this study, we analyzed the CT value of normal brain and ECS with normal brain model by comparing patient brain CT scan with a statistical normal model. Our method has constructed normal brain models consisted of 60 normal brain X-ray CT images. We calculated Z-score based on statistical model for 16 cases of cerebral infarction with ECS, 3 cases of cerebral infarction without ECS, and 25 cases of normal brain. The results of statistical analysis showed that there was a statistically significant difference between control and abnormal groups. This result implied that the automated detection scheme for ECS by using Z-score would be a possible application for brain computer-aided diagnosis (CAD). (author)

Compensation for nonuniform attenuation in SPECT brain imaging

International Nuclear Information System (INIS)

Glick, S.J.; King, M.A.; Pan, T.S.; Soares, E.J.

1996-01-01

Accurate compensation for photon attenuation is needed to perform quantitative brain single-photon-emission computed tomographic (SPECT) imaging. Bellini's attenuation-compensation method has been used with a nonuniform attenuation map to account for the nonuniform attenuation properties of the head. Simulation studies using a three-dimensional (3-D) digitized anthropomorphic brain phantom were conducted to compare quantitative accuracy of reconstructions obtained with the nonuniform Bellini method to that obtained with the Chang method and to iterative reconstruction using maximum-likelihood expectation maximization (ML-EM). Using the Chang method and assuming the head to be a uniform attenuator gave reconstructions with an average bias of approximately 6-8%, whereas using the Bellini or the iterative ML-EM method with a nonuniform attenuation map gave an average bias of approximately 1%. The computation time required to implement nonuniform attenuation compensation with the Bellini algorithm is approximately equivalent to the time required to perform one iteration of ML-EM. Thus, using the Bellini method with a nonuniform attenuation map provides accurate compensation for photon attenuation within the head, and the method can be implemented in computation times suitable for routine clinical use

Volume of Structures in the Fetal Brain Measured with a New Semiautomated Method.

Science.gov (United States)

Ber, R; Hoffman, D; Hoffman, C; Polat, A; Derazne, E; Mayer, A; Katorza, E

2017-11-01

Measuring the volume of fetal brain structures is challenging due to fetal motion, low resolution, and artifacts caused by maternal tissue. Our aim was to introduce a new, simple, Matlab-based semiautomated method to measure the volume of structures in the fetal brain and present normal volumetric curves of the structures measured. The volume of the supratentorial brain, left and right hemispheres, cerebellum, and left and right eyeballs was measured retrospectively by the new semiautomated method in MR imaging examinations of 94 healthy fetuses. Four volume ratios were calculated. Interobserver agreement was calculated with the intraclass correlation coefficient, and a Bland-Altman plot was drawn for comparison of manual and semiautomated method measurements of the supratentorial brain. We present normal volumetric curves and normal percentile values of the structures measured according to gestational age and of the ratios between the cerebellum and the supratentorial brain volume and the total eyeball and the supratentorial brain volume. Interobserver agreement was good or excellent for all structures measured. The Bland-Altman plot between manual and semiautomated measurements showed a maximal relative difference of 7.84%. We present a technologically simple, reproducible method that can be applied prospectively and retrospectively on any MR imaging protocol, and we present normal volumetric curves measured. The method shows results like manual measurements while being less time-consuming and user-dependent. By applying this method on different cranial and extracranial structures, anatomic and pathologic, we believe that fetal volumetry can turn from a research tool into a practical clinical one. © 2017 by American Journal of Neuroradiology.

Brain-inspired algorithms for retinal image analysis

NARCIS (Netherlands)

ter Haar Romeny, B.M.; Bekkers, E.J.; Zhang, J.; Abbasi-Sureshjani, S.; Huang, F.; Duits, R.; Dasht Bozorg, Behdad; Berendschot, T.T.J.M.; Smit-Ockeloen, I.; Eppenhof, K.A.J.; Feng, J.; Hannink, J.; Schouten, J.; Tong, M.; Wu, H.; van Triest, J.W.; Zhu, S.; Chen, D.; He, W.; Xu, L.; Han, P.; Kang, Y.

2016-01-01

Retinal image analysis is a challenging problem due to the precise quantification required and the huge numbers of images produced in screening programs. This paper describes a series of innovative brain-inspired algorithms for automated retinal image analysis, recently developed for the RetinaCheck

Minireview of Stereoselective Brain Imaging

DEFF Research Database (Denmark)

Smith, Donald F.; Jakobsen, Steen

2014-01-01

Stereoselectivity is a fundamental principle in living systems. Stereoselectivity reflects the dependence of molecular processes on the spatial orientation of constituent atoms. Stereoselective processes govern many aspects of brain function and direct the course of many psychotropic drugs. Today......, modern imaging techniques such as SPECT and PET provide a means for studying stereoselective processes in the living brain. Chemists have prepared numerous radiolabelled stereoisomers for use in SPECT and PET in order to explore various molecular processes in the living brain of anesthetized laboratory...... animals and awake humans. The studies have demonstrated how many aspects of neurotransmission consist of crucial stereoselective events that can affect brain function in health and disease. Here, we present a brief account of those findings in hope of stimulating further interest in the vital topic....

Visceral Afferent Pathways and Functional Brain Imaging

Directory of Open Access Journals (Sweden)

Stuart W.G. Derbyshire

2003-01-01

Full Text Available The application of functional imaging to study painful sensations has generated considerable interest regarding insight into brain dysfunction that may be responsible for functional pain such as that suffered in patients with irritable bowel syndrome (IBS. This review provides a brief introduction to the development of brain science as it relates to pain processing and a snapshot of recent functional imaging results with somatic and visceral pain. Particular emphasis is placed on current hypotheses regarding dysfunction of the brain-gut axis in IBS patients. There are clear and interpretable differences in brain activation following somatic as compared with visceral noxious sensation. Noxious visceral distension, particularly of the lower gastrointestinal tract, activates regions associated with unpleasant affect and autonomic responses. Noxious somatic sensation, in contrast, activates regions associated with cognition and skeletomotor responses. Differences between IBS patients and control subjects, however, were far less clear and interpretable. While this is in part due to the newness of this field, it also reflects weaknesses inherent within the current understanding of IBS. Future use of functional imaging to examine IBS and other functional disorders will be more likely to succeed by describing clear theoretical and clinical endpoints.

MR imaging of the brain in neurofibromatosis

International Nuclear Information System (INIS)

Kuhn, J.P.; Cohen, M.L.; Duffner, P.K.; Seidel, F.; Harwood-Nash, D.

1986-01-01

Fifteen children and young adults with neurofibromatosis underwent CT and MR imaging (0.5-T superconducting magnet). Seven had optic gliomas and five had other intracranial neoplasms. Before thin-section MR imaging became available, CT was superior for demonstrating the optic nerves, although MR imaging better delineated tumor spread to the optic chiasm and tract. MR imaging was superior for demonstrating other gliomatous lesions associated with neurofibromatosis. Most lesions had long T1 and T2 values and were best seen on T2-weighted images. MR imaging revealed small areas of increased signal intensity on T2-weighted images in nearly half the patients. These lesions were not apparent on CT and were usually located in the globus pallidus, but were seen in many areas of the brain, commonly in the white matter, and in the brain steam and the cerebellar peduncles. Their exact etiology is unknown. Their imaging characteristics are somewhat different from those of gray matter. They may represent hamartomas or areas of glial scarring. Differentiation from a small glioma is presently not possible on a single examination

Image processing techniques for quantification and assessment of brain MRI

NARCIS (Netherlands)

Kuijf, H.J.

2013-01-01

Magnetic resonance imaging (MRI) is a widely used technique to acquire digital images of the human brain. A variety of acquisition protocols is available to generate images in vivo and noninvasively, giving great opportunities to study the anatomy and physiology of the human brain. In my thesis,

Alzheimer's Disease Detection in Brain Magnetic Resonance Images Using Multiscale Fractal Analysis

International Nuclear Information System (INIS)

Lahmiri, Salim; Boukadoum, Mounir

2013-01-01

We present a new automated system for the detection of brain magnetic resonance images (MRI) affected by Alzheimer's disease (AD). The MRI is analyzed by means of multiscale analysis (MSA) to obtain its fractals at six different scales. The extracted fractals are used as features to differentiate healthy brain MRI from those of AD by a support vector machine (SVM) classifier. The result of classifying 93 brain MRIs consisting of 51 images of healthy brains and 42 of brains affected by AD, using leave-one-out cross-validation method, yielded 99.18% ± 0.01 classification accuracy, 100% sensitivity, and 98.20% ± 0.02 specificity. These results and a processing time of 5.64 seconds indicate that the proposed approach may be an efficient diagnostic aid for radiologists in the screening for AD

The image of a brain stroke in a computed tomograph

International Nuclear Information System (INIS)

Just, E.G.

1982-01-01

On the basis of 100 findings from patients who suffered brain strokes and by the use of 1500 ensured stroke images it was tested whether or not the stroke-predilection typologie outlined by Zuelch is based on a coincidental summation of individual cases. The radio-computed tomography with the possibility of evaluation of non-lethal cases proved itself as a suited method for confirmation or repudiation of this stroke theory. By means of the consistently achieved association of the frontal, respectively horizontal sectional image for the typology it could be proven and - with the exception of a few rather seldom types - also demonstrated that the basic and predilection types of brain stroke repeated themselves in their pattern. In individual cases a specification of lower types could also be undertaken. (orig./TRV) [de

Brain magnetic resonance imaging of infants exposed prenatally to buprenorphine

International Nuclear Information System (INIS)

Kahila, H.; Kivitie-Kallio, S.; Halmesmaki, E.; Valanne, L.; Autti, T.

2007-01-01

Purpose: To evaluate the brains of newborns exposed to buprenorphine prenatally. Material and Methods: Seven neonates followed up antenatally in connection with their mothers' buprenorphine replacement therapy underwent 1.5T magnetic resonance imaging (MRI) of the brain before the age of 2 months. The infants were born to heavy drug abusers. Four mothers were hepatitis C positive, and all were HIV negative. All mothers smoked tobacco and used benzodiazepines. All pregnancies were full term, and no perinatal asphyxia occurred. All but one neonate had abstinence syndrome and needed morphine replacement therapy. Results: Neither structural abnormalities nor abnormalities in signal intensity were recorded. Conclusion: Buprenorphine replacement therapy does not seem to cause any major structural abnormalities of the brain, and it may prevent known hypoxic-ischemic brain changes resulting from uncontrolled drug abuse. Longitudinal studies are needed to assess possible abnormalities in the brain maturation process

NMR imaging of cell phone radiation absorption in brain tissue

Science.gov (United States)

Gultekin, David H.; Moeller, Lothar

2013-01-01

A method is described for measuring absorbed electromagnetic energy radiated from cell phone antennae into ex vivo brain tissue. NMR images the 3D thermal dynamics inside ex vivo bovine brain tissue and equivalent gel under exposure to power and irradiation time-varying radio frequency (RF) fields. The absorbed RF energy in brain tissue converts into Joule heat and affects the nuclear magnetic shielding and the Larmor precession. The resultant temperature increase is measured by the resonance frequency shift of hydrogen protons in brain tissue. This proposed application of NMR thermometry offers sufficient spatial and temporal resolution to characterize the hot spots from absorbed cell phone radiation in aqueous media and biological tissues. Specific absorption rate measurements averaged over 1 mg and 10 s in the brain tissue cover the total absorption volume. Reference measurements with fiber optic temperature sensors confirm the accuracy of the NMR thermometry. PMID:23248293

Brain magnetic resonance imaging of infants exposed prenatally to buprenorphine

Energy Technology Data Exchange (ETDEWEB)

Kahila, H.; Kivitie-Kallio, S.; Halmesmaki, E.; Valanne, L.; Autti, T. [Dept. of Obstetrics and Gynecology, Dept. of Pediatrics, and Helsinki Medical Imaging Center, Helsinki Univ. Central Hospital (Finland)

2007-02-15

Purpose: To evaluate the brains of newborns exposed to buprenorphine prenatally. Material and Methods: Seven neonates followed up antenatally in connection with their mothers' buprenorphine replacement therapy underwent 1.5T magnetic resonance imaging (MRI) of the brain before the age of 2 months. The infants were born to heavy drug abusers. Four mothers were hepatitis C positive, and all were HIV negative. All mothers smoked tobacco and used benzodiazepines. All pregnancies were full term, and no perinatal asphyxia occurred. All but one neonate had abstinence syndrome and needed morphine replacement therapy. Results: Neither structural abnormalities nor abnormalities in signal intensity were recorded. Conclusion: Buprenorphine replacement therapy does not seem to cause any major structural abnormalities of the brain, and it may prevent known hypoxic-ischemic brain changes resulting from uncontrolled drug abuse. Longitudinal studies are needed to assess possible abnormalities in the brain maturation process.

Cross-relaxation imaging:methods, challenges and applications

International Nuclear Information System (INIS)

Stikov, Nikola

2010-01-01

An overview of quantitative magnetization transfer (qMT) is given, with focus on cross relaxation imaging (CRI) as a fast method for quantifying the proportion of protons bound to complex macromolecules in tissue. The procedure for generating CRI maps is outlined, showing examples in the human brain and knee, and discussing the caveats and challenges in generating precise and accurate CRI maps. Finally, several applications of CRI for imaging tissue microstructure are presented.(Author)

Activation autoradiography: imaging and quantitative determination of endogenous and exogenous oxygen in the rat brain

International Nuclear Information System (INIS)

Kawashima, K.; Iwata, R.; Kogure, K.; Ohtomo, H.; Orihara, H.; Ido, T.

1987-01-01

Endogenous and exogenous oxygen in the rat brain were quantitatively determined using an autoradiographic technique. The oxygen images of frozen and dried rat brain sections were obtained as 18 F images by using the 16 O ( 3 He,p) 18 F reaction for endogenous 16 O images and the 18 O(p,n) 18 F reaction for endogenous and exogenous 18 O images. These autoradiograms demonstrated the different distribution of oxygen between gray and white matter. These images also allowed differentiation of the individual structures of hippocampal formation, owing to the differing water content of the various structures. Local oxygen contents were quantitatively determined from autoradiograms of brain sections and standard sections with known oxygen contents. The estimated values were 75.6 +/- 4.6 wt% in gray matter and 72.2 +/- 4.0 wt% in white matter. The systematic error in the present method was estimated to be 4.9%

Studies on the clinical application of MR perfusion image using arterial spin labeling method

International Nuclear Information System (INIS)

Miyasaka, Kenji

1999-01-01

A new technique for imaging brain perfusion, arterial spin labeling method was applied in clinic. Brain perfusion was imaged by FAIR and EPISTAR both of which using arterial spin labeling (ASL) method. Suitable parameters for small contamination were examined using a imaging phantom. Then normal volunteers were examined for imaging timing. Suitable time between labeling pulse and imaging pulse for brain capillary and parenchyma was 1.0 sec. For clinical application study, total 48 patients with brain diseases were examined by FAIR and/or EPISTAR. A lesion/white matter signal intensity ratio was calculated in all clinical cases. Average of signal intensity ratio in infarction, tumor and arteriovenous malformation (AVM) were 0.8, 2.2 and 18.6 at FAIR, and 0.6, 2.2 and 12.8 at EPISTAR, respectively. Low perfusion diseases such as cerebral infarction have low signal intensity ratio and high perfusion diseases such as AVM have high signal intensity ratio in both FAIR and EPISTAR. Brain lesions were imaged similarly in FAIR and EPISTAR, and no remarkable difference was found between FAIR and EPISTAR. As a result of diagnostic trial by signal intensity ratio in operated tumor, hemorrhagic cases could be diagnosed by accuracies of 75% in FAIR and 100% in EPISTAR, respectively. (author)

Language Development and Brain Magnetic Resonance Imaging Characteristics in Preschool Children with Cerebral Palsy

Science.gov (United States)

Choi, Ja Young; Choi, Yoon Seong; Park, Eun Sook

2017-01-01

Purpose: The purpose of this study was to investigate characteristics of language development in relation to brain magnetic resonance imaging (MRI) characteristics and the other contributing factors to language development in children with cerebral palsy (CP). Method: The study included 172 children with CP who underwent brain MRI and language…

Brain perfusion imaging using a Reconstruction-of-Difference (RoD) approach for cone-beam computed tomography

Science.gov (United States)

Mow, M.; Zbijewski, W.; Sisniega, A.; Xu, J.; Dang, H.; Stayman, J. W.; Wang, X.; Foos, D. H.; Koliatsos, V.; Aygun, N.; Siewerdsen, J. H.

2017-03-01

Purpose: To improve the timely detection and treatment of intracranial hemorrhage or ischemic stroke, recent efforts include the development of cone-beam CT (CBCT) systems for perfusion imaging and new approaches to estimate perfusion parameters despite slow rotation speeds compared to multi-detector CT (MDCT) systems. This work describes development of a brain perfusion CBCT method using a reconstruction of difference (RoD) approach to enable perfusion imaging on a newly developed CBCT head scanner prototype. Methods: A new reconstruction approach using RoD with a penalized-likelihood framework was developed to image the temporal dynamics of vascular enhancement. A digital perfusion simulation was developed to give a realistic representation of brain anatomy, artifacts, noise, scanner characteristics, and hemo-dynamic properties. This simulation includes a digital brain phantom, time-attenuation curves and noise parameters, a novel forward projection method for improved computational efficiency, and perfusion parameter calculation. Results: Our results show the feasibility of estimating perfusion parameters from a set of images reconstructed from slow scans, sparse data sets, and arc length scans as short as 60 degrees. The RoD framework significantly reduces noise and time-varying artifacts from inconsistent projections. Proper regularization and the use of overlapping reconstructed arcs can potentially further decrease bias and increase temporal resolution, respectively. Conclusions: A digital brain perfusion simulation with RoD imaging approach has been developed and supports the feasibility of using a CBCT head scanner for perfusion imaging. Future work will include testing with data acquired using a 3D-printed perfusion phantom currently and translation to preclinical and clinical studies.

Advantages in functional imaging of the brain

OpenAIRE

Mier, Walter; Mier, Daniela

2015-01-01

As neuronal pathologies cause only minor morphological alterations, molecular imaging techniques are a prerequisite for the study of diseases of the brain. The development of molecular probes that specifically bind biochemical markers and the advances of instrumentation have revolutionized the possibilities to gain insight into the human brain organization and beyond this?visualize structure-function and brain-behavior relationships. The review describes the development and current applicatio...

Brain perfusion image using N-isopropyl-p-[123I] iodoamphetamine

International Nuclear Information System (INIS)

Matsuda, Hiroshi; Seki, Hiroyasu; Ishida, Hiroko

1984-01-01

In brain perfusion images using N-Isopropyl-p-[ 123 I] Iodoamphetamine and rotating gamma camera emission computed tomography, brain maps showing laterality indices (LI) were made for the purpose of detecting ineterhemispheric differences. Left (L) and right (R) leteral images were made by adding sagittal section images in each hemisphere, respectively. LI was calculated as follows. LI=100(1+(R-L)/(R+L)). The normal ranges (mean+-2 s.d.) of the indices determined by those obtained in five normal right-handed subjects were 103+-4 and 103+-10 for brain mean and each pixel, respectively. Out of 25 measurements in 22 righthanded patients with cerebrovascular accidents, brain mean LI beyond the normal limits and areas showing abnormal regional LI were observed in 5 (20%) and 21 (84%) measurements, respectively. On the other hand, X-ray CT showed low density areas in only 12 (48%). These brain maps were clinically useful for detecting and quantifying interhemispheric differences in brain perfusion images with N-Isopropyl-p-[ 123 I] Iodoamphetamine. (author)

Theoretical background and experimental measurements of human brain noise intensity in perception of ambiguous images

International Nuclear Information System (INIS)

Runnova, Anastasiya E.; Hramov, Alexander E.; Grubov, Vadim V.; Koronovskii, Alexey A.; Kurovskaya, Maria K.; Pisarchik, Alexander N.

2016-01-01

We propose a theoretical approach associated with an experimental technique to quantitatively characterize cognitive brain activity in the perception of ambiguous images. Based on the developed theoretical background and the obtained experimental data, we introduce the concept of effective noise intensity characterizing cognitive brain activity and propose the experimental technique for its measurement. The developed theory, using the methods of statistical physics, provides a solid experimentally approved basis for further understanding of brain functionality. The rather simple way to measure the proposed quantitative characteristic of the brain activity related to the interpretation of ambiguous images will hopefully become a powerful tool for physicists, physiologists and medics. Our theoretical and experimental findings are in excellent agreement with each other.

Brain Imaging with the Spintharicon

Energy Technology Data Exchange (ETDEWEB)

Forsaith, Ann L.; Horwitz, N. H.; Lofstrom, J. E.; Izenstark, J. L.; Cook, K. J. [William Beaumont Hospital, Royal Oak, MI (United States)

1969-01-15

The spark imaging camera has been successfully applied to the imaging of the distributions of radioactive {sup 125}I in the thyroid gland. A 7-in.-diameter chamber has been developed for use with larger organs. In experiments with skull phantoms, high-resolution images have been obtained with focal areas of 2.2 cm in diameter containing as little as 30 {mu}Ci of {sup 99'}mTc-labelled sodium pertechnetate at a distance as great as 10 cm from the face of the collimator. In its present form, the Spintharicon is not adaptable to electronic discrimination of photon energies. An electronic quenching circuit aids in increasing the count-rate with the high fluxes that can be obtained in {sup 99m}Tc brain imaging. The contrast obtained in the image is controlled by the film contrast and camera f-stop. By using high-contrast copy film instead of the conventional ASA 3000 type, areas of increased activity are more easily visualized in a background pool of radioactivity. In these large distributions spark contents ranging from 30 000 to 60 000 are usually required for adequate resolution. In-vivo demonstrations of known brain lesions have been obtained with the Spintharicon. In its present stage of development, the inability to enhance contrast may limit its clinical usefulness in situations where the target to non-target ratio is low. (author)

Molecular Imaging of the Brain Using Multi-Quantum Coherence and Diagnostics of Brain Disorders

CERN Document Server

Kaila, M M

2013-01-01

This book examines multi-quantum magnetic resonance imaging methods and the diagnostics of brain disorders. It consists of two Parts. The part I is initially devoted towards the basic concepts of the conventional single quantum MRI techniques. It is supplemented by the basic knowledge required to understand multi-quantum MRI. Practical illustrations are included both on recent developments in conventional MRI and the MQ-MRI. This is to illustrate the connection between theoretical concepts and their scope in the clinical applications. The Part II initially sets out the basic details about quadrupole charge distribution present in certain nuclei and their importance about the functions they perform in our brain. Some simplified final mathematical expressions are included to illustrate facts about the basic concepts of the quantum level interactions between magnetic dipole and the electric quadrupole behavior of useful nuclei present in the brain. Selected practical illustrations, from research and clinical pra...

Love songs, bird brains and diffusion tensor imaging.

Science.gov (United States)

De Groof, Geert; Van der Linden, Annemie

2010-08-01

The song control system of songbirds displays a remarkable seasonal neuroplasticity in species in which song output also changes seasonally. Thus far, this song control system has been extensively analyzed by histological and electrophysiological methods. However, these approaches do not provide a global view of the brain and/or do not allow repeated measurements, which are necessary to establish causal correlations between alterations in neural substrate and behavior. Research has primarily been focused on the song nuclei themselves, largely neglecting their interconnections and other brain regions involved in seasonally changing behavior. In this review, we introduce and explore the song control system of songbirds as a natural model for brain plasticity. At the same time, we point out the added value of the songbird brain model for in vivo diffusion tensor techniques and its derivatives. A compilation of the diffusion tensor imaging (DTI) data obtained thus far in this system demonstrates the usefulness of this in vivo method for studying brain plasticity. In particular, it is shown to be a perfect tool for long-term studies of morphological and cellular changes of specific brain circuits in different endocrine/photoperiod conditions. The method has been successfully applied to obtain quantitative measurements of seasonal changes of fiber tracts and nuclei from the song control system. In addition, outside the song control system, changes have been discerned in the optic chiasm and in an interhemispheric connection. DTI allows the detection of seasonal changes in a region analogous to the mammalian secondary auditory cortex and in regions of the 'social behavior network', an interconnected group of structures that controls multiple social behaviors, including aggression and courtship. DTI allows the demonstration, for the first time, that the songbird brain in its entirety exhibits an extreme seasonal plasticity which is not merely limited to the song control

High-throughput dual-color precision imaging for brain-wide mapping of the connectome with cytoarchitectonic landmarks at the cellular level (Conference Presentation)

Science.gov (United States)

Luo, Qingming; Gong, Hui; Yuan, Jing; Li, Xiangning; Li, Anan; Xu, Tonghui

2017-02-01

Deciphering the fine morphology and precise location of neurons and neural circuits are crucial to enhance our understanding of brain function and diseases. Traditionally, we have to map brain images to coarse axial-sampling planar reference atlases to orient neural structures. However, this means might fail to orient neural projections at single-cell resolution due to position errors resulting from individual differences at the cellular level. Here, we present a high-throughput imaging method that can automatically obtain the fine morphologies and precise locations of both neurons and circuits, employing wide-field large-volume tomography to acquire three-dimensional images of thick tissue and implementing real-time soma counterstaining to obtain cytoarchitectonic landmarks during the imaging process. The reconstruction and orientation of brain-wide neural circuits at single-neuron resolution can be accomplished for the same mouse brain without additional counterstains or image registration. Using our method, mouse brain imaging datasets of multiple type-specific neurons and circuits were successfully acquired, demonstrating the versatility. The results show that the simultaneous acquisition of labeled neural structures and cytoarchitecture reference at single-neuron resolution in the same brain greatly facilitates precise tracing of long-range projections and accurate locating of nuclei. Our method provides a novel and effective tool for application in studies on genetic dissection, brain function and the pathology of the nervous system.

Learning-based prediction of gestational age from ultrasound images of the fetal brain.

Science.gov (United States)

Namburete, Ana I L; Stebbing, Richard V; Kemp, Bryn; Yaqub, Mohammad; Papageorghiou, Aris T; Alison Noble, J

2015-04-01

We propose an automated framework for predicting gestational age (GA) and neurodevelopmental maturation of a fetus based on 3D ultrasound (US) brain image appearance. Our method capitalizes on age-related sonographic image patterns in conjunction with clinical measurements to develop, for the first time, a predictive age model which improves on the GA-prediction potential of US images. The framework benefits from a manifold surface representation of the fetal head which delineates the inner skull boundary and serves as a common coordinate system based on cranial position. This allows for fast and efficient sampling of anatomically-corresponding brain regions to achieve like-for-like structural comparison of different developmental stages. We develop bespoke features which capture neurosonographic patterns in 3D images, and using a regression forest classifier, we characterize structural brain development both spatially and temporally to capture the natural variation existing in a healthy population (N=447) over an age range of active brain maturation (18-34weeks). On a routine clinical dataset (N=187) our age prediction results strongly correlate with true GA (r=0.98,accurate within±6.10days), confirming the link between maturational progression and neurosonographic activity observable across gestation. Our model also outperforms current clinical methods by ±4.57 days in the third trimester-a period complicated by biological variations in the fetal population. Through feature selection, the model successfully identified the most age-discriminating anatomies over this age range as being the Sylvian fissure, cingulate, and callosal sulci. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Automatic registration of imaging mass spectrometry data to the Allen Brain Atlas transcriptome

Science.gov (United States)

Abdelmoula, Walid M.; Carreira, Ricardo J.; Shyti, Reinald; Balluff, Benjamin; Tolner, Else; van den Maagdenberg, Arn M. J. M.; Lelieveldt, B. P. F.; McDonnell, Liam; Dijkstra, Jouke

2014-03-01

Imaging Mass Spectrometry (IMS) is an emerging molecular imaging technology that provides spatially resolved information on biomolecular structures; each image pixel effectively represents a molecular mass spectrum. By combining the histological images and IMS-images, neuroanatomical structures can be distinguished based on their biomolecular features as opposed to morphological features. The combination of IMS data with spatially resolved gene expression maps of the mouse brain, as provided by the Allen Mouse Brain atlas, would enable comparative studies of spatial metabolic and gene expression patterns in life-sciences research and biomarker discovery. As such, it would be highly desirable to spatially register IMS slices to the Allen Brain Atlas (ABA). In this paper, we propose a multi-step automatic registration pipeline to register ABA histology to IMS- images. Key novelty of the method is the selection of the best reference section from the ABA, based on pre-processed histology sections. First, we extracted a hippocampus-specific geometrical feature from the given experimental histological section to initially localize it among the ABA sections. Then, feature-based linear registration is applied to the initially localized section and its two neighbors in the ABA to select the most similar reference section. A non-rigid registration yields a one-to-one mapping of the experimental IMS slice to the ABA. The pipeline was applied on 6 coronal sections from two mouse brains, showing high anatomical correspondence, demonstrating the feasibility of complementing biomolecule distributions from individual mice with the genome-wide ABA transcriptome.

Brain involvement in patients with inflammatory bowel disease: a voxel-based morphometry and diffusion tensor imaging study.

Science.gov (United States)

Zikou, Anastasia K; Kosmidou, Maria; Astrakas, Loukas G; Tzarouchi, Loukia C; Tsianos, Epameinondas; Argyropoulou, Maria I

2014-10-01

To investigate structural brain changes in inflammatory bowel disease (IBD). Brain magnetic resonance imaging (MRI) was performed on 18 IBD patients (aged 45.16 ± 14.71 years) and 20 aged-matched control subjects. The imaging protocol consisted of a sagittal-FLAIR, a T1-weighted high-resolution three-dimensional spoiled gradient-echo sequence, and a multisession spin-echo echo-planar diffusion-weighted sequence. Differences between patients and controls in brain volume and diffusion indices were evaluated using the voxel-based morphometry (VBM) and tract-based spatial statistics (TBSS) methods, respectively. The presence of white-matter hyperintensities (WMHIs) was evaluated on FLAIR images. VBM revealed decreased grey matter (GM) volume in patients in the fusiform and the inferior temporal gyrus bilaterally, the right precentral gyrus, the right supplementary motor area, the right middle frontal gyrus and the left superior parietal gyrus (p tensor imaging detects microstructural brain abnormalities in IBD. • Voxel based morphometry reveals brain atrophy in IBD.

Proton MRS imaging in pediatric brain tumors

Energy Technology Data Exchange (ETDEWEB)

Zarifi, Maria [Aghia Sophia Children' s Hospital, Department of Radiology, Athens (Greece); Tzika, A.A. [Harvard Medical School, Department of Surgery, Massachusetts General Hospital, Boston, MA (United States); Shriners Burn Hospital, Boston, MA (United States)

2016-06-15

Magnetic resonance (MR) techniques offer a noninvasive, non-irradiating yet sensitive approach to diagnosing and monitoring pediatric brain tumors. Proton MR spectroscopy (MRS), as an adjunct to MRI, is being more widely applied to monitor the metabolic aspects of brain cancer. In vivo MRS biomarkers represent a promising advance and may influence treatment choice at both initial diagnosis and follow-up, given the inherent difficulties of sequential biopsies to monitor therapeutic response. When combined with anatomical or other types of imaging, MRS provides unique information regarding biochemistry in inoperable brain tumors and can complement neuropathological data, guide biopsies and enhance insight into therapeutic options. The combination of noninvasively acquired prognostic information and the high-resolution anatomical imaging provided by conventional MRI is expected to surpass molecular analysis and DNA microarray gene profiling, both of which, although promising, depend on invasive biopsy. This review focuses on recent data in the field of MRS in children with brain tumors. (orig.)

Accurate and robust brain image alignment using boundary-based registration.

Science.gov (United States)

Greve, Douglas N; Fischl, Bruce

2009-10-15

The fine spatial scales of the structures in the human brain represent an enormous challenge to the successful integration of information from different images for both within- and between-subject analysis. While many algorithms to register image pairs from the same subject exist, visual inspection shows that their accuracy and robustness to be suspect, particularly when there are strong intensity gradients and/or only part of the brain is imaged. This paper introduces a new algorithm called Boundary-Based Registration, or BBR. The novelty of BBR is that it treats the two images very differently. The reference image must be of sufficient resolution and quality to extract surfaces that separate tissue types. The input image is then aligned to the reference by maximizing the intensity gradient across tissue boundaries. Several lower quality images can be aligned through their alignment with the reference. Visual inspection and fMRI results show that BBR is more accurate than correlation ratio or normalized mutual information and is considerably more robust to even strong intensity inhomogeneities. BBR also excels at aligning partial-brain images to whole-brain images, a domain in which existing registration algorithms frequently fail. Even in the limit of registering a single slice, we show the BBR results to be robust and accurate.

Functional brain imaging - baric and clinical questions

International Nuclear Information System (INIS)

Mager, T.; Moeller, H.J.

1997-01-01

The advancing biological knowledge of disease processes plays a central part in the progress of modern psychiatry. An essential contribution comes from the functional and structural brain imaging techniques (CT, MRI, SPECT, PET). Their application is important for biological oriented research in psychiatry and there is also a growing relevance in clinical aspects. This development is taken into account by recent diagnostic classification systems in psychiatry. The capabilities and limitations of functional brain imaging in the context of research and clinic will be presented and discussed by examples and own investigations. (orig.) [de

Mr imaging and mr spectroscopy of brain metastases by mr perfusion

International Nuclear Information System (INIS)

Weber, Marc-Andre; Lichy, M.P.; Thilmann, C.; Guenther, M.; Bachert, P.; Delorme, S.; Schad, L.R.; Debus, J.; Schlemmer, H.P.; Maudsley, A.A.

2003-01-01

In follow-up examinations of irradiated brain metastases conventional contrast-enhanced morphological MR imaging is often unable to distinguish between transient radiation effects, radionecrosis, and tumor recurrence. To evaluate changes of relative cerebral blood flow (rCBF) in irradiated brain metastases arterial spin-labeling techniques (ASL) were applied and compared to the outcome of 1 H MR spectroscopy and spectroscopic imaging ( 1 H MRS, SI). Patients and methods In 2 patients follow-up examinations of irradiated brain metastases were performed on a 1.5-T tomograph (average single dose: 20 Gy/80% isodose). Relative CBF values of gray matter (GM), white matter (WM), and metastases (Met) were measured by means of the ASL techniques ITS-FAIR and Q2TIPS. 1 H MRS was performed with PRESS 1500/135. In both patients with initially hyperperfused metastases (Met/GM >1) the reduction of rCBF after stereotactic radiosurgery indicated response to treatment - even if the contrast-enhancing region increased - while increasing rCBF values indicated tumor progression. The findings were confirmed by 1 H MRS, SI and subsequent follow-up. The ASL techniques ITS-FAIR and Q2TIPS are able to monitor changes of rCBF in irradiated brain metastases. The two cases imply a possible role for ASL-MR perfusion imaging and 1 H MR spectroscopy in differentiating radiation effects from tumor progression. (orig.) [de

Advanced Pediatric Brain Imaging Research Program

Science.gov (United States)

2016-10-01

pediatric magnetic resonance imaging ( MRI ) techniques are revolutionizing our understanding of brain injury, its potential for recovery, and...training program, advanced MRI , brain injury. 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER OF PAGES 19a. NAME OF RESPONSIBLE...is located at www.MilitaryMedED.com. The site can be accessed from any device web browser (personal computer, tablet or phone) and operating system

Brain Atlas Fusion from High-Thickness Diagnostic Magnetic Resonance Images by Learning-Based Super-Resolution.

Science.gov (United States)

Zhang, Jinpeng; Zhang, Lichi; Xiang, Lei; Shao, Yeqin; Wu, Guorong; Zhou, Xiaodong; Shen, Dinggang; Wang, Qian

2017-03-01

It is fundamentally important to fuse the brain atlas from magnetic resonance (MR) images for many imaging-based studies. Most existing works focus on fusing the atlases from high-quality MR images. However, for low-quality diagnostic images (i.e., with high inter-slice thickness), the problem of atlas fusion has not been addressed yet. In this paper, we intend to fuse the brain atlas from the high-thickness diagnostic MR images that are prevalent for clinical routines. The main idea of our works is to extend the conventional groupwise registration by incorporating a novel super-resolution strategy. The contribution of the proposed super-resolution framework is two-fold. First, each high-thickness subject image is reconstructed to be isotropic by the patch-based sparsity learning. Then, the reconstructed isotropic image is enhanced for better quality through the random-forest-based regression model. In this way, the images obtained by the super-resolution strategy can be fused together by applying the groupwise registration method to construct the required atlas. Our experiments have shown that the proposed framework can effectively solve the problem of atlas fusion from the low-quality brain MR images.

Segmentation of internal brain structures in three-dimensional nuclear magnetic resonance imaging

International Nuclear Information System (INIS)

Geraud, Th.

1998-01-01

For neurological studies, the in vivo aspect of imaging systems is very attractive. Brain images are currently a classical tool used in clinical routine and research. The most appropriate system to observe brain anatomy is tridimensional magnetic resonance imaging, and a major issue of image processing is to segment automatically cerebral structures. This is the scope of our thesis. The number of applications is steadily growing: morphometric measurements, pathology detection, surgery planning, getting a reference for functional studies,a and so forth. The use of pattern recognition to classify the different cerebral tissues from the only radiometric levels of the images is limited. Even supervised, these methods can not lead to distinguish easily several classes of grey matter. When these methods are automatic, their use has to be empirical in order to ensure robust results, and has to be restricted to regions of interest in order to get reliable results. As these methods do not fully respect the spatial consistency of classes in the images, we have introduced contextual information with the help of different formalisms. With Markovian regularization, we have shown that energetic terms of localization permit the separation of two grey classes: cortex and central nuclei. With mathematical morphology, we have proposed processing chains dedicated to several cerebral objects; in particular, brain segmentation is robust and reproducible, and we have successfully obtained individual markers for lateral ventricles, caudate nuclei, putamen and thalami. We have also proposed a contextual method to estimate pure tissue characteristics from a rough segmentation. Our main contribution has been to present a recognition method which is progressive and atlas guided. The originality of this method is manifold. At first, it takes into account structural information processed as flexible spatial constraints the formalism of which relies on fuzzy set theory and information fusion

Intraoperative Imaging Modalities and Compensation for Brain Shift in Tumor Resection Surgery

Directory of Open Access Journals (Sweden)

Siming Bayer

2017-01-01

Full Text Available Intraoperative brain shift during neurosurgical procedures is a well-known phenomenon caused by gravity, tissue manipulation, tumor size, loss of cerebrospinal fluid (CSF, and use of medication. For the use of image-guided systems, this phenomenon greatly affects the accuracy of the guidance. During the last several decades, researchers have investigated how to overcome this problem. The purpose of this paper is to present a review of publications concerning different aspects of intraoperative brain shift especially in a tumor resection surgery such as intraoperative imaging systems, quantification, measurement, modeling, and registration techniques. Clinical experience of using intraoperative imaging modalities, details about registration, and modeling methods in connection with brain shift in tumor resection surgery are the focuses of this review. In total, 126 papers regarding this topic are analyzed in a comprehensive summary and are categorized according to fourteen criteria. The result of the categorization is presented in an interactive web tool. The consequences from the categorization and trends in the future are discussed at the end of this work.

Magnetic resonance imaging of the fetal brain.

Science.gov (United States)

Tee, L Mf; Kan, E Yl; Cheung, J Cy; Leung, W C

2016-06-01

This review covers the recent literature on fetal brain magnetic resonance imaging, with emphasis on techniques, advances, common indications, and safety. We conducted a search of MEDLINE for articles published after 2010. The search terms used were "(fetal OR foetal OR fetus OR foetus) AND (MR OR MRI OR [magnetic resonance]) AND (brain OR cerebral)". Consensus statements from major authorities were also included. As a result, 44 relevant articles were included and formed the basis of this review. One major challenge is fetal motion that is largely overcome by ultra-fast sequences. Currently, single-shot fast spin-echo T2-weighted imaging remains the mainstay for motion resistance and anatomical delineation. Recently, a snap-shot inversion recovery sequence has enabled robust T1-weighted images to be obtained, which is previously a challenge for standard gradient-echo acquisitions. Fetal diffusion-weighted imaging, diffusion tensor imaging, and magnetic resonance spectroscopy are also being developed. With multiplanar capabilities, superior contrast resolution and field of view, magnetic resonance imaging does not have the limitations of sonography, and can provide additional important information. Common indications include ventriculomegaly, callosum and posterior fossa abnormalities, and twin complications. There are safety concerns about magnetic resonance-induced heating and acoustic damage but current literature showed no conclusive evidence of deleterious fetal effects. The American College of Radiology guideline states that pregnant patients can be accepted to undergo magnetic resonance imaging at any stage of pregnancy if risk-benefit ratio to patients warrants that the study be performed. Magnetic resonance imaging of the fetal brain is a safe and powerful adjunct to sonography in prenatal diagnosis. It can provide additional information that aids clinical management, prognostication, and counselling.

Incidental ferumoxytol artifacts in clinical brain MR imaging

Energy Technology Data Exchange (ETDEWEB)

Bowser, Bruce A.; Campeau, Norbert G.; Carr, Carrie M.; Diehn, Felix E.; McDonald, Jennifer S.; Miller, Gary M.; Kaufmann, Timothy J. [Mayo Clinic, Department of Radiology, Rochester, MN (United States)

2016-11-15

Ferumoxytol (Feraheme) is a parenteral therapy approved for treatment of iron deficiency anemia. The product insert for ferumoxytol states that it may affect the diagnostic ability of MRI for up to 3 months. However, the expected effects may not be commonly recognized among clinical neuroradiologists. Our purpose is to describe the artifacts we have seen at our institution during routine clinical practice. We reviewed the patients at our institution that had brain MRI performed within 90 days of receiving intravenous ferumoxytol. The imaging was reviewed for specific findings, including diffusion-weighted imaging vascular susceptibility artifact, gradient-echo echo-planar T2*-weighted vascular susceptibility artifact, SWI/SWAN vascular susceptibility artifact, hypointense vascular signal on T2-weighted images, pre-gadolinium contrast vascular enhancement on magnetization-prepared rapid acquisition gradient echo (MPRAGE) imaging, and effects on post-gadolinium contrast T1 imaging. Multiple artifacts were observed in patients having a brain MRI within 3 days of receiving intravenous ferumoxytol. These included susceptibility artifact on DWI, GRE, and SWAN/SWI imaging, pre-gadolinium contrast increased vascular signal on MPRAGE imaging, and decreased expected enhancement on post-gadolinium contrast T1-weighted imaging. Ferumoxytol can create imaging artifacts which complicate clinical interpretation when brain MRI is performed within 3 days of administration. Recognition of the constellation of artifacts produced by ferumoxytol is important in order to obviate additional unnecessary examinations and mitigate errors in interpretation. (orig.)

Amide Proton Transfer (APT) MR imaging and Magnetization Transfer (MT) MR imaging of pediatric brain development

International Nuclear Information System (INIS)

Zhang, Hong; Kang, Huiying; Peng, Yun; Zhao, Xuna; Jiang, Shanshan; Zhang, Yi; Zhou, Jinyuan

2016-01-01

To quantify the brain maturation process during childhood using combined amide proton transfer (APT) and conventional magnetization transfer (MT) imaging at 3 Tesla. Eighty-two neurodevelopmentally normal children (44 males and 38 females; age range, 2-190 months) were imaged using an APT/MT imaging protocol with multiple saturation frequency offsets. The APT-weighted (APTW) and MT ratio (MTR) signals were quantitatively analyzed in multiple brain areas. Age-related changes in MTR and APTW were evaluated with a non-linear regression analysis. The APTW signals followed a decreasing exponential curve with age in all brain regions measured (R"2 = 0.7-0.8 for the corpus callosum, frontal and occipital white matter, and centrum semiovale). The most significant changes appeared within the first year. At maturation, larger decreases in APTW and lower APTW values were found in the white matter. On the contrary, the MTR signals followed an increasing exponential curve with age in the same brain regions measured, with the most significant changes appearing within the initial 2 years. There was an inverse correlation between the MTR and APTW signal intensities during brain maturation. Together with MT imaging, protein-based APT imaging can provide additional information in assessing brain myelination in the paediatric population. (orig.)

Amide Proton Transfer (APT) MR imaging and Magnetization Transfer (MT) MR imaging of pediatric brain development

Energy Technology Data Exchange (ETDEWEB)

Zhang, Hong; Kang, Huiying; Peng, Yun [Beijing Children' s Hospital, Capital Medical University, Imaging Center, Department of Radiology, Beijing (China); Zhao, Xuna [Philips Healthcare, Beijing (China); Jiang, Shanshan; Zhang, Yi; Zhou, Jinyuan [Johns Hopkins University, Division of MR Research, Department of Radiology, Baltimore, MD (United States)

2016-10-15

To quantify the brain maturation process during childhood using combined amide proton transfer (APT) and conventional magnetization transfer (MT) imaging at 3 Tesla. Eighty-two neurodevelopmentally normal children (44 males and 38 females; age range, 2-190 months) were imaged using an APT/MT imaging protocol with multiple saturation frequency offsets. The APT-weighted (APTW) and MT ratio (MTR) signals were quantitatively analyzed in multiple brain areas. Age-related changes in MTR and APTW were evaluated with a non-linear regression analysis. The APTW signals followed a decreasing exponential curve with age in all brain regions measured (R{sup 2} = 0.7-0.8 for the corpus callosum, frontal and occipital white matter, and centrum semiovale). The most significant changes appeared within the first year. At maturation, larger decreases in APTW and lower APTW values were found in the white matter. On the contrary, the MTR signals followed an increasing exponential curve with age in the same brain regions measured, with the most significant changes appearing within the initial 2 years. There was an inverse correlation between the MTR and APTW signal intensities during brain maturation. Together with MT imaging, protein-based APT imaging can provide additional information in assessing brain myelination in the paediatric population. (orig.)

Repeatability of Brain Volume Measurements Made with the Atlas-based Method from T1-weighted Images Acquired Using a 0.4 Tesla Low Field MR Scanner.

Science.gov (United States)

Goto, Masami; Suzuki, Makoto; Mizukami, Shinya; Abe, Osamu; Aoki, Shigeki; Miyati, Tosiaki; Fukuda, Michinari; Gomi, Tsutomu; Takeda, Tohoru

2016-10-11

An understanding of the repeatability of measured results is important for both the atlas-based and voxel-based morphometry (VBM) methods of magnetic resonance (MR) brain volumetry. However, many recent studies that have investigated the repeatability of brain volume measurements have been performed using static magnetic fields of 1-4 tesla, and no study has used a low-strength static magnetic field. The aim of this study was to investigate the repeatability of measured volumes using the atlas-based method and a low-strength static magnetic field (0.4 tesla). Ten healthy volunteers participated in this study. Using a 0.4 tesla magnetic resonance imaging (MRI) scanner and a quadrature head coil, three-dimensional T 1 -weighted images (3D-T 1 WIs) were obtained from each subject, twice on the same day. VBM8 software was used to construct segmented normalized images [gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) images]. The regions-of-interest (ROIs) of GM, WM, CSF, hippocampus (HC), orbital gyrus (OG), and cerebellum posterior lobe (CPL) were generated using WFU PickAtlas. The percentage change was defined as[100 × (measured volume with first segmented image - mean volume in each subject)/(mean volume in each subject)]The average percentage change was calculated as the percentage change in the 6 ROIs of the 10 subjects. The mean of the average percentage changes for each ROI was as follows: GM, 0.556%; WM, 0.324%; CSF, 0.573%; HC, 0.645%; OG, 1.74%; and CPL, 0.471%. The average percentage change was higher for the orbital gyrus than for the other ROIs. We consider that repeatability of the atlas-based method is similar between 0.4 and 1.5 tesla MR scanners. To our knowledge, this is the first report to show that the level of repeatability with a 0.4 tesla MR scanner is adequate for the estimation of brain volume change by the atlas-based method.

Clinical correlative evaluation of an iterative method for reconstruction of brain SPECT images

International Nuclear Information System (INIS)

Nobili, Flavio; Vitali, Paolo; Calvini, Piero; Bollati, Francesca; Girtler, Nicola; Delmonte, Marta; Mariani, Giuliano; Rodriguez, Guido

2001-01-01

Background: Brain SPECT and PET investigations have showed discrepancies in Alzheimer's disease (AD) when considering data deriving from deeply located structures, such as the mesial temporal lobe. These discrepancies could be due to a variety of factors, including substantial differences in gamma-cameras and underlying technology. Mesial temporal structures are deeply located within the brain and the commonly used Filtered Back-Projection (FBP) technique does not fully take into account either the physical parameters of gamma-cameras or geometry of collimators. In order to overcome these limitations, alternative reconstruction methods have been proposed, such as the iterative method of the Conjugate Gradients with modified matrix (CG). However, the clinical applications of these methods have so far been only anecdotal. The present study was planned to compare perfusional SPECT data as derived from the conventional FBP method and from the iterative CG method, which takes into account the geometrical and physical characteristics of the gamma-camera, by a correlative approach with neuropsychology. Methods: Correlations were compared between perfusion of the hippocampal region, as achieved by both the FBP and the CG reconstruction methods, and a short-memory test (Selective Reminding Test, SRT), specifically addressing one of its function. A brain-dedicated camera (CERASPECT) was used for SPECT studies with 99m Tc-hexamethylpropylene-amine-oxime in 23 consecutive patients (mean age: 74.2±6.5) with mild (Mini-Mental Status Examination score ≥15, mean 20.3±3), probable AD. Counts from a hippocampal region in each hemisphere were referred to the average thalamic counts. Results: Hippocampal perfusion significantly correlated with the MMSE score with similar statistical significance (p<0.01) between the two reconstruction methods. Correlation between hippocampal perfusion and the SRT score was better with the CG method (r=0.50 for both hemispheres, p<0.01) than with

Clinical correlative evaluation of an iterative method for reconstruction of brain SPECT images

Energy Technology Data Exchange (ETDEWEB)

Nobili, Flavio E-mail: fnobili@smartino.ge.it; Vitali, Paolo; Calvini, Piero; Bollati, Francesca; Girtler, Nicola; Delmonte, Marta; Mariani, Giuliano; Rodriguez, Guido

2001-08-01