ライフサイエンスコーパス: diffusion tensor imaging

1 l imaging and fibre tracking with the use of diffusion tensor imaging.

2 nations of white-matter tracts identified by diffusion tensor imaging.

3 ges in white matter, which were confirmed by diffusion tensor imaging.

4 g resting-state functional MRI (rs-fMRI) and diffusion tensor imaging.

5 dex measurement of the corpus callosum using diffusion tensor imaging.

6 isotropy (FA) and mean diffusivity (MD) with diffusion tensor imaging.

7 s of apathy, depression, quality of life and diffusion tensor imaging.

8 nalyses included voxel-based morphometry and diffusion tensor imaging.

9 s throughout the brain were obtained through diffusion tensor imaging.

10 sis of fractional anisotropy (FA) in newborn diffusion tensor imaging.

11 ractional anisotropy values, as derived from diffusion tensor imaging.

12 ubjects underwent volumetric T1-weighted and diffusion tensor imaging.

13 linical control subjects were assessed using diffusion tensor imaging.

14 white matter microstructure was assessed by diffusion tensor imaging.

15 Diffusion tensor imaging, a translational imaging techni

16 hip among presurgical cognitive performance, diffusion tensor imaging abnormalities and postoperative

17 aumatic brain injury was not associated with diffusion tensor imaging abnormalities detectable with t

18 Diffusion tensor imaging abnormalities in a cohort of 97

19 While the diffusion tensor imaging abnormalities observed in the c

20 Presurgical diffusion tensor imaging abnormalities of the cerebellum

21 ntrolling for general cognitive performance, diffusion tensor imaging abnormalities of the cerebellum

22 matter and white matter atrophy, as well as diffusion-tensor imaging abnormalities (P < .01).

23 Perfusion and diffusion tensor imaging accounted for variation in clin

24 sotropy in various brain regions revealed by diffusion tensor imaging, along with increased levels of

25 Diffusion tensor imaging also detected deficits in the c

26 Diffusion tensor imaging analysis revealed a significant

27 The diffusion tensor imaging analysis revealed that fraction

28 assessments, and magnetic resonance imaging, diffusion tensor imaging and (18)F-fluorodeoxyglucose po

29 be seizures in temporal lobe epilepsy, using diffusion tensor imaging and automated fibre quantificat

30 lly increases risk of MMI, to undertake both diffusion tensor imaging and cellular studies to evaluat

31 Structural networks based on diffusion tensor imaging and cortical thickness were ana

32 herotomy (at mean age: 12.4 years) underwent Diffusion Tensor Imaging and evaluation of motor functio

33 Diffusion tensor imaging and fluorescence microscopy stu

34 structural connectivity (SC) as measured by diffusion tensor imaging and frontoparietal functional c

35 also can change white matter as measured by diffusion tensor imaging and increase resting-state midl

36 e to tissue microstructural changes, such as diffusion tensor imaging and magnetization transfer imag

37 haemic changes, all of which can affect both diffusion tensor imaging and magnetization transfer imag

38 roimaging methods-surface-based morphometry, diffusion tensor imaging and network-based statistics-ea

39 Here, we utilize quantitative techniques of diffusion tensor imaging and neurite orientation dispers

40 opontine nucleus structural connectivity via diffusion tensor imaging and performance on cognitive te

41 We used diffusion tensor imaging and probabilistic tractography

42 (n = 12; age and sex matched), we performed diffusion tensor imaging and structural MRI, polysomnogr

43 e and hippocampal volume were assessed using diffusion tensor imaging and structural MRI, respectivel

44 , anatomical connectivity was examined using diffusion tensor imaging and tract-based spatial statist

45 Network models were constructed from diffusion tensor imaging and tractography in physically

46 Diffusion tensor imaging and transverse relaxation time

47 Sixty-direction diffusion-tensor imaging and magnetization-prepared rapi

48 Diffusion-tensor imaging and serial neurocognitive testi

49 operties and second-language immersion using diffusion tensor imaging, and (ii) to determine whether

50 control participants of both sexes underwent diffusion tensor imaging, and a large subset performed a

51 functional assessment, structural MRI (3 T), diffusion tensor imaging, and arterial spin labelled per

52 ed networks was probed using high-resolution diffusion tensor imaging, and cellular/regional activati

53 nance imaging, fractional anisotropy (FA) of diffusion tensor imaging, and cognitive differences in a

54 t 3T T1-weighted magnetic resonance imaging, diffusion tensor imaging, and cognitive testing.

55 logical immunostaining, electron microscopy, diffusion tensor imaging, and electrophysiology.

56 We evaluated the animals using CT, MRI, diffusion tensor imaging, and immunohistochemistry.

57 and the medial lemniscus was performed with diffusion tensor imaging, and lesions were classified by

58 in-behavior relationships derived from fMRI, diffusion tensor imaging, and online repetitive transcra

59 imaging measures of voxel-based morphometry, diffusion tensor imaging, and resting-state functional c

60 d with amyloid positron emission tomography, diffusion tensor imaging, and structural magnetic resona

61 rent ALS pathological stages as evaluated by diffusion-tensor imaging, and in single patients NFL lev

62 Conclusion Diffusion-weighted imaging, diffusion-tensor imaging, and intravoxel incoherent moti

63 However, data based primarily on diffusion tensor imaging approaches remain inconclusive.

64 ural MRI, resting--state functional MRI, and diffusion tensor imaging--are highly sensitive to common

65 Fractional anisotropy was calculated from diffusion tensor imaging as a measure of diffuse axonal

66 al connectivity abnormalities, measured with diffusion tensor imaging, as well as the convergent impa

67 microstructural organization using neonatal diffusion tensor imaging, associated with skills importa

68 ns) of healthy rat ventricles-obtained using diffusion tensor imaging at 100 mum resolution-were regi

69 erm newborns underwent a brain MRI including diffusion tensor imaging at approximately 2 weeks of age

70 d underwent resting-state functional MRI and diffusion tensor imaging at each time point, along with

71 te matter tract degeneration was assessed on diffusion-tensor imaging at each time-point.

72 ine, neuropsychological, retinal vessel, and diffusion tensor imaging-based cerebral WM evaluations.

73 A high amyloid load does not influence diffusion tensor imaging-based measures of white matter

74 Using diffusion tensor imaging-based probabilistic tracking, w

75 Magnetic resonance imaging (T1-weighted and diffusion tensor imaging-based structural connectome), a

76 a white matter diffusion profile by means of diffusion-tensor imaging-based parameters and constraine

77 in microstructural integrity, as measured by diffusion tensor imaging before surgery, on postoperativ

78 For diffusion tensor imaging, brains were scanned with a dif

79 y and microstructural brain development with diffusion tensor imaging by measuring fractional anisotr

80 However, both clinical and DTI diffusion-tensor imaging changes did not persist beyond

81 opological centrality of nodes in the normal diffusion tensor imaging connectome were generally repli

82 RI (85% sensitivity, 83% specificity) and on diffusion tensor imaging data (88% sensitivity, 92% spec

83 We analyzed diffusion tensor imaging data from 35 patients and 35 he

84 h and a regional-based analysis, we analyzed diffusion tensor imaging data from healthy individuals w

85 of brain anatomical networks estimated from diffusion tensor imaging data on healthy volunteers (n =

86 ntations could be represented by each of the diffusion tensor imaging data sets or by an idealized ru

87 Diffusion tensor imaging data were acquired in 63 patien

88 ng and functional magnetic resonance imaging/diffusion tensor imaging data, we also find that variabi

89 tivity matrices calculated from skeletonized diffusion tensor imaging data.

90 s, we employed probabilistic tractography on diffusion tensor imaging data.

91 Here, analysing a publicly shared diffusion tensor imaging dataset, we found that, during

92 aging scanner to acquire T1-weighted images, diffusion tensor imaging datasets, and single volume dif

93 ging was used to calculate T1 volumetric and Diffusion Tensor Imaging derived fractional anisotropy a

94 PT and aMF in motor compensation by relating diffusion-tensor-imaging-derived parameters of white mat

95 invasive magnetic resonance spectroscopy and diffusion tensor imaging detected differences between th

96 changes corresponded with Magnetic Resonance Diffusion Tensor Imaging differences.

97 tter structure and function were assessed by diffusion tensor imaging (DTI) and (1)H magnetic resonan

98 of the uncinate fasciculus (UF) measured by Diffusion Tensor Imaging (DTI) and anxiety symptoms in a

99 ify a PD-specific MRI pattern using combined diffusion tensor imaging (DTI) and arterial spin labelin

100 actional anisotropy (FA) measure provided by diffusion tensor imaging (DTI) and cross-hemispheric com

101 etest reliability of high spatial resolution diffusion tensor imaging (DTI) and diffusion kurtosis im

102 21, crush = 23, cut/repair = 19) and ex vivo diffusion tensor imaging (DTI) and diffusion kurtosis im

103 ation in the field of epilepsy, such as with Diffusion Tensor Imaging (DTI) and Diffusion Tensor Trac

104 tions between PC integrity, measured through diffusion tensor imaging (DTI) and fractional anisotropy

105 Diffusion tensor imaging (DTI) and genome-wide single-nu

106 ve cerebrospinal fluid (CSF) sampling, brain diffusion tensor imaging (DTI) and magnetic resonance sp

107 Metrics of diffusion tensor imaging (DTI) and magnetization transfe

108 Diffusion tensor imaging (DTI) and neurite orientation d

109 ic disorders, and integrated these data with diffusion tensor imaging (DTI) and psychometric measurem

110 Diffusion tensor imaging (DTI) and resting-state functio

111 not only contrast-enhanced T1 MRI, but also diffusion tensor imaging (DTI) and resting-state functio

112 ned longitudinally from 6 to 48 months using diffusion tensor imaging (DTI) and tract-based spatial s

113 al, EVF/task-based and resting-state MRI and diffusion tensor imaging (DTI) before and after completi

114 d the processing and statistical analyses of diffusion tensor imaging (DTI) data across sites and met

115 Processing of diffusion tensor imaging (DTI) data and statistical anal

116 We conducted a secondary analysis of diffusion tensor imaging (DTI) data for 28 contact athle

117 Diffusion tensor imaging (DTI) data were acquired from 2

118 monemia-associated astrocytic changes, while diffusion tensor imaging (DTI) demonstrates changes in n

119 Diffusion tensor imaging (DTI) enables comprehensive who

120 Diffusion tensor imaging (DTI) enables in-vivo quantific

121 encing a first episode of psychosis received diffusion tensor imaging (DTI) exams, clinical assessmen

122 While diffusion tensor imaging (DTI) failed to distinguish sim

123 INTRODUCTION: Discrepancies between diffusion tensor imaging (DTI) findings and functional r

124 This study investigates diffusion tensor imaging (DTI) for providing microstruct

125 Diffusion tensor imaging (DTI) harnesses the power of co

126 Diffusion tensor imaging (DTI) has been used to evaluate

127 included using both T1-weighted imaging and diffusion tensor imaging (DTI) in a cross-sectional samp

128 Diffusion tensor imaging (DTI) is a derivative MRI techn

129 Diffusion tensor imaging (DTI) is a unique in vivo imagi

130 tructural changes in white matter (WM) using diffusion tensor imaging (DTI) may be a useful outcome m

131 ted white matter abnormalities of ASPD using diffusion tensor imaging (DTI) measures: fractional anis

132 We extracted tract-specific diffusion tensor imaging (DTI) metrics to assess changes

133 fer measurements), myelin water fraction and diffusion tensor imaging (DTI) metrics, in addition to p

134 Diffusion tensor imaging (DTI) MRI is a sensitive techni

135 pecific structural connectivity derived from diffusion tensor imaging (DTI) of 22 individuals with le

136 Diffusion tensor imaging (DTI) of perfusion fixed specim

137 Structural connectivity was defined by diffusion tensor imaging (DTI) of white matter tract mic

138 Standard diffusion tensor imaging (DTI) parameters were computed

139 Diffusion tensor imaging (DTI) provides us an insight in

140 sotropy (FA) and mean diffusivity (MD) in MR diffusion tensor imaging (DTI) requires adequate signal-

141 on structural magnetic resonance imaging and diffusion tensor imaging (DTI) scanning.

142 ks) underwent magnetic resonance imaging and diffusion tensor imaging (DTI) scans, early in life (pos

143 Diffusion tensor imaging (DTI) studies consistently repo

144 with Down syndrome (DS) are limited, with no diffusion tensor imaging (DTI) studies covering that age

145 Diffusion tensor imaging (DTI) studies have detected whi

146 hysiology of bipolar disorder (BD); however, diffusion tensor imaging (DTI) studies have reported het

147 Diffusion tensor imaging (DTI) studies in the related co

148 Cross-sectional diffusion tensor imaging (DTI) studies indicate that, af

149 Diffusion tensor imaging (DTI) studies show widespread w

150 To date, most diffusion tensor imaging (DTI) studies used fractional a

151 This investigation was a cross-sectional diffusion tensor imaging (DTI) study at an outpatient ac

152 urpose To develop a diagnostic tool based on diffusion tensor imaging (DTI) to distinguish between PS

153 impact of brief exposure to hyperoxia using diffusion tensor imaging (DTI) to identify axonal injury

154 The aim of this study was to use MR diffusion tensor imaging (DTI) to identify brain microst

155 Thirty-three MMT patients underwent diffusion tensor imaging (DTI) twice - at the start of t

156 Brain diffusion tensor imaging (DTI) was performed before and

157 ng state functional connectivity (rs-FC) and diffusion tensor imaging (DTI) yielded convergent result

158 Here, we applied diffusion tensor imaging (DTI), a modality of magnetic r

159 unctional magnetic resonance imaging (fMRI), diffusion tensor imaging (DTI), and electroencephalograp

160 1) who underwent magnetic resonance imaging, diffusion tensor imaging (DTI), and positron emission to

161 such as single voxel spectroscopy (MRS) and diffusion tensor imaging (DTI), in children with X-linke

162 tients by using magnetic resonance (MRI) and diffusion tensor imaging (DTI), unbiased stereology and

163 the thalamus and less thalamic fiber loss by diffusion tensor imaging (DTI).

164 ine motor skill assessment and scanning with diffusion tensor imaging (DTI).

165 tion and can be assessed non-invasively with diffusion tensor imaging (DTI).

166 (FA) and mean diffusivity were derived from diffusion tensor imaging (DTI).

167 th improvements in cognitive function, using diffusion tensor imaging (DTI).

168 ond the motor pathways, can be visualised by diffusion tensor imaging (DTI).

169 ment effects on white matter integrity using diffusion tensor imaging (DTI).

170 M) in multiple sclerosis (MS) patients using diffusion tensor imaging (DTI).

171 quantitative magnetic resonance imaging and diffusion tensor imaging (DTI).

172 monstrated using fiber tractography based on diffusion tensor imaging (DTI).

173 ting transsexuals and healthy controls using diffusion tensor imaging (DTI).

174 hite matter microstructural properties using Diffusion Tensor Imaging (DTI).

175 ed magnetic resonance (MR) imaging, with two diffusion-tensor imaging (DTI) acquisitions and arterial

176 ology of the brain was examined by MRI using diffusion-tensor imaging (DTI) and immunohistochemistry

177 Purpose To determine the changes of diffusion-tensor imaging (DTI) and tractography in the d

178 MRI including diffusion-tensor imaging (DTI) may enable detection of m

179 l DWI, diffusion kurtosis imaging (DKI), and diffusion-tensor imaging (DTI) with quantitative histopa

180 eters from diffusion-weighted imaging (DWI), diffusion-tensor imaging (DTI), and intravoxel incoheren

181 ctober 13, 2011, and June 15, 2015, by using diffusion-tensor imaging (DTI).Materials and MethodsIn t

182 arametric (ie, three-dimensional T1-weighted diffusion tensor imaging [DTI]) brain imaging.

183 l imaging approach (voxel-based morphometry, diffusion-tensor imaging, electroencephalography) to tes

184 Diffusion tensor imaging estimated microstructural prope

185 Stability of diffusion tensor imaging findings was verified by repeat

186 ated brain structural and Magnetic Resonance Diffusion Tensor Imaging findings.

187 Diffusion-tensor imaging findings were correlated with s

188 VI is indicative of better agreement between diffusion tensor imaging fractional anisotropy across th

189 Whole-brain and regional diffusion tensor imaging fractional anisotropy were used

190 te functional magnetic resonance imaging and diffusion tensor imaging fractional anisotropy were used

191 r quantification of brain connectivity using diffusion tensor imaging, functional connectivity, and g

192 l ganglia volumetry; white matter integrity (diffusion tensor imaging); gray matter density (voxel-ba

193 Connectomic approaches using diffusion tensor imaging have contributed to our underst

194 Diffusion-weighted sequences and diffusion tensor imaging have opened a new horizon in ne

195 m as quickly as possible with concurrent 3T diffusion tensor imaging in 164 participants (57.1% fema

196 , we modeled the structural connectome using diffusion tensor imaging in a sample of 949 youths (aged

197 ffusion properties of white matter tracts by diffusion tensor imaging in the presence of cerebrospina

198 rostructural integrity of white matter using diffusion tensor imaging in two healthy control samples

199 and to evaluate white matter integrity with diffusion-tensor imaging in patients who are recovering

200 ic white matter (WM) tracts as detected with diffusion-tensor imaging in the absence of clinically di

201 d mean diffusivity were measured by means of diffusion-tensor imaging in the white matter adjacent to

202 sonance imaging [MRI], resting-state MRI, or diffusion tensor imaging) in combination with multivaria

203 dial diffusivity in this region, measured by diffusion tensor imaging, inversely predicted thickness.

204 Further, we show that diffusion tensor imaging is sensitive to these cellular

205 Diffusion Tensor Imaging is the most advanced imaging te

206 Diffusion-tensor imaging is potentially promising but to

207 This study evaluates whether diffusion tensor imaging magnetic resonance neurography

208 Diffusion tensor imaging maps were calculated and transf

209 atosus with past NPSLE, significantly higher diffusion tensor imaging mean and radial diffusivities w

210 inal fluid (CSF) Ptau collected at baseline, diffusion tensor imaging measure twice, 2 year apart, an

211 crimination power of a novel set of cortical Diffusion Tensor Imaging measures (DTI), on FTD subtypes

212 egional measures of TSPO using [11C]DPA-713, diffusion tensor imaging measures of regional white matt

213 Diffusion tensor imaging measures properties of water di

214 Diffusion tensor imaging measures recovery of axonal inj

215 Correlations among clinical, structural and diffusion tensor imaging measures were calculated.

216 nance imaging brain data included a study of diffusion tensor imaging metrics (mean diffusivity, frac

217 h/without past NPSLE and healthy controls on diffusion tensor imaging metrics and on diffusion coeffi

218 measurement of cord cross-sectional area and diffusion tensor imaging metrics in the GM and posterior

219 ormance of pain attenuation was explained by diffusion tensor imaging metrics of increased white matt

220 Brain white matter diffusion tensor imaging metrics were assessed using who

221 s from C2-3 to T2-3 level were measured, and diffusion tensor imaging metrics, i.e. fractional anisot

222 ng (NODDI) model as well as the conventional diffusion tensor imaging model.

223 orodeoxyglucose PET imaging) and structural (diffusion tensor imaging MRI) measures.

224 sychological assessments, 3 T structural and diffusion tensor imaging MRI, 18F-fluorodeoxyglucose and

225 Children's Environmental Health, we acquired diffusion tensor imaging, multiplanar chemical shift ima

226 ealthy controls using the magnetic resonance diffusion tensor imaging, myocardial tagging, and biomec

227 om T1-weighted volumetric (n = 1,136) and/or diffusion tensor imaging (n = 1,088) had been collected.

228 ion kurtosis imaging as well as conventional diffusion tensor imaging of 89 preterm neonates aged 31-

229 Finally, in vivo diffusion tensor imaging of CSPG4(A131T) mutation carrie

230 y) and volume of axon pathways using in vivo diffusion tensor imaging of fronto-frontal, fronto-tempo

231 sms of local versus distal acupuncture using diffusion tensor imaging of white matter microstructure

232 Diffusion-tensor imaging of the knee was performed at 3.

233 Using diffusion tensor imaging on a subset of patients, we als

234 stigated the association between presurgical diffusion tensor imaging parameters of brain microstruct

235 Group comparisons on tissue volume and diffusion tensor imaging parameters were made between DM

236 0 years without associated changes in GM and diffusion tensor imaging parameters.

237 hy control subjects in postural sway and DTI diffusion-tensor imaging parameters (P < .05).

238 iance were performed to evaluate whether DTI diffusion-tensor imaging parameters significantly change

239 with streamline tractography; values of DTI diffusion-tensor imaging parameters were then obtained f

240 res: Quantitative neurologic examination and diffusion tensor imaging performed 1 to 3 times through

241 temperament, magnetic resonance imaging, and diffusion tensor imaging phenotypes.

242 Diffusion-tensor imaging provided evidence for long-term

243 aims to evaluate how parameters derived from diffusion tensor imaging reflect axonal disruption and d

244 Diffusion tensor imaging revealed reduced reorientation

245 Diffusion tensor imaging revealed that trait anxiety pre

246 ond time-point, they also underwent a second diffusion tensor imaging scan.

247 volunteers between 8 and 26 years underwent diffusion tensor imaging scanning and completed a delay-

248 used as seeds for tractographic analysis of diffusion tensor imaging scans acquired in the same subj

249 Presurgical diffusion tensor imaging scans of 136 older (>/=70 years

250 For n = 376 individuals, diffusion tensor imaging scans were also available.

251 magnetic resonance imaging (MRI) including a diffusion tensor imaging sequence to assess microstructu

252 Diffusion tensor imaging showed converging imaging abnor

253 Diffusion-tensor imaging shows the columnar microstructu

254 l magnetic resonance imaging marker based on diffusion tensor imaging, skeletonization of white matte

255 me or graph-theory measures from whole-brain diffusion tensor imaging structural connectomes.

256 We report here a meta-analysis of diffusion tensor imaging studies in these conditions.

257 Findings from diffusion tensor imaging studies of white matter integri

258 or the interpretation of the human and mouse diffusion tensor-imaging studies upon which it is based.

259 Here we present a diffusion tensor imaging study that examined white matte

260 Regression data incorporating diffusion tensor imaging suggest that microstructural pr

261 In the present study, we used a novel diffusion tensor imaging technique to obtain high resolu

262 s underwent multimodal MR imaging, including diffusion-tensor imaging, three-dimensional (3D) T1-weig

263 Follow-up MRI included diffusion tensor imaging to assess white matter integrit

264 We used diffusion tensor imaging to characterize putative white

265 ng structural magnetic resonance imaging and diffusion tensor imaging to determine neuroanatomic diff

266 We used voxel-based morphometry (VBM) and diffusion tensor imaging to identify structural and conn

267 The present study used diffusion tensor imaging to investigate whether military

268 We used diffusion tensor imaging to study the white matter in sp

269 Here we use diffusion tensor imaging to test whether changes in whit

270 Diffusion tensor imaging tractography demonstrates a clo

271 Diffusion tensor imaging tractography revealed increased

272 ctural networks were built using whole-brain diffusion tensor imaging tractography, and analysed usin

273 apping, susceptibility weighted imaging, and diffusion tensor imaging tractography.

274 olume and thickness reduction or grey matter diffusion tensor imaging values alterations were observe

275 Diffusion tensor imaging was applied in healthy particip

276 l white matter mean diffusivity derived from diffusion tensor imaging was compared between groups in

277 Brain grey and white matter volume and diffusion tensor imaging was compared between survivor g

278 Diffusion tensor imaging was performed to measure fracti

279 Dual heart-phase diffusion tensor imaging was successfully performed in 9

280 indices and whole-brain analyses (n = 2146); diffusion tensor imaging was used to assess global and s

281 In this study, diffusion tensor imaging was used to evaluate white matt

282 Diffusion tensor imaging was used to identify group diff

283 Diffusion tensor imaging was used to model white matter

284 strength of white matter connectivity using diffusion tensor imaging, we characterize a left frontal

285 Using diffusion tensor imaging, we defined fractional anisotro

286 Using diffusion tensor imaging, we first showed extensive whit

287 By means of diffusion tensor imaging, we here show that dyslexic mal

288 Using functional and diffusion tensor imaging, we present a comprehensive neu

289 hensive voxelwise analyses of volumetric and diffusion tensor imaging, we used an unsupervised machin

290 g functional magnetic resonance imaging, and diffusion tensor imaging were assessed before and 2 mont

291 utive function task, and structural MRI with diffusion tensor imaging were conducted.

292 OCT and diffusion tensor imaging were used.

293 usion-weighted imaging, MR spectroscopy, and diffusion-tensor imaging) were performed.

294 n magnetic resonance imaging data, including diffusion tensor imaging, were acquired in 16 patients w

295 On diffusion tensor imaging, white matter injury was promin

296 This hypothesis was tested by combining diffusion tensor imaging with a multistep decision task

297 We did so combining diffusion tensor imaging with diffusion-weighted magneti

298 Finally, diffusion tensor imaging with multivariate analysis of 3

299 We introduce a new method that combines diffusion tensor imaging with probabilistic tractography

300 racts within the human brain (measured using diffusion tensor imaging) with data from a large sample