ライフサイエンスコーパス: tractography

1 (whole brain, region of interest, and fiber tractography).

2 re selected individually using deterministic tractography.

3 e reconstructed with both DKI- and DTI-based tractography.

4 ct-based spatial statistics (TBSS) and fiber tractography.

5 ays documented by magnetic resonance imaging tractography.

6 tem dissection and advance diffusion imaging tractography.

7 d cortical and subcortical regions using DTI tractography.

8 between postmortem dissections and diffusion tractography.

9 ation tracts were traced using probabilistic tractography.

10 were incompletely identified with DTI-based tractography.

11 ined by using deterministic diffusion-tensor tractography.

12 y, which is quite different from the idea of tractography.

13 brain deterministic diffusion tensor imaging tractography.

14 o structural brain connectivity is diffusion tractography.

15 etic subjects using diffusion tensor imaging tractography.

16 longitudinal fasciculus using probabilistic tractography.

17 usion magnetic resonance imaging-based fiber tractography.

18 sSTR were quantified using diffusion tensor tractography.

19 e diffusion tensor imaging and probabilistic tractography.

20 quantified using probabilistic neighborhood tractography.

21 nd prefrontal cortex using diffusion imaging tractography.

22 usivity of diffusion tensor and quantitative tractography.

23 15 minutes to enable three-dimensional (3D) tractography.

24 tudied with diffusion-weighted imaging (DWI) tractography.

25 diffusion tensor magnetic resonance imaging tractography.

26 on diffusion-weighted MRI and probabilistic tractography.

27 ons were assessed with diffusion-based fiber tractography.

28 aging at rest and diffusion-weighted imaging tractography.

29 nitive and pain processing functions through tractography.

30 st were reconstructed by using probabilistic tractography.

31 Using probabilistic tractography, a grey matter connection network was defin

32 Probabilistic tractography, a technique for identifying fiber pathways

33 The probabilistic tractography algorithm segmented the bilateral CST, alon

34 lamus and cortex using a novel probabilistic tractography algorithm with diffusion imaging data.

35 was highly dependent upon parameters of the tractography algorithm, with different optimal values fo

36 There are many different tractography algorithms and each requires the user to se

37 the properties of the connectome, to compare tractography algorithms and to test hypotheses about tra

38 Do novel tractography algorithms provide a real advantage over pr

39 diffusion tensor magnetic resonance imaging tractography, allows us, for the first time in the human

40 diffusion tensor magnetic resonance imaging tractography alone and in combination with other magneti

41 Probabilistic tractography analyses calculated brain white matter conn

42 ral magnetic resonance imaging and diffusion-tractography analyses of intrahemispheric and interhemis

43 In addition, tractography analysis of the uncinate fasciculus, a trac

44 Tractography analysis of these specific pathways showed

45 s, we performed a skeletonized probabilistic tractography analysis--'seeding' the rostral temporal vo

46 22 known deep WM tracts using Q-ball imaging tractography and an automatized segmentation technique.

47 reconstructed separately using deterministic tractography and anatomical landmarks.

48 hich need to be considered when interpreting tractography and connectivity results.

49 st exciting recent advancements in diffusion tractography and critically highlight their advantages a

50 ovel framework for estimating reliability of tractography and encourages innovation to address its cu

51 We used diffusion tensor probabilistic tractography and functional magnetic resonance imaging-b

52 Here, we combined diffusion imaging tractography and functional MRI to study whether the str

53 test this hypothesis we performed diffusion tractography and graph theoretical analysis in a pseudo-

54 d, using diffusion tensor MRI, probabilistic tractography and graph theory based network analysis.

55 eshold of 40 degrees , the authors performed tractography and measured apparent diffusion coefficient

56 Using multi-fiber probabilistic diffusion tractography and MEG source analysis of conditioning-tes

57 Using a combination of probabilistic tractography and network analysis of the white matter tr

58 accounts of language with recent advances in tractography and neuropragmatics.

59 diffusion tensor imaging with probabilistic tractography and pattern recognition techniques.

60 ic radiation can be accurately delineated by tractography and propagated onto postoperative images.

61 Diffusion tensor tractography and psychophysics were assessed in tone-dea

62 y available human connectome data (diffusion tractography and resting state functional connectivity)

63 Conclusion Whole-brain CSD-based fiber tractography and super-resolution TDI mapping reveals ab

64 ementia using diffusion tensor imaging-based tractography and to combine the findings with cortical a

65 found a correlation between log-transformed tractography and tracer connection weights of r = 0.59,

66 ength and found that the correlation between tractography and tracers remains positive, albeit substa

67 m analysis from diffusion tensor MR imaging, tractography and tract of interest method have been adop

68 to provide explicit validation of diffusion tractography and transfer tractography strategies across

69 In contrast, advanced MRI (i.e., tractography) and blood proteomics (i.e., vascular endot

70 with structural (diffusion MRI-probabilistic tractography) and functional (stochastic dynamic causal

71 t using whole-brain diffusion tensor imaging tractography, and analysed using graph analysis and netw

72 on measures were calculated using streamline tractography, and correlations with DMN functional conne

73 eighted magnetic resonance image (MRI)-based tractography, and functional interactions were assessed

74 er tracts by deterministic and probabilistic tractography, and provide supporting resting-state funct

75 in vivo using diffusion-weighted imaging and tractography, and show that the VOF can be found in ever

76 grey matter brain regions were defined using tractography, and structural connectivity matrices calcu

77 ivity was assessed by means of probabilistic tractography, and the integrity of the resulting fibers

78 ns of interest was mapped with probabilistic tractography, and the probabilistic fibre density betwee

79 In summary, a systematic ensemble tractography approach can produce connectomes that are s

80 tem (by magnetic resonance imaging diffusion tractography), assuming that marked hypoplasia or Waller

81 In vivo tractography based on diffusion magnetic resonance imagi

82 Tractography based on diffusion MRI has great potential

83 Tractography based on diffusion MRI offers the promise o

84 onnectome, has been demonstrated using fiber tractography based on diffusion tensor imaging (DTI).

85 Tractography based on diffusion-weighted MRI (DWI) is wi

86 tudy was to assess structural asymmetry with tractography based on diffusional kurtosis imaging (DKI)

87 We also used MR tractography based on high-angular resolution diffusion

88 Tractography based on non-invasive diffusion imaging is

89 s to the well known limitations of classical tractography based on the tensor model.

90 application of this atlas by calculating DTI tractography based structural connectivity between the a

91 Tractography-based analysis confirmed the results within

92 le-brain tract-based spatial statistics, and tractography-based analysis on corticospinal tracts.

93 Based on this exploratory analysis, a tractography-based approach with constrained spherical d

94 We find strong correlation between tractography-based basal ganglia parcellation and anatom

95 Cross-correlation in the tractography-based connectivity patterns of parietal vox

96 interareal cortical distances, we show that tractography-based estimates of connection strength have

97 Using DW-MRI tractography-based parcellation, we identified 10 dorsal

98 Deterministic tractography between FC-impaired regions was performed t

99 Finally, we performed probabilistic tractography between the frontal and posterior nodes of

100 imaging (DKI), which improves upon DTI-based tractography by delineating intravoxel crossing fibers.

101 port the notion that probabilistic diffusion tractography can be used to parcellate subcortical gray

102 Diffusion tensor imaging (DTI) tractography can delineate the optic radiation preoperat

103 These results suggest that DKI-based tractography can improve the identification of asymmetri

104 The results illustrate how tractography can reveal connections that are verifiable

105 or language, motor function, and memory, and tractography can reveal white matter tracts that are vit

106 h tracts, we organized an open international tractography challenge, which resulted in 96 distinct su

107 ng grey matter morphometry and probabilistic tractography combined with multivariate statistical mode

108 tenable by the parallel connectivity in dMRI tractography connecting the anterior regions of the PFC

109 Tractography connection weights were estimated using a f

110 rgery, this pilot study used the four-bundle tractography 'connectome blueprint' to plan surgical tar

111 by diffusion magnetic resonance imaging and tractography, could explain interindividual differences

112 strained spherical deconvolution (CSD)-based tractography data and super-resolution track-density ima

113 abnormal structures were not visible on the tractography data from any of the control subjects and w

114 The tractography data were overlaid on coregistered three-di

115 nique using cortical thickness and diffusion tractography data, showing that the subnetworks which em

116 novel method of "triangulation" analysis of tractography data, we also found that both the IFC and t

117 Using the full tractography data, we were able to cluster, visualize, a

118 man and with monkey visual anatomy; (ii) the tractography-defined ILF is structurally distinct from f

119 Structural MRI and diffusion tractography demonstrated broad disorganization of white

120 Whole-brain activation volume tractography demonstrated that all DBS responders at 6 m

121 Diffusion tensor imaging tractography demonstrates a close relationship between f

122 voxel-based connectivity measures along the tractography-derived corticospinal tract (CST).

123 es were based on spherical deconvolution and tractography-derived indices of tract volume and hindran

124 Diffusion- and tractography-derived measures of these tracts, including

125 This Review will outline the limitations of tractography, describe its current clinical applications

126 rimary visual cortex measured with diffusion tractography did not differ between the two populations.

127 magnetic resonance imaging diffusion tensor tractography (DTT).

128 ing deep brain stimulation, and neuroimaging tractography efforts to localize descending orofacial mo

129 Diffusion-based tractography enables the graphical reconstruction of the

130 asured with graph theoretical metrics of DTI tractography, even in the preclinical stages of AD.

131 However, DTI-based tractography fails to resolve axonal fiber bundles that

132 The in vivo tractography findings were confirmed with histology.

133 the semantic dementia group mapped onto the tractographies for the uncinate and arcuate bundles well

134 ive on both the strengths and limitations of tractography for analyzing interareal corticocortical co

135 recent studies in three broad areas: use of tractography for quantitative comparisons of specific wh

136 te matter pathways in disease; evidence from tractography for the presence of qualitatively different

137 and clinical applications, diffusion imaging tractography has reached a crossroad.

138 Tractography has shown the connections of the language c

139 nal magnetic resonance imaging and diffusion tractography have been used to identify cortical areas o

140 For diffusion tractography, high-resolution diffusion imaging datasets

141 oned cortex also influenced diffusion tensor tractography, highlighting the fact that spurious tracts

142 hrough the deep white matter, the success of tractography hinges on the capacity to follow fibers acr

143 = .01, false discovery rate corrected), and tractography identified significant WM differences bilat

144 Virtual tractography illustrates 3D topography among interconnec

145 usion tensor imaging (DTI) and probabilistic tractography in 15 patients with schizophrenia and 22 ag

146 Here, we used diffusion tensor imaging tractography in combination with functional magnetic res

147 We therefore used DWI tractography in four macaque and 10 human hemispheres to

148 Using probabilistic diffusion tractography in healthy humans and rhesus monkeys, we sh

149 diffusion-weighted imaging and probabilistic tractography in normal subjects.

150 MR imaging and tractography in the c.226del2 proband revealed a primary

151 hanges of diffusion-tensor imaging (DTI) and tractography in the distal femur and proximal tibia rela

152 We used tractography in the living human brain to address the di

153 nnectivity (using diffusion spectrum imaging tractography) in the same individuals at high resolution

154 the cerebral areas identified using in vivo tractography, in addition to the cerebral motor cortex,

155 -3)mm(2)/sec), and fiber paths, extracted by tractography, increase linearly with gestation, indicati

156 ng constrained spherical deconvolution-based tractography indicated that fractional anisotropy and ap

157 Probabilistic tractography indicated that the regional abnormality lie

158 Because diffusion tractography is a relatively new technique, however, it

159 Quantitative diffusion-tensor tractography is able to show posttraumatic FA and ADC ab

160 Diffusion tensor tractography is an advanced magnetic resonance imaging t

161 Tractography is being used to define critical pathways p

162 Diffusion-weighted imaging coupled with tractography is currently the only method for in vivo ma

163 er, assessing the anatomical accuracy of DWI tractography is difficult because of the lack of indepen

164 The goal of probabilistic tractography is to obtain a connectivity index along a w

165 support the utility of a group probabilistic tractography map as a connectome blueprint for individua

166 graphy map to the pre-surgical deterministic tractography map for each subject.

167 by matching the post-operative probabilistic tractography map to the pre-surgical deterministic tract

168 ith ALS or ALS-FTD, changes in corticospinal tractography measures correlated with changes in ALSFRS-

169 ar significance, this study identified novel tractography measures that are able to detect mTBI and m

170 We discuss the degree to which diffusion tractography meets the requirements of a technique to as

171 rimates and a framework for assessing future tractography methodological refinements objectively.

172 ed connectional imaging by applying advanced tractography methods to an ex vivo DWI dataset of the ma

173 The results of different tractography methods were compared with maps of known ax

174 quality and implementation of sophisticated tractography methods will lead to increasingly accurate

175 ng by evaluating 1,490 connectomes, thirteen tractography methods, and three data sets.

176 The VBM and probabilistic tractography metrics were correlated with clinical respo

177 Patient-specific activation volume tractography modeling may identify critical tracts that

178 urements of R1 (1/T1) with diffusion MRI and tractography (N=102, ages 7-85).

179 tracts to reconstruct using diffusion tensor tractography, namely, the middle and superior cerebellar

180 e brain's connectivity network obtained from tractography of 14 healthy-brain MRIs.

181 tories in macaque monkeys with diffusion MRI tractography of both macaques and humans.

182 MR spectroscopy and diffusion-based tractography of the cervical cord provide measures that

183 Tractography of the corticospinal tract and the medial l

184 diffusion tensor magnetic resonance imaging tractography of the heart in vivo, is presented.

185 Microstructural parameters were analyzed via tractography of the main bundles in the limbic system an

186 opy of the cervical cord and diffusion-based tractography of the major spinal cord pathways, in patie

187 In view of this, diffusion tensor tractography of the optic radiation is a potentially use

188 Tractography of the optic radiation was performed on pre

189 redictors of recovery derived from diffusion tractography of the perisylvian language networks.

190 riven resting connectivity and probabilistic tractography of the right inferior longitudinal fascicul

191 uctural connectivity analyses (probabilistic tractography) of multimodal neuroimaging data examining

192 Diffusion MR tractography offers an overall view of brain anatomy, in

193 We conclude that although tractography offers novel opportunities it also raises s

194 Deterministic fiber tractography on diffusion spectrum imaging data from neu

195 sing residual bootstrap Q-ball probabilistic tractography on high angular resolution diffusion-weight

196 We use probabilistic tractography on magnetic resonance diffusion weighted im

197 st enough to propagate accurate preoperative tractography onto intraoperative scans acquired during n

198 Diffusion tractography opens exciting new possibilities for explor

199 hether conduction distance was obtained from tractography or from histological analysis of labeled ax

200 sheet poses severe challenges for long-range tractography over roughly half of the brain.

201 stics: P < .05, family-wise error corrected; tractography: P values < .001 to .05, false discovery ra

202 With probabilistic tractography, pathways between the amygdala and the dors

203 Post hoc analyses of the structural tractography patterns mediating distinct categories of e

204 Tractography performed on the diffusion tensor imaging d

205 Because tractography performs fiber tracking according to local

206 had been reconstructed using a deterministic tractography protocol.

207 dentified in both postmortem dissections and tractography reconstructions: (1) U-fibres running in th

208 ional connectivity during the resting state, tractography related to DMN, and the association between

209 Diffusion axonal tracing, namely tractography, relies on local directional information pr

210 Can tractography reproduce reliably known anatomy or describ

211 Tractography resulted in parallel tracts in the physis a

212 Diffusion tensor imaging tractography revealed increased structural connectivity

213 Diffusion tensor imaging tractography revealed increased structural integrity in

214 In addition, tractography revealed no significant differences in diff

215 DTI color maps and tractography revealed that important white matter tracts

216 In parallel, DTI-based tractography revealed weaker AI-PPC structural connectiv

217 matter fibres and, through the technique of 'tractography', reveals the trajectories of cerebral whit

218 Here, we evaluate tractography's ability to estimate the presence and stre

219 We found the correlation of tractography's estimated connection strengths versus tra

220 we describe methods to assess quantitatively tractography's performance in detecting interareal corti

221 Postoperative tractography seeded from this area suggests that this cl

222 We then conducted whole brain probabilistic tractography seeding from the previously identified cont

223 sis of combined resting-state fMRI diffusion tractography showed pronounced modifications of function

224 Diffusion tractography showed that of the three groups of interhem

225 ation of diffusion tractography and transfer tractography strategies across species to test the exten

226 estimate interareal connection lengths from tractography streamlines, we regressed out the distance

227 Tractography studies investigating white matter (WM) abn

228 Future tractography studies of patients with occipito-temporal

229 , multicenter, international, Q-ball imaging tractography study comparing 118 BPI patients and 86 hea

230 brain injury (PBI) for an fMRI/diffusion MRI tractography study of working memory and hypothesized th

231 Diffusion MRI measures based on tractography supported the findings of decreased DMN-CEN

232 Tractography takes diffusion measurements as input and p

233 ividualized, patient-specific, deterministic tractography targeting, confirming retrospective finding

234 c indications for non-invasive diffusion MRI tractography, the only existing method to map these fibr

235 We then used fiber tractography to assess the structural integrity of the f

236 We then used diffusion-weighted imaging with tractography to assess white matter structure in the pat

237 aimed here to use diffusion tensor MRI (DTI) tractography to characterize the evolution of fiber arch

238 We used DTI and probabilistic tractography to compare FA and RD in ten prefrontal-cent

239 In this study we used diffusion tractography to define the anatomy of the frontal aslant

240 Here we performed probabilistic DWI tractography to delineate this cognitive control network

241 , and uncinate) tracts were quantified using tractography to derive measures of fractional anisotropy

242 c measures based on diffusion tensor imaging tractography to examine both diffusivity and geometric p

243 oral testing, and magnetic resonance imaging tractography to examine the connectivity of LIS1-deficie

244 ital disorders or following recovery; use of tractography to gain insights into normal brain anatomy

245 e diffusion tensor imaging and probabilistic tractography to identify the specific circuit abnormalit

246 , functional magnetic resonance imaging, and tractography to investigate the functional and structura

247 The present study employed diffusion MRI tractography to investigate the relationship between mic

248 iffusion weighted imaging with probabilistic tractography to investigate these connections in humans.

249 To illustrate the potential for tractography to provide new information in clinical neur

250 ug-using controls, and we used probabilistic tractography to quantify changes in corticosubcortical c

251 ere we used diffusion-weighted imaging (DWI) tractography to show that the IFC and the STN region are

252 g and diffusion tensor imaging probabilistic tractography to study the functional and anatomical inte

253 The authors applied tractography to subdivide the corpus callosum into regio

254 Here we use diffusion tractography to subdivide the right NAc into lateral-ros

255 we used a tract-specific analysis, based on tractography, to carry out a more detailed analysis of i

256 uctural connectivity, based on probabilistic tractography, to prefrontal cortical and subcortical lim

257 , combined analysis of whole-brain diffusion tractography together with genomewide, single-nucleotide

258 Tractography uses diffusion MRI to estimate the trajecto

259 Diffusion tractography uses non-invasive brain imaging data to tra

260 Tractography using a constrained spherical deconvolution

261 whole-brain, voxel-based analysis and fiber tractography using diffusion tensor magnetic resonance i

262 matter tracts was performed with streamline tractography; values of DTI diffusion-tensor imaging par

263 Patterns of tractography varied with age in the femur (P < .001) and

264 Diffusion tensor magnetic resonance imaging tractography was able to directly resolve the ability of

265 Here advanced tractography was combined with quantitative indices to c

266 Deterministic white matter tractography was performed after voxelwise tensor calcul

267 Diffusion-tensor tractography was performed at 3.0 T in 106 consecutive c

268 Probabilistic tractography was performed at C1-C3 to track the lateral

269 Tractography was performed by using a fractional anisotr

270 Fiber tractography was performed for each individual for a pri

271 diation and arcuate fasciculus probabilistic tractography was performed for each subject.

272 Probabilistic tractography was performed on high-quality postmortem di

273 Tractography was performed to extract the left and the r

274 major cerebral white matter tracts, and DTI tractography was performed to identify cortical regions

275 Whole brain tractography was performed using a spherical deconvoluti

276 In addition, deterministic tractography was used to assess the integrity of ascendi

277 Probabilistic tractography was used to delineate the white matter trac

278 Fiber tractography was used to derive whole brain structural g

279 Diffusion tractography was used to dissect and extract indirect vo

280 Probabilistic tractography was used to identify bilateral inferior lon

281 Kurtosis-based diffusion tensor tractography was used to measure mean kurtosis (MK) alon

282 Tractography was used to obtain indirect indices of micr

283 Probabilistic tractography was used to quantify anatomical connectivit

284 Diffusion-weighted MRI tractography was used to reconstruct three candidate fas

285 nnectivity MRI (rs-fcMRI) and diffusion MRI (tractography), we examined connectivity within the defau

286 Using FOD-based tractography, we describe novel methods for fiber bundle

287 Using global probabilistic tractography, we examined relationships between WM struc

288 Using diffusion tensor tractography, we extracted the UF, calculated its volume

289 Using diffusion tensor imaging and tractography, we found that a disruption in structural c

290 By combining diffusion-weighted MRI with tractography, we identified the anatomical trajectory of

291 Using quantitative tractography, we measured fractional anisotropy and two

292 eighted magnetic resonance imaging and fibre tractography were applied in 17 patients with V1 damage

293 matrices based on whole-brain deterministic tractography were constructed, followed by the computati

294 t-based spatial statistics and probabilistic tractography were used to measure integrity of WM micros

295 Tract-based spatial statistics and tractography were used to study white matter tract damag

296 the wider use of specific techniques such as tractography which displays white matter tracts not dire

297 ted the TC projections inferred from in vivo tractography with correlative histological axonal tracin

298 on contacts was assessed using probabilistic tractography with diffusion-tensor data.

299 es diffusion tensor estimation, white matter tractography with single and multi-fiber models, and dMR

300 This was substantiated by applying tractography, yielding a relationship between trait anxi