• Documents
  • Authors
  • Tables
  • Log in
  • Sign up
  • MetaCart
  • DMCA
  • Donate

CiteSeerX logo

Tools

Sorted by:
Try your query at:
Semantic Scholar Scholar Academic
Google Bing DBLP
Results 1 - 10 of 67,039
Next 10 →

TABLE I MR Image Parameters. #28TR#2FTE#29

in Automatic Segmentation of Non-enhancing Brain Tumors in Magnetic Resonance Images
by Lynn M. Fletcher-heath, Lawrence O. Hall, Dmitry B. Goldgof, F. Reed Murtagh 2001
Cited by 6

TABLE 1 Imaging Parameters for MR Imaging and Spectroscopy

in Prostate Cancer: Precision of . . .
by Henkjan J. Huisman, Jurgen J. Fütterer, Tom W. J. Scheenen, Jorn A. Van Dalen, Andries G. Visser, J. A. Witjes, Jelle O. Barentsz, et al.

Table 1: Typical parameters. The parameters apply for proton density weighted (20 ms echo) 8 bit MR images. Computation time for this parameter setting is around 15 min.

in Bayesian Signal Processing and Interpretation of Brain Scans
by Ulrik Kjems

Table 3. Parameters for Brain MR Image of size (189x205) having SNR=25dB in supervised mode

in Brain MR Image Segmentation Using Tabu Search and Hidden Markov Random Field Model
by D. Patra, A. Pradhan

Table 2. Parameters for Brain MR Image of size (74x100) having SNR=25dB corre- sponding to Fig.2 in supervised mode

in Brain MR Image Segmentation Using Tabu Search and Hidden Markov Random Field Model
by D. Patra, A. Pradhan
"... In PAGE 10: ...s shown in Fig.2(b). The corresponding segmented image is shown in Fig.2(c). Because of noisy case , parameters for six classes as given in Table2 . are used to segment the noisy image.... ..."

Table 5. Parameters for Real Brain MR Image of size (189x205) having SNR=25dB for di erent classes corresponding to Fig.5 for di erent initial conditions.

in Brain MR Image Segmentation Using Tabu Search and Hidden Markov Random Field Model
by D. Patra, A. Pradhan
"... In PAGE 13: ... The noisy image was input to the algorithm and ve di erent classes were assumed initially. The initial values of and for ve di erent classes are given in Table5 . However, the algorithm converged to four di erent classes as seen from Fig.... ..."

Table 6. Parameters for Real Brain MR Image of size (74x100) having SNR=22dB for di erent initial conditions corresponding to Fig.7.

in Brain MR Image Segmentation Using Tabu Search and Hidden Markov Random Field Model
by D. Patra, A. Pradhan

Table 1 MR Imaging Protocol

in unknown title
by unknown authors

TABLE 1 Results of the Subjective Evaluation of Anatomic Details

in Index terms: Computed tomography (CT),
by Abel-jan Tasman Md, Michael Forsting Md, Olav Jansen Md, Comparative Studies, Magnetic Resonance (mr 1998

Table 5-2 The relations between reference image and subject images.

in Automatic Rigid and Deformable Medical Image Registration
by Hongliang Yu 2005
"... In PAGE 93: ... 5.1 Rigid Registration on 3D Synthetic Images Reference image: the 3D MR image of rat brain whose parameters (modality, dimensions, field of view, data type, endian type) are listed in Table5 -1. Table 5-1 The parameters of reference image.... In PAGE 93: ...1 Rigid Registration on 3D Synthetic Images Reference image: the 3D MR image of rat brain whose parameters (modality, dimensions, field of view, data type, endian type) are listed in Table 5-1. Table5 -1 The parameters of reference image. Image Modality Dimension FOV (mm) Data type Endian Reference-1 MR 256x256x18 30x30x18 16 bit Big Subject images: six subject images were synthetically generated by adjusting the transformation parameters relative to the reference image.... In PAGE 94: ...83 rotation. Table5 -2 indicates the spatial relations between the reference image and subject images. Table 5-2 The relations between reference image and subject images.... In PAGE 94: ...nd [0.5, 1.5] for scaling ratio. Registration result: the parameters of rigid body and affine transformation matrix output from three registration systems were listed in Table5 -3. ... In PAGE 95: ...84 Table5 -3 The outputs from three registrations. System Exp x T y T z T z R x S y S DHS Sub 1 20.... In PAGE 96: ... 5.2 Rigid Registration on 3D Rat Brain Images Test data: this group of rat brain images has 6 subjects and their specifications were described in Table5 -4. Each image set had (256x256) in-plane pixel resolution.... In PAGE 96: ... Dataset entitled Reference-2 was assigned as the reference image, and all others as subject images. Table5 -4 Specifications of rat brain images. Num Name Dimension FOV (mm) Data type Endian 1 Reference-2 256x256x18 30x30x18 16 bit Big 2 Subject 7 256x256x16 30x30x16 16 bit Big 3 Subject 8 256x256x16 30x30x16 16 bit Big 4 Subject 9 256x256x16 30x30x16 16 bit Big 5 Subject 10 256x256x18 30x30x18 16 bit Big 6 Subject 11 256x256x16 30x30x16 16 bit Big ... In PAGE 97: ...ranslation, [-10, 10] degrees for rotation and [0.5, 1.5] for scaling ratio. Registration results: three registration systems registration were validated with 5 pair of image sets. The computational time, initial mutual information and maximum mutual information of each experiment were listed in Table5 -5. Table 5-5 The outputs from three registration systems.... In PAGE 97: ... The computational time, initial mutual information and maximum mutual information of each experiment were listed in Table 5-5. Table5 -5 The outputs from three registration systems. System Experiment Time (sec) Initial MI Maximum MI DHS 1-2 369.... ..."
Cited by 1
Next 10 →
Results 1 - 10 of 67,039
Powered by: Apache Solr
  • About CiteSeerX
  • Submit and Index Documents
  • Privacy Policy
  • Help
  • Data
  • Source
  • Contact Us

Developed at and hosted by The College of Information Sciences and Technology

© 2007-2019 The Pennsylvania State University