NAMIC Wiki - User contributions [en]

MarlyResults

2009-09-24T10:59:36Z

Marly: /* Prostate Segmentation Challenge for 5 patient cases */

== '''Prostate Segmentation Challenge for 5 patient cases''' ==

{| border="1" cellpadding="2"
!width="75"|Patient Number
!width="150"|T2 images
!width="150"|Description
!width="150"|T2 segmented images
!width="150"|T2 manual segmentation
|-
| 1 || http://prostatemrimagedatabase.com/Database/000145/00002/002/index.html || 1.5T with Surface Coil || ‎ [[File:Marti_145.nrrd.zip]] ||
|-
|-
| 2 || http://prostatemrimagedatabase.com/Database/000190/00001/001/index.html || 3T with endorectal coil || Submit here your result ||
|-
|-
| 3 || http://prostatemrimagedatabase.com/Database/000148/00003/001/index.html || 1.5T with Surface Coil || [[File:Marti_148.nrrd.zip‎]] ||
|-
| 4 || http://prostatemrimagedatabase.com/Database/000135/00003/001/index.html || 1.5T Surface coil || [[File:Marti_135.nrrd.zip‎]] ||
|-
|-
| 5|| http://prostatemrimagedatabase.com/Database/000134/00002/001/index.html || 1.5T surface coil, after prostate treatment || [[File:Marti_134.nrrd.zip]] ||
|-
|-
|}

File:Marti 135.nrrd.zip

2009-09-24T10:58:53Z

Marly:

MarlyResults

2009-09-24T10:53:52Z

Marly: /* Prostate Segmentation Challenge for 5 patient cases */

== '''Prostate Segmentation Challenge for 5 patient cases''' ==

{| border="1" cellpadding="2"
!width="75"|Patient Number
!width="150"|T2 images
!width="150"|Description
!width="150"|T2 segmented images
!width="150"|T2 manual segmentation
|-
| 1 || http://prostatemrimagedatabase.com/Database/000145/00002/002/index.html || 1.5T with Surface Coil || ‎ [[File:Marti_145.nrrd.zip]] ||
|-
|-
| 2 || http://prostatemrimagedatabase.com/Database/000190/00001/001/index.html || 3T with endorectal coil || Submit here your result ||
|-
|-
| 3 || http://prostatemrimagedatabase.com/Database/000148/00003/001/index.html || 1.5T with Surface Coil || [[File:Marti_148.nrrd.zip‎]] ||
|-
| 4 || http://prostatemrimagedatabase.com/Database/000135/00003/001/index.html || 1.5T Surface coil || ||
|-
|-
| 5|| http://prostatemrimagedatabase.com/Database/000134/00002/001/index.html || 1.5T surface coil, after prostate treatment || [[File:Marti_134.nrrd.zip]] ||
|-
|-
|}

MarlyResults

2009-09-24T10:53:28Z

Marly: /* Prostate Segmentation Challenge for 5 patient cases */

== '''Prostate Segmentation Challenge for 5 patient cases''' ==

{| border="1" cellpadding="2"
!width="75"|Patient Number
!width="150"|T2 images
!width="150"|Description
!width="150"|T2 segmented images
!width="150"|T2 manual segmentation
|-
| 1 || http://prostatemrimagedatabase.com/Database/000145/00002/002/index.html || 1.5T with Surface Coil || ‎ [[File:Marti_145.nrrd.zip]] ||
|-
|-
| 2 || http://prostatemrimagedatabase.com/Database/000190/00001/001/index.html || 3T with endorectal coil || Submit here your result ||
|-
|-
| 3 || http://prostatemrimagedatabase.com/Database/000148/00003/001/index.html || 1.5T with Surface Coil || [[FileMarti_148.nrrd.zip‎]] ||
|-
| 4 || http://prostatemrimagedatabase.com/Database/000135/00003/001/index.html || 1.5T Surface coil || ||
|-
|-
| 5|| http://prostatemrimagedatabase.com/Database/000134/00002/001/index.html || 1.5T surface coil, after prostate treatment || [[File:Marti_134.nrrd.zip]] ||
|-
|-
|}

File:Marti 148.nrrd.zip

2009-09-24T10:52:39Z

Marly:

MarlyResults

2009-09-24T10:37:33Z

Marly: /* Prostate Segmentation Challenge for 5 patient cases */

== '''Prostate Segmentation Challenge for 5 patient cases''' ==

{| border="1" cellpadding="2"
!width="75"|Patient Number
!width="150"|T2 images
!width="150"|Description
!width="150"|T2 segmented images
!width="150"|T2 manual segmentation
|-
| 1 || http://prostatemrimagedatabase.com/Database/000145/00002/002/index.html || 1.5T with Surface Coil || ‎ [[File:Marti_145.nrrd.zip]] ||
|-
|-
| 2 || http://prostatemrimagedatabase.com/Database/000190/00001/001/index.html || 3T with endorectal coil || Submit here your result ||
|-
|-
| 3 || http://prostatemrimagedatabase.com/Database/000148/00003/001/index.html || 1.5T with Surface Coil || Submit here your result ||
|-
| 4 || http://prostatemrimagedatabase.com/Database/000135/00003/001/index.html || 1.5T Surface coil || ||
|-
|-
| 5|| http://prostatemrimagedatabase.com/Database/000134/00002/001/index.html || 1.5T surface coil, after prostate treatment || [[File:Marti_134.nrrd.zip]] ||
|-
|-
|}

MarlyResults

2009-09-24T10:36:47Z

Marly: /* Prostate Segmentation Challenge for 5 patient cases */

== '''Prostate Segmentation Challenge for 5 patient cases''' ==

{| border="1" cellpadding="2"
!width="75"|Patient Number
!width="150"|T2 images
!width="150"|Description
!width="150"|T2 segmented images
!width="150"|T2 manual segmentation
|-
| 1 || http://prostatemrimagedatabase.com/Database/000145/00002/002/index.html || 1.5T with Surface Coil || ‎ [[File:Marti_145.nrrd.zip]] ||
|-
|-
| 2 || http://prostatemrimagedatabase.com/Database/000190/00001/001/index.html || 3T with endorectal coil || Submit here your result ||
|-
|-
| 3 || http://prostatemrimagedatabase.com/Database/000148/00003/001/index.html || 1.5T with Surface Coil || Submit here your result ||
|-
| 4 || http://prostatemrimagedatabase.com/Database/000135/00003/001/index.html || 1.5T Surface coil || [[File:Marti_134.nrrd.zip]] ||
|-
|-
| 5|| http://prostatemrimagedatabase.com/Database/000134/00002/001/index.html || 1.5T surface coil, after prostate treatment || Submit here your result ||
|-
|-
|}

File:Marti 145.nrrd.zip

2009-09-24T10:32:57Z

Marly: uploaded a new version of "File:Marti 145.nrrd.zip"

File:Marti 145.nrrd.zip

2009-09-24T10:31:44Z

Marly:

File:145 segmentation.nrrd.zip

2009-09-24T10:27:53Z

Marly:

MarlyResults

2009-09-24T09:49:51Z

Marly: /* Prostate Segmentation Challenge for 5 patient cases */

== '''Prostate Segmentation Challenge for 5 patient cases''' ==

{| border="1" cellpadding="2"
!width="75"|Patient Number
!width="150"|T2 images
!width="150"|Description
!width="150"|T2 segmented images
!width="150"|T2 manual segmentation
|-
| 1 || http://prostatemrimagedatabase.com/Database/000145/00002/002/index.html || 1.5T with Surface Coil || ‎ [[File:Marti_134.nrrd.zip]] ||
|-
|-
| 2 || http://prostatemrimagedatabase.com/Database/000190/00001/001/index.html || 3T with endorectal coil || Submit here your result ||
|-
|-
| 3 || http://prostatemrimagedatabase.com/Database/000148/00003/001/index.html || 1.5T with Surface Coil || Submit here your result ||
|-
| 4 || http://prostatemrimagedatabase.com/Database/000135/00003/001/index.html || 1.5T Surface coil || Submit here your result ||
|-
|-
| 5|| http://prostatemrimagedatabase.com/Database/000134/00002/001/index.html || 1.5T surface coil, after prostate treatment || Submit here your result ||
|-
|-
|}

MarlyResults

2009-09-24T09:48:45Z

Marly: /* Prostate Segmentation Challenge for 5 patient cases */

== '''Prostate Segmentation Challenge for 5 patient cases''' ==

{| border="1" cellpadding="2"
!width="75"|Patient Number
!width="150"|T2 images
!width="150"|Description
!width="150"|T2 segmented images
!width="150"|T2 manual segmentation
|-
| 1 || http://prostatemrimagedatabase.com/Database/000145/00002/002/index.html || 1.5T with Surface Coil || Marti_134.nrrd.zip‎ ||
|-
|-
| 2 || http://prostatemrimagedatabase.com/Database/000190/00001/001/index.html || 3T with endorectal coil || Submit here your result ||
|-
|-
| 3 || http://prostatemrimagedatabase.com/Database/000148/00003/001/index.html || 1.5T with Surface Coil || Submit here your result ||
|-
| 4 || http://prostatemrimagedatabase.com/Database/000135/00003/001/index.html || 1.5T Surface coil || Submit here your result ||
|-
|-
| 5|| http://prostatemrimagedatabase.com/Database/000134/00002/001/index.html || 1.5T surface coil, after prostate treatment || Submit here your result ||
|-
|-
|}

File:Marti 134.nrrd.zip

2009-09-24T09:47:52Z

Marly:

User:Marly

2009-09-24T08:30:04Z

Marly: /* NRRD files */

__NOTOC__
==Gubern-Mérida_Results==
Atlas Based Segmentation of the prostate in MR images.

==Contestant Names and Institutions==
* Albert Gubern-Mérida. Computer Vision and Robotics Group, University of Girona, Spain.
* Robert Martí. Computer Vision and Robotics Group, University of Girona, Spain.

==NRRD files==
* Segmentation Results [[File:Gubern-Merida_NRRD.zip]].
* Case 132 [[File:132.nrrd]].

==Paper==
* Paper describing the methodology and results [[File:Gubern-Merida_Paper.pdf]].

File:132.nrrd

2009-09-24T08:28:47Z

Marly:

File:Gubern-Merida Paper.pdf

2009-07-29T13:25:58Z

Marly: uploaded a new version of "File:Gubern-Merida Paper.pdf"

User talk:Marly

2009-07-20T14:41:02Z

Marly: Blanked the page

User talk:Marly

2009-07-20T14:40:46Z

Marly: /* test */ new section

== test ==

testsss

User:Marly

2009-07-20T14:39:54Z

Marly: /* NRRD files */

__NOTOC__
==Gubern-Mérida_Results==
Atlas Based Segmentation of the prostate in MR images.

==Contestant Names and Institutions==
* Albert Gubern-Mérida. Computer Vision and Robotics Group, University of Girona, Spain.
* Robert Martí. Computer Vision and Robotics Group, University of Girona, Spain.

==NRRD files==
* Segmentation Results [[File:Gubern-Merida_NRRD.zip]].

==Paper==
* Paper describing the methodology and results [[File:Gubern-Merida_Paper.pdf]].

User:Marly

2009-07-20T14:39:37Z

Marly: /* NRRD files */

__NOTOC__
==Gubern-Mérida_Results==
Atlas Based Segmentation of the prostate in MR images.

==Contestant Names and Institutions==
* Albert Gubern-Mérida. Computer Vision and Robotics Group, University of Girona, Spain.
* Robert Martí. Computer Vision and Robotics Group, University of Girona, Spain.

==NRRD files==
* Segmentation Results [[File:Gubern-Merida_NRRD.zip | Zip file]].

==Paper==
* Paper describing the methodology and results [[File:Gubern-Merida_Paper.pdf]].

2009 prostate segmentation challenge MICCAI

2009-07-20T14:37:37Z

Marly: /* Contestants Results Submission */

=Goal=
To discuss the state-of-art for prostate segmentation of MR images in the context of MRI-guided prostate therapy, through comparison of the segmentation methods using sample data.

=Workshop=
Thursday - 24th September
at MICCAI 2009 (London, UK)
http://www.miccai2009.org/

=Sponsor=
*National Center for Image Guided Therapy (NCIGT, PI: Jolesz, Tempany)
*National Alliance for Medical Image Computing (NA-MIC, PI: Kikinis)

=Organizer=
*Nobuhiko Hata (co-lead organizer, BWH, Boston, MA, Email hata at-mark bwh.harvard.edu)
*Gabor Fichtinger (co-lead organizer, Queens Univ, Kingston, ON)
*Sota Oguro (Data managing, BWH, Boston, MA)
*Haytham Elhawary (Slicer module for validation, BWH, Boston, MA)
*Theo van Walsum (Organizer of the umbrella MICCAI workshop "3D segmentation in Clinic").

=Rules=
#Download 3D Slicer for viewing and manipulating the dataset we provide below. All files to be downloaded are available in the Download section below.
#(Optional) Download the prostate image processing tutorial and its associated images.
#Download the MR images of the prostate and the manually segmented gland (as training data). The segmentations have been performed by expert radiologists.
#Perform the segmentation of the prostate gland with your algorithm. The segmentation result should be [http://teem.sourceforge.net/nrrd/index.html NRRD format ] and loadable to Slicer. The segmentation result should be aligned to the original MR image when loaded to Slicer. In addition the segmentation result should be a label map image maintaining the same pixel intensity value assigned to each segmentation image in the training dataset. A [http://www.slicer.org/slicerWiki/index.php/Modules:RegistrationMetrics-Documentation-3.5 module] has been created in Slicer3 which can calculate the 95% Hausdorff distance and Dice Similarity Coefficient between your segmentation and the manual segmentations of the prostate provided.
#Create an account at this NA-MIC wiki: [http://wiki.na-mic.org/Wiki/index.php/Special:RequestAccount Account Request]. Once your account has been accepted, upload the NRRD file with your segmentation results in the Contestants section of this page, along with the paper describing the method developed and applied.
#The organizer will score the segmentation result by comparing it with the manual segmentation of the expert using the announced comparison scheme: 95% Hausdorff distance and Dice Similarity Coeeficient.
#Repeat step above at the workshop with the competition dataset available on the day.
Those who submit paper and make their code available at Insight Journal (http://www.insight-journal.org/) will get extra points.
Those who submit paper and make their code available as a Slicer module will get extra recognition at the contest.

=Dates=
#Training data available: June 2009
#Submission of results of segmented training data: starts June 25th 2009 and continues until the paper submission deadline.
#Submission of papers (with results) (no page limit, Springer/MICCAI format/PDF file): July 20, 2009
#Workshop: September 2009

=Downloads=
#[http://www.slicer.org/pages/Special:SlicerDownloads 3D Slicer]
#[http://wiki.na-mic.org/Wiki/index.php/IGT:ToolKit/Prostate-Planning Prostate MRI tutorial for 3D Slicer]
#[http://wiki.na-mic.org/Wiki/index.php/Training_Data_Prostate_Segmentation_Challenge_MICCAI09 Training MRI data with expert's segmentation]
#[http://prostatemrimagedatabase.com/Database/000132/00003/001/index.html Subject data (for paper submission)]
#Subject data (for contest on-site)

=Contestants Results Submission=
Use the following template to upload results:

#Albert Gubern-Merida and Robert Marti, University of Girona, [[User:Marly | Link to Page]]
#Contestant Name(s), Contestant Institution(s), [[MICCAI2009Prostate-BWH | Link to template]]

For example:
#Nobuhiko Hata, PhD, Brigham and Women's Hospital, [[MICCAI2009Prostate-BWH]]

=Evaluation Scheme=
Two evaluation methods are used to determine the accuracy of the segmentation: the 95% Hausdorff distance and the Dice Similarity Coefficient.

*95% Hausdorff distance (HD)
The HD is calculated between the contours of the segmented prostates which result from the manual segmentation and the proposed contestant algorithm. The HD is the maximum distance of a set to the nearest point in another set. A more formal description of the HD can be found in the following publication:

**Archip N, Clatz O, Whalen S, et al. Non-rigid alignment of pre-operative MRI, fMRI, and DT-MRI with intra-operative MRI for enhanced visualization and navigation in image-guided neurosurgery. Neuroimage 2007; 35:609-624.

*Dice Similarity Coefficient (DSC)
The DSC, which has been extensively used in the evaluation of segmentation, gives a measure of the volumetric overlap between the two segmented prostates. The DSC indicates twice the number of voxels which are shared by or are common to both segmentations divided by the total number of voxels in both datasets. The DSC can range from zero to one, where zero is no alignment between segmented glands and one is perfect alignment. An example of the DSC used in prostate segmetation can be found at:

**A. Bharatha, M. Hirose, N. Hata, S. K. Warfield, M. Ferrant, K. H. Zou, E. Suarez-Santana, J. Ruiz-Alzola, A. D'Amico, R. A. Cormack, R. Kikinis, F. A. Jolesz, and C. M. Tempany, "Evaluation of three-dimensional finite element-based deformable registration of pre- and intraoperative prostate imaging," Med Phys, vol. 28(12), pp. 2551-60, 2001.

2009 prostate segmentation challenge MICCAI

2009-07-20T14:37:22Z

Marly: /* Contestants Results Submission */

=Goal=
To discuss the state-of-art for prostate segmentation of MR images in the context of MRI-guided prostate therapy, through comparison of the segmentation methods using sample data.

=Workshop=
Thursday - 24th September
at MICCAI 2009 (London, UK)
http://www.miccai2009.org/

=Sponsor=
*National Center for Image Guided Therapy (NCIGT, PI: Jolesz, Tempany)
*National Alliance for Medical Image Computing (NA-MIC, PI: Kikinis)

=Organizer=
*Nobuhiko Hata (co-lead organizer, BWH, Boston, MA, Email hata at-mark bwh.harvard.edu)
*Gabor Fichtinger (co-lead organizer, Queens Univ, Kingston, ON)
*Sota Oguro (Data managing, BWH, Boston, MA)
*Haytham Elhawary (Slicer module for validation, BWH, Boston, MA)
*Theo van Walsum (Organizer of the umbrella MICCAI workshop "3D segmentation in Clinic").

=Rules=
#Download 3D Slicer for viewing and manipulating the dataset we provide below. All files to be downloaded are available in the Download section below.
#(Optional) Download the prostate image processing tutorial and its associated images.
#Download the MR images of the prostate and the manually segmented gland (as training data). The segmentations have been performed by expert radiologists.
#Perform the segmentation of the prostate gland with your algorithm. The segmentation result should be [http://teem.sourceforge.net/nrrd/index.html NRRD format ] and loadable to Slicer. The segmentation result should be aligned to the original MR image when loaded to Slicer. In addition the segmentation result should be a label map image maintaining the same pixel intensity value assigned to each segmentation image in the training dataset. A [http://www.slicer.org/slicerWiki/index.php/Modules:RegistrationMetrics-Documentation-3.5 module] has been created in Slicer3 which can calculate the 95% Hausdorff distance and Dice Similarity Coefficient between your segmentation and the manual segmentations of the prostate provided.
#Create an account at this NA-MIC wiki: [http://wiki.na-mic.org/Wiki/index.php/Special:RequestAccount Account Request]. Once your account has been accepted, upload the NRRD file with your segmentation results in the Contestants section of this page, along with the paper describing the method developed and applied.
#The organizer will score the segmentation result by comparing it with the manual segmentation of the expert using the announced comparison scheme: 95% Hausdorff distance and Dice Similarity Coeeficient.
#Repeat step above at the workshop with the competition dataset available on the day.
Those who submit paper and make their code available at Insight Journal (http://www.insight-journal.org/) will get extra points.
Those who submit paper and make their code available as a Slicer module will get extra recognition at the contest.

=Dates=
#Training data available: June 2009
#Submission of results of segmented training data: starts June 25th 2009 and continues until the paper submission deadline.
#Submission of papers (with results) (no page limit, Springer/MICCAI format/PDF file): July 20, 2009
#Workshop: September 2009

=Downloads=
#[http://www.slicer.org/pages/Special:SlicerDownloads 3D Slicer]
#[http://wiki.na-mic.org/Wiki/index.php/IGT:ToolKit/Prostate-Planning Prostate MRI tutorial for 3D Slicer]
#[http://wiki.na-mic.org/Wiki/index.php/Training_Data_Prostate_Segmentation_Challenge_MICCAI09 Training MRI data with expert's segmentation]
#[http://prostatemrimagedatabase.com/Database/000132/00003/001/index.html Subject data (for paper submission)]
#Subject data (for contest on-site)

=Contestants Results Submission=
Use the following template to upload results:
#Contestant Name(s), Contestant Institution(s), [[MICCAI2009Prostate-BWH | Link to template]]
#Albert Gubern-Merida and Robert Marti, University of Girona, [[User:Marly | Link to Page]]

For example:
#Nobuhiko Hata, PhD, Brigham and Women's Hospital, [[MICCAI2009Prostate-BWH]]

=Evaluation Scheme=
Two evaluation methods are used to determine the accuracy of the segmentation: the 95% Hausdorff distance and the Dice Similarity Coefficient.

*95% Hausdorff distance (HD)
The HD is calculated between the contours of the segmented prostates which result from the manual segmentation and the proposed contestant algorithm. The HD is the maximum distance of a set to the nearest point in another set. A more formal description of the HD can be found in the following publication:

**Archip N, Clatz O, Whalen S, et al. Non-rigid alignment of pre-operative MRI, fMRI, and DT-MRI with intra-operative MRI for enhanced visualization and navigation in image-guided neurosurgery. Neuroimage 2007; 35:609-624.

*Dice Similarity Coefficient (DSC)
The DSC, which has been extensively used in the evaluation of segmentation, gives a measure of the volumetric overlap between the two segmented prostates. The DSC indicates twice the number of voxels which are shared by or are common to both segmentations divided by the total number of voxels in both datasets. The DSC can range from zero to one, where zero is no alignment between segmented glands and one is perfect alignment. An example of the DSC used in prostate segmetation can be found at:

**A. Bharatha, M. Hirose, N. Hata, S. K. Warfield, M. Ferrant, K. H. Zou, E. Suarez-Santana, J. Ruiz-Alzola, A. D'Amico, R. A. Cormack, R. Kikinis, F. A. Jolesz, and C. M. Tempany, "Evaluation of three-dimensional finite element-based deformable registration of pre- and intraoperative prostate imaging," Med Phys, vol. 28(12), pp. 2551-60, 2001.

2009 prostate segmentation challenge MICCAI

2009-07-20T14:36:47Z

Marly: /* Contestants Results Submission */

=Goal=
To discuss the state-of-art for prostate segmentation of MR images in the context of MRI-guided prostate therapy, through comparison of the segmentation methods using sample data.

=Workshop=
Thursday - 24th September
at MICCAI 2009 (London, UK)
http://www.miccai2009.org/

=Sponsor=
*National Center for Image Guided Therapy (NCIGT, PI: Jolesz, Tempany)
*National Alliance for Medical Image Computing (NA-MIC, PI: Kikinis)

=Organizer=
*Nobuhiko Hata (co-lead organizer, BWH, Boston, MA, Email hata at-mark bwh.harvard.edu)
*Gabor Fichtinger (co-lead organizer, Queens Univ, Kingston, ON)
*Sota Oguro (Data managing, BWH, Boston, MA)
*Haytham Elhawary (Slicer module for validation, BWH, Boston, MA)
*Theo van Walsum (Organizer of the umbrella MICCAI workshop "3D segmentation in Clinic").

=Rules=
#Download 3D Slicer for viewing and manipulating the dataset we provide below. All files to be downloaded are available in the Download section below.
#(Optional) Download the prostate image processing tutorial and its associated images.
#Download the MR images of the prostate and the manually segmented gland (as training data). The segmentations have been performed by expert radiologists.
#Perform the segmentation of the prostate gland with your algorithm. The segmentation result should be [http://teem.sourceforge.net/nrrd/index.html NRRD format ] and loadable to Slicer. The segmentation result should be aligned to the original MR image when loaded to Slicer. In addition the segmentation result should be a label map image maintaining the same pixel intensity value assigned to each segmentation image in the training dataset. A [http://www.slicer.org/slicerWiki/index.php/Modules:RegistrationMetrics-Documentation-3.5 module] has been created in Slicer3 which can calculate the 95% Hausdorff distance and Dice Similarity Coefficient between your segmentation and the manual segmentations of the prostate provided.
#Create an account at this NA-MIC wiki: [http://wiki.na-mic.org/Wiki/index.php/Special:RequestAccount Account Request]. Once your account has been accepted, upload the NRRD file with your segmentation results in the Contestants section of this page, along with the paper describing the method developed and applied.
#The organizer will score the segmentation result by comparing it with the manual segmentation of the expert using the announced comparison scheme: 95% Hausdorff distance and Dice Similarity Coeeficient.
#Repeat step above at the workshop with the competition dataset available on the day.
Those who submit paper and make their code available at Insight Journal (http://www.insight-journal.org/) will get extra points.
Those who submit paper and make their code available as a Slicer module will get extra recognition at the contest.

=Dates=
#Training data available: June 2009
#Submission of results of segmented training data: starts June 25th 2009 and continues until the paper submission deadline.
#Submission of papers (with results) (no page limit, Springer/MICCAI format/PDF file): July 20, 2009
#Workshop: September 2009

=Downloads=
#[http://www.slicer.org/pages/Special:SlicerDownloads 3D Slicer]
#[http://wiki.na-mic.org/Wiki/index.php/IGT:ToolKit/Prostate-Planning Prostate MRI tutorial for 3D Slicer]
#[http://wiki.na-mic.org/Wiki/index.php/Training_Data_Prostate_Segmentation_Challenge_MICCAI09 Training MRI data with expert's segmentation]
#[http://prostatemrimagedatabase.com/Database/000132/00003/001/index.html Subject data (for paper submission)]
#Subject data (for contest on-site)

=Contestants Results Submission=
Use the following template to upload results:
#Contestant Name(s), Contestant Institution(s), [[MICCAI2009Prostate-BWH | Link to template]]
Albert Gubern-Merida and Robert Marti, University of Girona, [[User:Marly | Link to Page]]

For example:
#Nobuhiko Hata, PhD, Brigham and Women's Hospital, [[MICCAI2009Prostate-BWH]]

=Evaluation Scheme=
Two evaluation methods are used to determine the accuracy of the segmentation: the 95% Hausdorff distance and the Dice Similarity Coefficient.

*95% Hausdorff distance (HD)
The HD is calculated between the contours of the segmented prostates which result from the manual segmentation and the proposed contestant algorithm. The HD is the maximum distance of a set to the nearest point in another set. A more formal description of the HD can be found in the following publication:

**Archip N, Clatz O, Whalen S, et al. Non-rigid alignment of pre-operative MRI, fMRI, and DT-MRI with intra-operative MRI for enhanced visualization and navigation in image-guided neurosurgery. Neuroimage 2007; 35:609-624.

*Dice Similarity Coefficient (DSC)
The DSC, which has been extensively used in the evaluation of segmentation, gives a measure of the volumetric overlap between the two segmented prostates. The DSC indicates twice the number of voxels which are shared by or are common to both segmentations divided by the total number of voxels in both datasets. The DSC can range from zero to one, where zero is no alignment between segmented glands and one is perfect alignment. An example of the DSC used in prostate segmetation can be found at:

**A. Bharatha, M. Hirose, N. Hata, S. K. Warfield, M. Ferrant, K. H. Zou, E. Suarez-Santana, J. Ruiz-Alzola, A. D'Amico, R. A. Cormack, R. Kikinis, F. A. Jolesz, and C. M. Tempany, "Evaluation of three-dimensional finite element-based deformable registration of pre- and intraoperative prostate imaging," Med Phys, vol. 28(12), pp. 2551-60, 2001.

User:Marly

2009-07-20T14:34:26Z

Marly: /* Paper */

__NOTOC__
==Gubern-Mérida_Results==
Atlas Based Segmentation of the prostate in MR images.

==Contestant Names and Institutions==
* Albert Gubern-Mérida. Computer Vision and Robotics Group, University of Girona, Spain.
* Robert Martí. Computer Vision and Robotics Group, University of Girona, Spain.

==NRRD files==
* Segmentation Results (zip file).[[File:Gubern-Merida_NRRD.zip]]

==Paper==
* Paper describing the methodology and results [[File:Gubern-Merida_Paper.pdf]].

User:Marly

2009-07-20T14:33:34Z

Marly: /* Paper */

__NOTOC__
==Gubern-Mérida_Results==
Atlas Based Segmentation of the prostate in MR images.

==Contestant Names and Institutions==
* Albert Gubern-Mérida. Computer Vision and Robotics Group, University of Girona, Spain.
* Robert Martí. Computer Vision and Robotics Group, University of Girona, Spain.

==NRRD files==
* Segmentation Results (zip file).[[File:Gubern-Merida_NRRD.zip]]

==Paper==
* Paper describing the methodology and results[[File:Gubern-Merida_Paper.pdf|pdf]].

File:Gubern-Merida Paper.pdf

2009-07-20T14:31:46Z

Marly:

User:Marly

2009-07-20T14:29:53Z

Marly: /* NRRD files */

__NOTOC__
==Gubern-Mérida_Results==
Atlas Based Segmentation of the prostate in MR images.

==Contestant Names and Institutions==
* Albert Gubern-Mérida. Computer Vision and Robotics Group, University of Girona, Spain.
* Robert Martí. Computer Vision and Robotics Group, University of Girona, Spain.

==NRRD files==
* Segmentation Results (zip file).[[File:Gubern-Merida_NRRD.zip]]

==Paper==
* Paper describing the methodology and results.

File:Gubern-Merida NRRD.zip

2009-07-20T14:25:59Z

Marly:

User talk:Marly

2009-07-20T14:19:02Z

Marly: Blanked the page

User:Marly

2009-07-20T14:18:50Z

Marly: Created page with '__NOTOC__ ==Gubern-Mérida_Results== Atlas Based Segmentation of the prostate in MR images. ==Contestant Names and Institutions== * Albert Gubern-Mérida. Computer Vision and Ro...'

__NOTOC__
==Gubern-Mérida_Results==
Atlas Based Segmentation of the prostate in MR images.

==Contestant Names and Institutions==
* Albert Gubern-Mérida. Computer Vision and Robotics Group, University of Girona, Spain.
* Robert Martí. Computer Vision and Robotics Group, University of Girona, Spain.

==NRRD files==
* Segmentation Results (zip file).

==Paper==
* Paper describing the methodology and results.

User talk:Marly

2009-07-20T14:17:01Z

Marly:

__NOTOC__
==Gubern-Mérida_Results==
Atlas Based Segmentation of the prostate in MR images.

==Contestant Names and Institutions==
* Albert Gubern-Mérida. Computer Vision and Robotics Group, University of Girona, Spain.
* Robert Martí. Computer Vision and Robotics Group, University of Girona, Spain.

==NRRD files==
* Segmentation Results (zip file).

==Paper==
* Paper describing the methodology and results.