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Automated Author Profile

Huisman, Henkjan

Current S-Index

124.4

Sum of Dataset Indices for all datasets

Average Dataset Index per Dataset

41.5

Average Dataset Index per dataset

Total Datasets

3

Total datasets for this author

Average FAIR Score

83.3%

Average FAIR Score per dataset

Total Citations

195

Total citations to the author's datasets

Total Mentions

35

Total mentions of the author's datasets

S-Index Interpretation

S-Index Over Time

Cumulative Citations Over Time

Cumulative Mentions Over Time

Datasets

SPIE-AAPM PROSTATEx Challenge Data (Version: 2)

SPIE, along with the support of the American Association of Physicists in Medicine (AAPM) and the National Cancer Institute (NCI), will conduct a “Grand Challenge” on quantitative image analysis methods for the diagnostic classification of clinically significant prostate lesions. As part of the 2017 SPIE Medical Imaging Symposium, the PROSTATEx Challenge will provide a unique opportunity for participants to compare their algorithms with those of others from academia, industry, and government in a structured, direct way using the same data sets. For more details, go to http://www.spie.org/PROSTATEx/

Authors

  • Litjens, Geert ;
  • Debats, Oscar ;
  • Barentsz, Jelle ;
  • Karssemeijer, Nico ;
  • Huisman, Henkjan
118 Citations35 Mentions88% FAIR79.1 Dataset Index
10.7937/k9tcia.2017.murs5clJanuary 2017

Data From Prostate-3T (Version: 1)

Prostate transversal T2-weighted magnetic resonance images (MRIs) acquired on a 3.0T Siemens TrioTim using only a pelvic phased-array coil were acquired for prostate cancer detection. The data was provided to TCIA as part of an ISBI challenge competition in 2013.

Authors

  • Litjens, Geert ;
  • Futterer, Jurgen ;
  • Huisman, Henkjan
19 Citations0 Mentions81% FAIR12.3 Dataset Index
10.7937/k9/tcia.2015.qjtv5il5January 2015

NCI-ISBI 2013 Challenge: Automated Segmentation of Prostate Structures (ISBI-MR-Prostate-2013) (Version: 1)

This data set was created for use in the NCI-ISBI 2013 Challenge - Automated Segmentation of Prostate Structures. The challenge data set was divided into 3 parts including training, leaderboard and test data sets. This allowed participants to prepare their algorithms and test their results prior to submitting to a final test phase for selecting the winner.Image data were selected from PROSTATE-DIAGNOSIS and Prostate-3T collections on TCIA. Cases consist of axial scans with half obtained at 1.5 T (Philips Achieva) with an endo-rectal receiver coil (fromBostonMedicalCenter) and the other half at 3T (Siemens TIM) with a surface coil (from Radboud University Nijmegen Medical Centre [RUNMC],Netherlands). They were acquired as T2-weighted MR axial pulse sequences with either 4 mm thick slices at 3T or 3 mm thick at 1.5T. Each case has had central gland (CG) and peripheral zone (PZ) outlines marked by NB and MR, or HH, GL, or JF.

Authors

  • Bloch, B. Nicholas ;
  • Madabhushi, Anant ;
  • Huisman, Henkjan ;
  • Freymann, John ;
  • Kirby, Justin ;
  • Grauer, Michael ;
  • Enquobahrie, Andinet ;
  • Jaffe, Carl ;
  • Clarke, Larry ;
  • Farahani, Keyvan
58 Citations0 Mentions81% FAIR34.0 Dataset Index
10.7937/k9/tcia.2015.zf0vlopvJanuary 2015