Automated Author ProfileHuisman, Henkjan
Huisman, Henkjan
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 124.4 (sum of 3 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
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
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
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