We have organised ANHIR Workshop as a part of the ISBI 2019 conference on 11th of April in Venice, Italy. The presentation with some short overview and announcing winners could be found here.
The workshop program
| ANHIR Workshop programme, April 11, 2019, Venetian Ballroom B | |||
| Time | Authors | Title | |
| 14:45 | 15:00 | organizers | Introduction, challenge description and some statistics |
| 15:00 | 15:20 | Nazanin Tahmasebi, Michelle Noga, and Kumaradevan Punithakumar, | Cascaded Rigid Multi-Resolution and Moving Mesh Image Registration Frameworks for Histological Image Registration |
| 15:20 | 15:40 | Masi Valkonen, Kimmo Kartasalo, Leena Latonen, Pekka Ruusuvuori | Stain invariant elastic registration of histological sections |
| 15:40 | 16:00 | Yu Xiang | Stain deconvolution based pathological image registration |
| 16:00 | 16:30 | --- | coffee break |
| 16:30 | 16:50 | Johannes Lotz, Nick Weiss and Stefan Heldmann | Robust, fast and accurate: A 3-step method for automatic histological image registration |
| 16:50 | 17:10 | Marek Wodzinski and Andrzej Skalski | Automatic nonrigid histological image registration with an adaptive multistep algorithm |
| 17:10 | 17:30 | Ludovic Venet, Sarthak Pati, Paul Yushkevich, Spyridon Bakas | Accurate and robust alignment of variable-stained histological images using a general-purpose greedy diffeomorphic registration tool |
| 17:30 | 17:40 | organizers | prize giving ceremony, closing remarks |
| 17:40 | 18:00 | organizers | article planning (by invitation, for active participants) |
Final leaderboard/results
As the Evaluation says, the winning criterion is slightly different from the automatic leaderboard on Results. The final metric is the average rank median rTRE on the test dataset (“evaluation”). We present the final ranking of participants taking part in this challenge.
The complete statistic of participants could be found below:
| Avg-Median-rTRE | Avg-Norm-Time | Avg-Rank-Median-rTRE | Avg-Robustness | Median-Median-rTRE | ||||||
| test | training | test | training | test | training | test | training | test | training | |
| nick.weiss | 0.00287 | 0.00492 | 0.16661 | 0.12224 | 2.91633 | 3.30435 | 1 | 0.99565 | 0.0018 | 0.00186 |
| HistoReg | 0.00286 | 0.00272 | 1.59568 | 1.29352 | 3.34263 | 3.42609 | 1 | 1 | 0.0019 | 0.00195 |
| lMW | 0.00359 | 0.00404 | 6.54809 | 7.20808 | 3.43825 | 3.9087 | 0.99602 | 1 | 0.00191 | 0.00202 |
| delamoer | 0.0027 | 0.0067 | 7.79555 | 6.3977 | 4.18327 | 7.90435 | 1 | 0.98696 | 0.00226 | 0.00505 |
| zsyzzsoft | 0.00775 | 0.00011 | 0.00088 | 0.00051 | 4.41434 | 1.09565 | 0.99602 | 1 | 0.00206 | 0.00011 |
| masi | 0.00479 | 0.01303 | 9.72578 | 9.51425 | 5.31474 | 6.83043 | 0.99602 | 0.86916 | 0.00208 | 0.00311 |
| zhaoshuaibit | 0.00416 | 0.00273 | 7.17615 | 4.92249 | 6.34263 | 4.83913 | 0.99602 | 1 | 0.00265 | 0.00245 |
| bUnwarpJ | 0.09713 | 0.03409 | 7.22483 | 5.91475 | 8.16733 | 7.96087 | 0.92032 | 0.93913 | 0.0054 | 0.00587 |
| Mohammed | 0.0252 | 0.0167 | 2.72945 | 2.33206 | 9.21514 | 8.72609 | 0.95102 | 0.96847 | 0.00799 | 0.00821 |
| punithakumar | 0.05065 | 0.05949 | 1.70407 | 1.2165 | 9.70518 | 9.66087 | 0.84861 | 0.84783 | 0.00825 | 0.00999 |
| pszma2 | 0.02523 | 0.01584 | 2.72945 | 2.29903 | 10.37849 | 10.03043 | 0.95102 | 0.9607 | 0.00791 | 0.00821 |
| rNiftyReg | 0.11358 | 0.04911 | 0.09219 | 0.0954 | 10.58167 | 10.31304 | 0.82996 | 0.82969 | 0.03626 | 0.03119 |
Photos from the workshop:
