Optimization with soft Dice can lead to a volumetric bias

Vapnik, V.N.: The Nature of Statistical Learning Theory. Springer (1995)

1995

Earlier work this paper cites.

Menze, B.H., Jakab, A., Bauer, S., Kalpathy-Cramer, J., Farahani, K., Kirby, J., Burren, Y., Porz, N., Slotboom, J., Wiest, R., Lanczi, L., Gerstner, E., Weber, M.A., Arbel, T., Avants, B.B., Ayache, N., Buendia, P., Collins, D.L., Cordier, N., Corso, J.J., Criminisi, A., Das, T., Delingette, H., Demiralp, Ç., Durst, C.R., Dojat, M., Doyle, S., Festa, J., Forbes, F., Geremia, E., Glocker, B., Golland, P., Guo, X., Hamamci, A., Iftekharuddin, K.M., Jena, R., John, N.M., Konukoglu, E., Lashkari, D., Mariz, J.A., Meier, R., Pereira, S., Precup, D., Price, S.J., Raviv, T.R., Reza, S.M., Ryan, M., Sarikaya, D., Schwartz, L., Shin, H.C., Shotton, J., Silva, C.A., Sousa, N., Subbanna, N.K., Szekely, G., Taylor, T.J., Thomas, O.M., Tustison, N.J., Unal, G., Vasseur, F., Wintermark, M., Ye, D.H., Zhao, L., Zhao, B., Zikic, D., Prastawa, M., Reyes, M., Van Leemput, K.: The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS). IEEE Transactions on Medical Imaging (2015). https://doi.org/10.1109/TMI.2014.2377694

2014

Earlier work this paper cites.

Drozdzal, M., Vorontsov, E., Chartrand, G., Kadoury, S., Pal, C.: Deep Learning and Data Labeling for Medical Applications. LNCS 10008

2016

Earlier work this paper cites.

Goodfellow, I., Bengio, Y., Courville, A.: Deep Learning. MIT Press (2016)

2016

Earlier work this paper cites.

Goyal, M., Menon, B.K., Zwam, W.H.V., Dippel, D.W.J., Mitchell, P.J., Demchuk, A.M., Dávalos, A., Majoie, C.B.L.M., Berg, L.A.V.D., Levy, E.I., Berkhemer, O.A., Pereira, V.M., Rempel, J., Millán, M., Davis, S.M., Roy, D., Thornton, J., Román, L.S., Ribó, M., Beumer, D., Stouch, B., Brown, S., Campbell, B.C.V., Oostenbrugge, R.J.V., Saver, L., Hill, M.D., Jovin, T.G.: Endovascular thrombectomy after large-vessel ischaemic stroke: a meta-analysis of individual patient data from five randomised trials. The Lancet 387

2016

Earlier work this paper cites.

Milletari, F., Navab, N., Ahmadi, S.A.: V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation. International Conference on 3D Vision 4

Original

2016

Earlier work this paper cites.

Ischemic Stroke Lesion Segmentation (ISLES) challenge (2017), http://www.isles-challenge.org/ISLES2017/

2017

Cited alongside, same era.

Bakas, S., Akbari, H., Sotiras, A., Bilello, M., Rozycki, M., Kirby, J.S., Freymann, J.B., Farahani, K., Davatzikos, C.: Advancing The Cancer Genome Atlas glioma MRI collections with expert segmentation labels and radiomic features. Scientific Data 4

2017

Cited alongside, same era.

De Tobel, J., Radesh, P., Vandermeulen, D., Thevissen, P.W.: An automated technique to stage lower third molar development on panoramic radiographs for age estimation: a pilot study. Journal of Forensic Odonto-Stomatology 35

2017

Cited alongside, same era.

Kamnitsas, K., Ledig, C., Newcombe, V.F.J.: Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation. Medical Image Analysis 36

2017

Cited alongside, same era.

Ischemic Stroke Lesion Segmentation (ISLES) challenge (2018), http://www.isles-challenge.org/ISLES2017/

2018

Later among the works it cites.

Multimodal Brain Tumor Segmentation (BRATS) challenge (2018), https://www.med.upenn.edu/sbia/brats2018.html

2018

Later among the works it cites.

Isensee, F., Kickingereder, P., Wick, W., Bendszus, M., Maier-Hein, K.H.: No New-Net. LNCS 11384

Original

2018

Later among the works it cites.

Winzeck, S., Hakim, A., McKinley, R., Pinto, J.A., Alves, V., Silva, C., Pisov, M., Krivov, E., Belyaev, M., Monteiro, M., Oliveira, A., Choi, Y., Paik, M.C., Kwon, Y., Lee, H., Kim, B.J., Won, J.H., Islam, M., Ren, H., Robben, D., Suetens, P., Gong, E., Niu, Y., Xu, J., Pauly, J.M., Lucas, C., Heinrich, M.P., Rivera, L.C., Castillo, L.S., Daza, L.A., Beers, A.L., Arbelaezs, P., Maier, O., Chang, K., Brown, J.M., Kalpathy-Cramer, J., Zaharchuk, G., Wiest, R., Reyes, M.: ISLES 2016 and 2017-benchmarking ischemic stroke lesion outcome prediction based on multispectral MRI. Frontiers in Neurology 9