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발행년	- (예 : 2010-2015)

전체선택

Domain generalization across tumor types, laboratories, and species — Insights from the 2022 edition of the Mitosis Domain Generalization Challenge

Academic Journal

Aubreville, M.; Ammeling, J.; Ganz, J.; Stathonikos, N.; Donovan, T.A.; Klopfleisch, R.; Wilm, F.; Breininger, K.; Veta, M.; Jabari, S.; Eckstein, M.; Annuscheit, J.; Krumnow, C.; Bozaba, E.; Çayır, S.; Gu, H.; Chen, X.‘.; Jahanifar, M.; Shephard, A.; Kondo, S.; Kasai, S.; Kotte, S.; Saipradeep, V.G.; Lafarge, M.W.; Koelzer, V.H.; Wang, Z.; Zhang, Y.; Yang, S.; Wang, X.; Bertram, C.A.

In: Medical Image Analysis. (Medical Image Analysis, May 2024, 94)

Full Text (ScienceDirect) Full Text (ScienceDirect 종량제) Web of Science JCR 저널정보 Scopus Find it@PNU

Curious Containers: A framework for computational reproducibility in life sciences with support for Deep Learning applications

Academic Journal

Jansen, C.; Annuscheit, J.; Schilling, B.; Strohmenger, K.; Witt, M.; Herta, C.; Hufnagl, P.; Krefting, D.; Bartusch, F.

In: Future Generation Computer Systems. (Future Generation Computer Systems, November 2020, 112:209-227)

Full Text (ScienceDirect) Web of Science JCR 저널정보 Scopus Find it@PNU

Radial Prediction Domain Adaption Classifier for the MIDOG 2022 Challenge

Book

Annuscheit, J.; Krumnow, C.

In: Mitosis Domain Generalization and Diabetic Retinopathy Analysis - MICCAI Challenges MIDOG 2022 and DRAC 2022, Held in Conjunction with MICCAI 2022, Proceedings. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2023, 13597 LNCS:206-210)

Scopus Find it@PNU

Diagnostic assessment of deep learning algorithms for detection of lymph node metastases in women with breast cancer

Academic Journal

Bejnordi, B.E.; Van Ginneken, B.; Karssemeijer, N.; Manson, Q.F.; Stathonikos, N.; Veta, M.; Van Diest, P.J.; Hermsen, M.; Geessink, O.; Litjens, G.; Van Der Laak, J.A.W.M.; Tellez, D.; Racoceanu, D.; Balkenhol, M.; Bult, P.; Venâncio, R.; Van Dijk, M.C.R.F.; Beca, F.; Beck, A.H.; Wang, D.; Irshad, H.; Khosla, A.; Gargeya, R.; Zhong, A.; Dou, Q.; Li, Q.; Chen, H.; Lin, H.-J.; Heng, P.-A.; Haß, C.; Bruni, E.; Wong, Q.; Halici, U.; Öner, M.U.; Cetin-Atalay, R.; Berseth, M.; Khvatkov, V.; Vylegzhanin, A.; Kraus, O.; Shaban, M.; Rajpoot, N.; Sirinukunwattana, K.; Qaiser, T.; Tsang, Y.-W.; Awan, R.; Annuscheit, J.; Hufnagl, P.; Kartasalo, K.; Ruusuvuori, P.; Liimatainen, K.; Valkonen, M.; Latonen, L.; Albarqouni, S.; Mungal, B.; George, A.; Demirci, S.; Navab, N.; Watanabe, S.; Seno, S.; Takenaka, Y.; Matsuda, H.; Phoulady, H.A.; Kovalev, V.; Kalinovsky, A.; Liauchuk, V.; Bueno, G.; Fernandez-Carrobles, M.M.; Serrano, I.; Deniz, O.

In: JAMA - Journal of the American Medical Association. (JAMA - Journal of the American Medical Association, 12 December 2017, 318(22):2199-2210)

Full Text (AMA) Web of Science JCR 저널정보 Scopus Find it@PNU

Higher Education Teaching Material on Machine Learning in the Domain of Digital Pathology

Book

Strohmenger, K.; Herta, C.; Fischer, O.; Annuscheit, J.; Hufnagl, P.

(Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2020, 12090 LNCS:155-174)

Scopus Find it@PNU

Reproducibility and performance of deep learning applications for cancer detection in pathological images

Conference

Jansen, C.; Schilling, B.; Strohmenger, K.; Witt, M.; Annuscheit, J.; Krefting, D.

In: Proceedings - 19th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGrid 2019, Proceedings - 19th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGrid 2019. (Proceedings - 19th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGrid 2019, May 2019, :621-630)

Full Text (IEEE) Scopus Find it@PNU

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