Performance of a Deep Neural Network Algorithm Based on a Small Medical Image Dataset: Incremental Impact of 3D-to-2D Reformation Combined with Novel Data Augmentation, Photometric Conversion, or Transfer Learning

Collecting and curating large medical-image datasets for deep neural network (DNN) algorithm development is typically difficult and resource-intensive. While transfer learning (TL) decreases reliance on large data collections, current TL implementations are tailored to two-dimensional (2D) datasets,...

Πλήρης περιγραφή

Αποθηκεύτηκε σε:
Λεπτομέρειες βιβλιογραφικής εγγραφής
Τόπος έκδοσης:J Digit Imaging
Κύριοι συγγραφείς: Gupta, Vikash, Demirer, Mutlu, Bigelow, Matthew, Little, Kevin J., Candemir, Sema, Prevedello, Luciano M., White, Richard D., O’Donnell, Thomas P., Wels, Michael, Erdal, Barbaros S.
Μορφή: Artigo
Γλώσσα:Inglês
Έκδοση: Springer International Publishing 2019
Θέματα:
Original Paper
Διαθέσιμο Online:https://ncbi.nlm.nih.gov/pmc/articles/PMC7165215/
https://ncbi.nlm.nih.gov/pubmed/31625028
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s10278-019-00267-3
Ετικέτες: Προσθήκη ετικέτας
Δεν υπάρχουν, Καταχωρήστε ετικέτα πρώτοι!

Παρόμοια τεκμήρια