Deep convolutional neural network for differentiating between sarcoidosis and lymphoma based on [18F...
Deep convolutional neural network for differentiating between sarcoidosis and lymphoma based on [18F]FDG maximum-intensity projection images
About this item
Full title
Author / Creator
Aoki, Hikaru , Miyazaki, Yasunari , Anzai, Tatsuhiko , Yokoyama, Kota , Tsuchiya, Junichi , Shirai, Tsuyoshi , Shibata, Sho , Sakakibara, Rie , Mitsumura, Takahiro , Honda, Takayuki , Furusawa, Haruhiko , Okamoto, Tsukasa , Tateishi, Tomoya , Tamaoka, Meiyo , Yamamoto, Masahide , Takahashi, Kunihiko , Tateishi, Ukihide and Yamaguchi, Tetsuo
Publisher
Berlin/Heidelberg: Springer Berlin Heidelberg
Journal title
Language
English
Formats
Publication information
Publisher
Berlin/Heidelberg: Springer Berlin Heidelberg
Subjects
More information
Scope and Contents
Contents
Objectives
To compare the [
18
F]FDG PET/CT findings of untreated sarcoidosis and malignant lymphoma (ML) and develop convolutional neural network (CNN) models to differentiate between these diseases using maximum intensity projection (MIP) [
18
F]FDG PET images.
Methods
We retrospectively collected data on consecutive patients...
Alternative Titles
Full title
Deep convolutional neural network for differentiating between sarcoidosis and lymphoma based on [18F]FDG maximum-intensity projection images
Authors, Artists and Contributors
Author / Creator
Miyazaki, Yasunari
Anzai, Tatsuhiko
Yokoyama, Kota
Tsuchiya, Junichi
Shirai, Tsuyoshi
Shibata, Sho
Sakakibara, Rie
Mitsumura, Takahiro
Honda, Takayuki
Furusawa, Haruhiko
Okamoto, Tsukasa
Tateishi, Tomoya
Tamaoka, Meiyo
Yamamoto, Masahide
Takahashi, Kunihiko
Tateishi, Ukihide
Yamaguchi, Tetsuo
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_proquest_journals_2915440576
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2915440576
Other Identifiers
ISSN
1432-1084,0938-7994
E-ISSN
1432-1084
DOI
10.1007/s00330-023-09937-x
