[WFNMB]Poster

The13th Congress of the World Federation of Nuclear Medicine and Biology(WFNMB2022) » [WFNMB]Poster Program

Oncology7

Technology

Sun. Sep 11, 2022 8:00 AM - 8:00 PM Web distribution only (配信のみ)

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[WP-12-1] A New Approach for Improving Detectability Using ResNet-based Denoising in dbPET

Koji Itagaki¹、Kanae Miyake²、Tae Oishi³、Minori Tanoue¹、Yuji Nakamoto³ (1.Division of Clinical Radiology Service, Kyoto University Hospital、2.Department of Advanced Medical Imaging Research, Graduate School of Medicine Kyoto University、3.Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine Kyoto University)

[WP-12-2] A convolutional neural network-based program to predict nodal metastasis of non-small cell lung cancer in 18F-FDG PET

Eitaro Kidera¹、Sho Koyasu²、Kenji Hirata³、Ryusuke Nakamoto²、Yuji Nakamoto² (1.Department of Radiology, Kishiwada City Hospital、2.Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University、3.Department of Diagnostic Imaging, Graduate School of Medicine, Hokkaido University)

[WP-12-3] Time-synchronized FDG PET/MRI with the Bayesian penalized likelihood reconstruction algorithm: Utility for assessment of locoregional extension in patients with uterine endometrial cancer

Miho Tachibana¹、Munenobu Nogami¹、Junko Inukai¹、Feibi Zeng¹、Kazuhiro Kubo¹、Takako Kurimoto²、Takamichi Murakami¹ (1.Department of Radiology, Kobe University Hospital、2.GE Healthcare)

[WP-12-4] PET radiomics signature based on machine learning for differential pathology classification in urothelial carcinoma.

Wenchao Gu¹、Entao Liu²、Takahito Nakajima¹ (1.Department of Diagnostic and Interventional Radiology、2.WeiLun PET Center, Department of Nuclear Medicine,Guangdong Academy of Medical Sciences)

[WP-12-5] The utility of machine learning using PET radiomic features to predict the outcome of melanoma patients treated with immunotherapy

Ryusuke Nakamoto、Guido Davidzon、Farshad Moradi、Andrei Iagaru、Benjamin Franc (Kyoto University Hospital)

[WP-12-6] Image Recognition of Tumors in Bone SPECT Images using Deep Learning

Seiryo Shukunobe¹、Mayu Konno¹、Hiroki Yamamoto¹、Koji Shirakawa²、Masataka Narita²、Shota Hosokawa¹、Yasuyuki Takahashi¹ (1.Hirosaki University、2.Hirosaki University Hospital)

[WP-12-7] Detection of Bone Metastasis on FDG-PET/CT Images using Multi-step Anomaly Voxel Detection and Local Patch analysis with Unsupervised Deep Features and Image Textures

Haruno Yamaguchi¹、Mitsutaka Nemoto²、Hayato Kaida^5,6、Yuichi Kimura^3,4、takashi Nagaoka¹、Takahiro Yamada⁶、Kohei Hanaoka⁶、Kazuhiro Kitajima⁷、Tatsuya Tsuchitani⁸、Kazunari Ishii^5,6 (1.Kindai University, Graduate school of bio-oriented science and technology、2.Kindai University, Faculty of Biology-Oriented Science and Technology、3.Kindai University, Faculty of Informatics、4.Kindai University, Cyber Informatics Research Institute、5.Kindai University Faculty of Medicine, Department of Radiology、6.Kindai University Institute of Advanced Clinical Medicine Division of Positron Emission Tomography、7.Hyogo College of Medicine, Department of Radiology、8.The Hospital of Hyogo College of Medicine, Department of Radiological Technology)

[WP-12-8] Whole Body Dynamic Na-18F PET/CT as Enabled by Digital Photon Counting

Katherine Binzel¹、Yu-lung Hsieh¹、Chadwick Wright¹、Edmund Folefac²、Dayssy Diaz Pardo²、Daniel Stover²、Michael Knopp¹ (1.OSU Wright Center of Innovation、2.The Ohio State University Wexner Medical Center)

Session information

Oncology7

Technology