Learning fuzzy clustering for SPECT/CT segmentation via convolutional neural networks-Reference-Cited by-同舟云学术

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Learning fuzzy clustering for SPECT/CT segmentation via convolutional neural networks

Published:2021-05-28 Issue:7 Volume:48 Page:3860-3877
ISSN:0094-2405
Container-title:Medical Physics
language:en
Short-container-title:Med. Phys.

Author:

Chen Junyu¹²,Li Ye¹²,Luna Licia P.²,Chung Hyun W.³,Rowe Steven P.²,Du Yong²,Solnes Lilja B.²,Frey Eric C.¹²

Affiliation:

1. Department of Electrical and Computer Engineering Johns Hopkins University Baltimore MD USA

2. Russell H. Morgan Department of Radiology and Radiological Science Johns Hopkins Medical Institutes Baltimore MD USA

3. Department of Nuclear Medicine Konkuk University Medical Center Konkuk University School of Medicine Seoul South Korea

Funder

National Cancer Institute

Publisher

Wiley

Subject

General Medicine

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/mp.14903

Reference69 articles.

1. Cancer statistics, 2020

2. Comparison of Residence Time Estimation Methods for Radioimmunotherapy Dosimetry and Treatment Planning—Monte Carlo Simulation Studies

3. Evaluation of quantitative imaging methods for organ activity and residence time estimation using a population of phantoms having realistic variations in anatomy and uptake

4. Comparison of conventional, model-based quantitative planar, and quantitative SPECT image processing methods for organ activity estimation using In-111 agents

5. A Monte Carlo and physical phantom evaluation of quantitative In-111 SPECT

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