Applications of Artificial Intelligence for Pediatric Cancer Imaging-Reference-Cited by-同舟云学术

Applications of Artificial Intelligence for Pediatric Cancer Imaging

Published:2024-08 Issue:2 Volume:223 Page:
ISSN:0361-803X
Container-title:American Journal of Roentgenology
language:en
Short-container-title:American Journal of Roentgenology

Author:

Singh Shashi B.¹,Sarrami Amir H.¹,Gatidis Sergios¹,Varniab Zahra S.¹,Chaudhari Akshay²³,Daldrup-Link Heike E.¹⁴

Affiliation:

1. Department of Radiology, Division of Pediatric Radiology, Stanford University School of Medicine, 1201 Welch Rd, Stanford, CA 94305.

2. Department of Radiology, Integrative Biomedical Imaging Informatics (IBIIS), Stanford University School of Medicine, Stanford University, Stanford, CA.

3. Department of Biomedical Data Science, Stanford University School of Medicine, Stanford University, Stanford, CA.

4. Department of Pediatrics, Pediatric Hematology-Oncology, Lucile Packard Children's Hospital, Stanford University, Stanford, CA.

Publisher

American Roentgen Ray Society

Reference67 articles.

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4. Fully automatic, multiorgan segmentation in normal whole body magnetic resonance imaging (MRI), using classification forests (CFs), convolutional neural networks (CNNs), and a multi-atlas (MA) approach

5. Comparative evaluation of conventional and deep learning methods for semi-automated segmentation of pulmonary nodules on CT

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1. Editorial Comment: The Radiologist's Role in Artificial Intelligence for Pediatric Oncologic Imaging;American Journal of Roentgenology;2024-08