Using Commercial and Open-Source Tools for Artificial Intelligence: A Case Demonstration on a Complete Radiomics Pipeline-Reference-Cited by-同舟云学术

Using Commercial and Open-Source Tools for Artificial Intelligence: A Case Demonstration on a Complete Radiomics Pipeline

Published:2023 Issue: Volume: Page:13-37
ISSN:2662-1541
Container-title:Imaging Informatics for Healthcare Professionals
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Author:

Stamoulou Elisavet,Spanakis Constantinos,Nikiforaki Katerina,Karantanas Apostolos H.,Tsiknakis Nikos,Matikas Alexios,Foukakis Theodoros,Manikis Georgios C.

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-25928-9_2

Reference101 articles.

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3. Afshar P, Mohammadi A, Plataniotis KN, Oikonomou A, Benali H. From handcrafted to deep-learning-based cancer radiomics: challenges and opportunities. IEEE Sig Process Mag. 2019;36(4):132–60

4. Tian J, Dong D, Liu Z, Zang Y, Wei J, Song J, Mu W, Wang S, Zhou M. Radiomics in medical imaging—detection, extraction and segmentation. In: Artificial intelligence in decision support systems for diagnosis in medical imaging. Berlin: Springer; 2018. p. 267–333

5. Severn C, Suresh K, Görg C, Choi YS, Jain R, Ghosh D. A pipeline for the implementation and visualization of explainable machine learning for medical imaging using radiomics features. Sensors. 2022;22(14):5205