Differentiation of Pilocytic Astrocytoma from Glioblastoma using a Machine-Learning framework based upon quantitative T1 perfusion MRI-Reference-Cited by-同舟云学术

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Differentiation of Pilocytic Astrocytoma from Glioblastoma using a Machine-Learning framework based upon quantitative T1 perfusion MRI

Published:2023-05 Issue: Volume:98 Page:76-82
ISSN:0730-725X
Container-title:Magnetic Resonance Imaging
language:en
Short-container-title:Magnetic Resonance Imaging

Author:

Vats Neha,Sengupta Anirban,Gupta Rakesh K.,Patir Rana,Vaishya Sandeep,Ahlawat Sunita,Saini Jitender,Agarwal Sumeet,Singh Anup

Funder

Science and Engineering Research Board

Department of Science and Technology, Ministry of Science and Technology, India

Publisher

Elsevier BV

Subject

Radiology, Nuclear Medicine and imaging,Biomedical Engineering,Biophysics

Reference42 articles.

1. MR imaging of brain pilocytic astrocytoma: beyond the stereotype of benign astrocytoma;Gaudino;Childs Nerv. Syst.,2017

2. Usefulness of perfusion- and diffusion-weighted imaging to differentiate between pilocytic astrocytomas and high-grade gliomas: a multicenter study in Japan;Kikuchi;Neuroradiology,2018

3. Comparison of perfusion, diffusion, and MR spectroscopy between low-grade enhancing pilocytic astrocytomas and high-grade astrocytomas;Aragao;Am. J. Neuroradiol.,2014

4. Pilocytic astrocytoma: radiologic- pathologic correlation;Koeller;RadioGraphics,2004

5. The 2016 World Health Organization classification of tumors of the central nervous system: a summary;Louis;Acta Neuropathol.,2016

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1. IRAM–NET model: image residual agnostics meta-learning-based network for rare de novo glioblastoma diagnosis;Neural Computing and Applications;2024-08-28

2. Pilocytic Astrocytoma of the fourth ventricle: A case report;Asian Journal of Surgery;2024-07

3. Hypothalamic Hemangioma-like Pilocytic Astrocytoma in an Adult Patient: A Systematic Review with a Focus on Differential Diagnosis and Neurological Presentation;Journal of Clinical Medicine;2024-06-17

4. Application of Machine Learning for Classification of Brain Tumors: A Systematic Review and Meta-Analysis;World Neurosurgery;2024-06

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