A combined MRI and MRSI based multiclass system for brain tumour recognition using LS-SVMs with class probabilities and feature selection-Reference-Cited by-同舟云学术

A combined MRI and MRSI based multiclass system for brain tumour recognition using LS-SVMs with class probabilities and feature selection

Published:2007-06 Issue:2 Volume:40 Page:87-102
ISSN:0933-3657
Container-title:Artificial Intelligence in Medicine
language:en
Short-container-title:Artificial Intelligence in Medicine

Author:

Luts Jan,Heerschap Arend,Suykens Johan A.K.,Van Huffel Sabine

Publisher

Elsevier BV

Subject

Artificial Intelligence,Medicine (miscellaneous)

Reference58 articles.

1. Magnetic resonance spectroscopy diagnosis of neurological diseases;Danielsen,1999

2. Accurate, noninvasive diagnosis of human brain tumors by using proton magnetic resonance spectroscopy;Preul;Nat Med,1996

3. A new approach for analyzing proton magnetic resonance spectroscopic images of brain tumors: nosologic images;Szabo de Edelenyi;Nat Med,2000

4. International network for pattern recognition of tumours using magnetic resonance., http://azizu.uab.es/INTERPRET/ (Accessed: 3 December 2006).

5. Development of a decision support system for diagnosis and grading of brain tumours using in vivo magnetic resonance single voxel spectra;Tate;Nucl Magn Reson Biomed,2006

Cited by 70 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Deep Learning Framework-Based Automated Multi-class Diagnosis for Neurological Disorders;2023 7th International Conference on Automation, Control and Robots (ICACR);2023-08-04

2. CSF-Glioma: A Causal Segmentation Framework for Accurate Grading and Subregion Identification of Gliomas;Bioengineering;2023-07-26

3. Convolutional neural networks to predict brain tumor grades and Alzheimer’s disease with MR spectroscopic imaging data;PLOS ONE;2022-08-24

4. Trends in DNN Model Based Classification and Segmentation of Brain Tumor Detection;The Open Neuroimaging Journal;2022-08-22

5. State-of-the-Art Level Set Models and Their Performances in Image Segmentation: A Decade Review;Archives of Computational Methods in Engineering;2021-09-17