scholarly journals Neuromorphometry of primary brain tumors by magnetic resonance imaging

2015 ◽  
Vol 2 (2) ◽  
pp. 024503 ◽  
Author(s):  
Nidiyare Hevia-Montiel ◽  
Pedro I. Rodriguez-Perez ◽  
Paul J. Lamothe-Molina ◽  
Alfonso Arellano-Reynoso ◽  
Ernesto Bribiesca ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Brain Tumors ◽  
Resonance Imaging ◽  
Primary Brain Tumors

scholarly journals Simultaneous 11C-Methionine Positron Emission Tomography/Magnetic Resonance Imaging of Suspected Primary Brain Tumors

PLoS ONE ◽  
2016 ◽  
Vol 11 (12) ◽  
pp. e0167596 ◽  
Author(s):  
Cornelius Deuschl ◽  
Sophia Goericke ◽  
Johannes Grueneisen ◽  
Lino Morris Sawicki ◽  
Juliane Goebel ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Positron Emission Tomography ◽  
Magnetic Resonance ◽  
Brain Tumors ◽  
Emission Tomography ◽  
Resonance Imaging ◽  
Primary Brain Tumors ◽  
Positron Emission

MAGNETIC RESONANCE IMAGING FEATURES OF PRIMARY BRAIN TUMORS IN DOGS

1996 ◽  
Vol 37 (1) ◽  
pp. 20-27 ◽  
Author(s):  
William B. Thomas ◽  
Simon J. Wheeler ◽  
Robert Kramer ◽  
Joe N. Kornegay
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Brain Tumors ◽  
Imaging Features ◽  
Resonance Imaging ◽  
Primary Brain Tumors

Multimodal Magnetic Resonance Imaging Evaluation of Primary Brain Tumors

2014 ◽  
Vol 41 (4) ◽  
pp. 478-495 ◽  
Author(s):  
Daniel Treister ◽  
Sara Kingston ◽  
Kristina E. Hoque ◽  
Meng Law ◽  
Mark S. Shiroishi
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Brain Tumors ◽  
Resonance Imaging ◽  
Imaging Evaluation ◽  
Magnetic Resonance Imaging Evaluation ◽  
Primary Brain Tumors

scholarly journals Differential Deep Convolutional Neural Network Model for Brain Tumor Classification

2021 ◽  
Vol 11 (3) ◽  
pp. 352
Author(s):  
Isselmou Abd El Kader ◽  
Guizhi Xu ◽  
Zhang Shuai ◽  
Sani Saminu ◽  
Imran Javaid ◽  
...  
Keyword(s):  
Neural Network ◽  
Magnetic Resonance Imaging ◽  
Brain Tumor ◽  
Magnetic Resonance ◽  
Brain Tumors ◽  
Medical Image ◽  
Resonance Imaging ◽  
Feature Maps ◽  
Deep Cnn

The classification of brain tumors is a difficult task in the field of medical image analysis. Improving algorithms and machine learning technology helps radiologists to easily diagnose the tumor without surgical intervention. In recent years, deep learning techniques have made excellent progress in the field of medical image processing and analysis. However, there are many difficulties in classifying brain tumors using magnetic resonance imaging; first, the difficulty of brain structure and the intertwining of tissues in it; and secondly, the difficulty of classifying brain tumors due to the high density nature of the brain. We propose a differential deep convolutional neural network model (differential deep-CNN) to classify different types of brain tumor, including abnormal and normal magnetic resonance (MR) images. Using differential operators in the differential deep-CNN architecture, we derived the additional differential feature maps in the original CNN feature maps. The derivation process led to an improvement in the performance of the proposed approach in accordance with the results of the evaluation parameters used. The advantage of the differential deep-CNN model is an analysis of a pixel directional pattern of images using contrast calculations and its high ability to classify a large database of images with high accuracy and without technical problems. Therefore, the proposed approach gives an excellent overall performance. To test and train the performance of this model, we used a dataset consisting of 25,000 brain magnetic resonance imaging (MRI) images, which includes abnormal and normal images. The experimental results showed that the proposed model achieved an accuracy of 99.25%. This study demonstrates that the proposed differential deep-CNN model can be used to facilitate the automatic classification of brain tumors.

Clinical relevance of diffusion and perfusion magnetic resonance imaging in assessing intra-axial brain tumors

2006 ◽  
Vol 48 (3) ◽  
pp. 150-159 ◽  
Author(s):  
N. Rollin ◽  
J. Guyotat ◽  
N. Streichenberger ◽  
J. Honnorat ◽  
V.-A. Tran Minh ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Brain Tumors ◽  
Clinical Relevance ◽  
Perfusion Magnetic Resonance Imaging ◽  
Resonance Imaging
Sign in / Sign up

Export Citation Format

Share Document