A survey of MRI-based medical image analysis for brain tumor studies
MRI-based medical image analysis for brain tumor studies is gaining attention in recent
times due to an increased need for efficient and objective evaluation of large amounts of …
times due to an increased need for efficient and objective evaluation of large amounts of …
Automatic brain tumor detection and segmentation using U-Net based fully convolutional networks
A major challenge in brain tumor treatment planning and quantitative evaluation is
determination of the tumor extent. The noninvasive magnetic resonance imaging (MRI) …
determination of the tumor extent. The noninvasive magnetic resonance imaging (MRI) …
Brain tumor detection: a long short-term memory (LSTM)-based learning model
To overcome the problems of automated brain tumor classification, a novel approach is
proposed based on long short-term memory (LSTM) model using magnetic resonance …
proposed based on long short-term memory (LSTM) model using magnetic resonance …
Fully automated detection and segmentation of meningiomas using deep learning on routine multiparametric MRI
KR Laukamp, F Thiele, G Shakirin, D Zopfs… - European …, 2019 - Springer
Objectives Magnetic resonance imaging (MRI) is the method of choice for imaging
meningiomas. Volumetric assessment of meningiomas is highly relevant for therapy …
meningiomas. Volumetric assessment of meningiomas is highly relevant for therapy …
Brain tumor segmentation with deep convolutional symmetric neural network
Gliomas are the most frequent primary brain tumors, which have a high mortality. Surgery is
the most commonly used treatment. Magnetic resonance imaging (MRI) is especially useful …
the most commonly used treatment. Magnetic resonance imaging (MRI) is especially useful …
Machine learning in meningioma MRI: past to present. A narrative review
E Neromyliotis, T Kalamatianos… - Journal of Magnetic …, 2022 - Wiley Online Library
Meningioma is one of the most frequent primary central nervous system tumors. While
magnetic resonance imaging (MRI), is the standard radiologic technique for provisional …
magnetic resonance imaging (MRI), is the standard radiologic technique for provisional …
Brain tumor segmentation based on local independent projection-based classification
Brain tumor segmentation is an important procedure for early tumor diagnosis and
radiotherapy planning. Although numerous brain tumor segmentation methods have been …
radiotherapy planning. Although numerous brain tumor segmentation methods have been …
A stacked multi-connection simple reducing net for brain tumor segmentation
Y Ding, F Chen, Y Zhao, Z Wu, C Zhang, D Wu - IEEE Access, 2019 - ieeexplore.ieee.org
It is well known that the Unet has been widely used in the area of medical image
segmentation because of the cascade connection in the up-sampling process. However, it …
segmentation because of the cascade connection in the up-sampling process. However, it …
Deep convolutional neural networks model-based brain tumor detection in brain MRI images
MAB Siddique, S Sakib, MMR Khan… - … Conference on I …, 2020 - ieeexplore.ieee.org
Diagnosing Brain Tumor with the aid of Magnetic Resonance Imaging (MRI) has gained
enormous prominence over the years primarily in the field of medical science. Detection …
enormous prominence over the years primarily in the field of medical science. Detection …
Fully automated MRI segmentation and volumetric measurement of intracranial meningioma using deep learning
Background Accurate and rapid measurement of the MRI volume of meningiomas is
essential in clinical practice to determine the growth rate of the tumor. Imperfect automation …
essential in clinical practice to determine the growth rate of the tumor. Imperfect automation …