Within-brain classification for brain tumor segmentation
Purpose In this paper, we investigate a framework for interactive brain tumor segmentation
which, at its core, treats the problem of interactive brain tumor segmentation as a machine …
which, at its core, treats the problem of interactive brain tumor segmentation as a machine …
[HTML][HTML] A survey of brain tumor segmentation and classification algorithms
A brain Magnetic resonance imaging (MRI) scan of a single individual consists of several
slices across the 3D anatomical view. Therefore, manual segmentation of brain tumors from …
slices across the 3D anatomical view. Therefore, manual segmentation of brain tumors from …
[HTML][HTML] GenU-Net++: An Automatic Intracranial Brain Tumors Segmentation Algorithm on 3D Image Series with High Performance
Y Zhang, X Liu, S Wa, Y Liu, J Kang, C Lv - Symmetry, 2021 - mdpi.com
Automatic segmentation of intracranial brain tumors in three-dimensional (3D) image series
is critical in screening and diagnosing related diseases. However, there are various …
is critical in screening and diagnosing related diseases. However, there are various …
A validation framework for brain tumor segmentation
N Archip, FA Jolesz, SK Warfield - Academic radiology, 2007 - Elsevier
RATIONALE AND OBJECTIVES: We introduce a validation framework for the segmentation
of brain tumors from magnetic resonance (MR) images. A novel unsupervised …
of brain tumors from magnetic resonance (MR) images. A novel unsupervised …
A convolutional neural network approach to brain tumor segmentation
We consider the problem of fully automatic brain focal pathology segmentation, in MR
images containing low and high grade gliomas and ischemic stroke lesion. We propose a …
images containing low and high grade gliomas and ischemic stroke lesion. We propose a …
Brain tumor segmentation in MRI scans using deeply-supervised neural networks
R Pourreza, Y Zhuge, H Ning, R Miller - Brainlesion: Glioma, Multiple …, 2018 - Springer
Gliomas are the most frequent primary brain tumors in adults. Improved quantification of the
various aspects of a glioma requires accurate segmentation of the tumor in magnetic …
various aspects of a glioma requires accurate segmentation of the tumor in magnetic …
Brain tumor segmantation using random forest trained on iteratively selected patients
A Ellwaa, A Hussein, E AlNaggar, M Zidan… - … Sclerosis, Stroke and …, 2016 - Springer
This paper extends a previously published brain tumor segmentation methods based on
Random Decision Forest (RDF). An iterative approach is used in training the RDF in each …
Random Decision Forest (RDF). An iterative approach is used in training the RDF in each …
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 …
Anatomy-guided brain tumor segmentation and classification
In this paper, we consider the problem of fully automatic brain tumor segmentation in
multimodal magnetic resonance images. In contrast to applying classification on entire …
multimodal magnetic resonance images. In contrast to applying classification on entire …
Brain tumor segmentation using convolutional neural networks in MRI images
Among brain tumors, gliomas are the most common and aggressive, leading to a very short
life expectancy in their highest grade. Thus, treatment planning is a key stage to improve the …
life expectancy in their highest grade. Thus, treatment planning is a key stage to improve the …