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Artificial intelligence in the radiomic analysis of glioblastomas: A review, taxonomy, and perspective
M Zhu, S Li, Y Kuang, VB Hill, AB Heimberger… - Frontiers in …, 2022 - frontiersin.org
Radiological imaging techniques, including magnetic resonance imaging (MRI) and positron
emission tomography (PET), are the standard-of-care non-invasive diagnostic approaches …
emission tomography (PET), are the standard-of-care non-invasive diagnostic approaches …
[HTML][HTML] TumorGAN: A multi-modal data augmentation framework for brain tumor segmentation
The high human labor demand involved in collecting paired medical imaging data severely
impedes the application of deep learning methods to medical image processing tasks such …
impedes the application of deep learning methods to medical image processing tasks such …
Automatic brain lesion segmentation on standard magnetic resonance images: a sco** review
E Gryska, J Schneiderman, I Björkman-Burtscher… - BMJ open, 2021 - bmjopen.bmj.com
Objectives Medical image analysis practices face challenges that can potentially be
addressed with algorithm-based segmentation tools. In this study, we map the field of …
addressed with algorithm-based segmentation tools. In this study, we map the field of …
Brain tumor segmentation in MR images using a sparse constrained level set algorithm
X Lei, X Yu, J Chi, Y Wang, J Zhang, C Wu - Expert Systems With …, 2021 - Elsevier
Brain tumor segmentation using Magnetic Resonance (MR) Imaging technology plays a
significant role in computer-aided brain tumor diagnosis. However, when applying classic …
significant role in computer-aided brain tumor diagnosis. However, when applying classic …
Glioma segmentation with a unified algorithm in multimodal MRI images
To achieve the better segmentation performance, we propose a unified algorithm for
automatic glioma segmentation. In this paper, we first use spatial fuzzy c-mean clustering to …
automatic glioma segmentation. In this paper, we first use spatial fuzzy c-mean clustering to …
A clinical support system for brain tumor classification using soft computing techniques
PRE Arasi, M Suganthi - Journal of medical systems, 2019 - Springer
A brain tumor is an accumulation of abnormal cells in human brain. As tumor increases in
size, it induces brain damage. Hence it is essential to diagnose the type of brain tumor. The …
size, it induces brain damage. Hence it is essential to diagnose the type of brain tumor. The …
A stochastic multi-agent approach for medical-image segmentation: application to tumor segmentation in brain MR images
MT Bennai, Z Guessoum, S Mazouzi, S Cormier… - Artificial Intelligence in …, 2020 - Elsevier
According to functional or anatomical modalities, medical imaging provides a visual
representation of complex structures or activities in the human body. One of the most …
representation of complex structures or activities in the human body. One of the most …
[PDF][PDF] Survey of brain tumor segmentation techniques on magnetic resonance imaging
M Hameurlaine, A Moussaoui - Nano Biomedicine and Engineering, 2019 - academia.edu
Brain tumor extraction is challenging task because brain image and its structure are
complicated that can be analyzed only by expert physicians or radiologist. Brain tumor …
complicated that can be analyzed only by expert physicians or radiologist. Brain tumor …
[PDF][PDF] Brain tumour detection using deep learning techniques
PT Selvy, VP Dharani, A Indhuja - Int. J. Sci. Res. Comput. Sci. Eng …, 2019 - academia.edu
In recent years the occurrence of brain tumor has exaggerated in large amount among the
people. Gliomas are one of the most common types of primary brain tumors that represent …
people. Gliomas are one of the most common types of primary brain tumors that represent …
Recent advancements in fuzzy C-means based techniques for brain MRI segmentation
Background: Variations of image segmentation techniques, particularly those used for Brain
MRI segmentation, vary in complexity from basic standard Fuzzy C-means (FCM) to more …
MRI segmentation, vary in complexity from basic standard Fuzzy C-means (FCM) to more …