Brain tumor detection and classification using intelligence techniques: an overview
A tumor is carried on by rapid and uncontrolled cell growth in the brain. If it is not treated in
the initial phases, it could prove fatal. Despite numerous significant efforts and encouraging …
the initial phases, it could prove fatal. Despite numerous significant efforts and encouraging …
IOUC-3DSFCNN: Segmentation of brain tumors via IOU constraint 3D symmetric full convolution network with multimodal auto-context
J Liu, H Liu, Z Tang, W Gui, T Ma, S Gong, Q Gao… - Scientific Reports, 2020 - nature.com
Accurate segmentation of brain tumors from magnetic resonance (MR) images play a pivot
role in assisting diagnoses, treatments and postoperative evaluations. However, due to its …
role in assisting diagnoses, treatments and postoperative evaluations. However, due to its …
Active contour model driven by optimized energy functionals for MR brain tumor segmentation with intensity inhomogeneity correction
Segmentation of brain tumors is important for medical diagnosis, treatment planning, and
disease development. However, the presence of image artifacts such as noise, intensity …
disease development. However, the presence of image artifacts such as noise, intensity …
Brain tumor segmentation with missing MRI modalities using edge aware discriminative feature fusion based transformer U-net
Brain tumor segmentation is an essential task for medical diagnosis and treatment planning.
Multi-modal MRI provides complementary information that is essential for accurate …
Multi-modal MRI provides complementary information that is essential for accurate …
Enhancing Autonomous Vehicle Navigation in Complex Environment With Semantic Proto‐Reinforcement Learning
Despite great progress in autonomous vehicle (AV) navigation, the technical challenges
within this space are still considerable when it comes to successful integration of AVs into …
within this space are still considerable when it comes to successful integration of AVs into …
Brain tumor segmentation using chi-square fuzzy C-mean clustering
Accurate brain tumor segmentation is an interesting and challenging task of magnetic
resonance imaging (MRI) in the field of medical image processing. For this purpose, we …
resonance imaging (MRI) in the field of medical image processing. For this purpose, we …
Design of Novel Brain Tumor Segmentation System Using Hybrid Heuristic-Aided Multiscale Self-Guided Attention Mechanism-Based Adaptive Unet+++ with 3D Brain …
D Ramya, C Lakshmi - … Journal of Pattern Recognition and Artificial …, 2024 - World Scientific
Segmentation of brain tumors attains great importance in the medical industry. As the brain
tumor causes an earlier death, detection and diagnosis are required. Generally, brain tumor …
tumor causes an earlier death, detection and diagnosis are required. Generally, brain tumor …
Glioma brain tumor identification using magnetic resonance imaging with deep learning methods: a systematic review
Z Khazaei, M Langarizadeh… - Journal of Health and …, 2021 - jhbmi.ir
Method: This study was a systematic review in which PubMed, ScienceDirect, Springer,
IEEE, and Arxiv databases were searched between 2010 and 2020 in order to retrieve …
IEEE, and Arxiv databases were searched between 2010 and 2020 in order to retrieve …
Perspective Review on Deep Learning Models to Medical Image Segmentation
In recent days, deep learning is on rage and is gaining a huge amount of popularity due to
its supremacy in terms of accuracy. Deep learning is being used for a vast number of …
its supremacy in terms of accuracy. Deep learning is being used for a vast number of …
[CITA][C] Novel center symmetric local binary pattern and chi square fuzzy c-mean clustering based segmentation in medical imaging technique
A Kumar, S Devi - International Journal of Scientific and Technology …, 2019