Efficient Segmentation of Brain Tumor Using FL-SNM with a Metaheuristic Approach to Optimization
Sign Up to like & getrecommendations! Published in 2018 at "Journal of Medical Systems"
DOI: 10.1007/s10916-018-1135-y
Abstract: Nowadays, automatic tumor detection from brain images is extremely significant for many diagnostic as well as therapeutic purposes, due to the unpredictable shape and appearance of tumors. In medical image analysis, the automatic segmentation of… read more here.
Keywords: segmentation brain; brain tumor; efficient segmentation; brain ... See more keywords
Segmentation of brain MR images using a proper combination of DCS based method with MRF
Sign Up to like & getrecommendations! Published in 2017 at "Multimedia Tools and Applications"
DOI: 10.1007/s11042-017-4696-8
Abstract: Manual segmentation of Magnetic Resonance Images (MRI) is a time-consuming process, thus automatic segmentation of brain MR images has attracted more attention in recent years. In this paper, we introduce Dynamic Classifier Selection Markov Random… read more here.
Keywords: brain images; segmentation; method; mrf ... See more keywords
Learning Based Segmentation of CT Brain Images: Application to Postoperative Hydrocephalic Scans
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Transactions on Biomedical Engineering"
DOI: 10.1109/tbme.2017.2783305
Abstract: Objective: Hydrocephalus is a medical condition in which there is an abnormal accumulation of cerebrospinal fluid (CSF) in the brain. Segmentation of brain imagery into brain tissue and CSF [before and after surgery, i.e., preoperative… read more here.
Keywords: brain images; based segmentation; segmentation; segmentation brain ... See more keywords
Segmentation of Brain MR Images by Using Fully Convolutional Network and Gaussian Mixture Model with Spatial Constraints
Sign Up to like & getrecommendations! Published in 2019 at "Mathematical Problems in Engineering"
DOI: 10.1155/2019/4625371
Abstract: Accurate segmentation of brain tissue from magnetic resonance images (MRIs) is a critical task for diagnosis, treatment, and clinical research. In this paper, a novel algorithm (GMMD-U) that incorporates the modified full convolutional neural network… read more here.
Keywords: brain tissue; network; segmentation; model ... See more keywords
Brain SegNet: 3D local refinement network for brain lesion segmentation
Sign Up to like & getrecommendations! Published in 2020 at "BMC Medical Imaging"
DOI: 10.1186/s12880-020-0409-2
Abstract: MR images (MRIs) accurate segmentation of brain lesions is important for improving cancer diagnosis, surgical planning, and prediction of outcome. However, manual and accurate segmentation of brain lesions from 3D MRIs is highly expensive, time-consuming,… read more here.
Keywords: network; segmentation; brain segnet; segmentation brain ... See more keywords
Multi-Modal Segmentation of 3D Brain Scans Using Neural Networks
Sign Up to like & getrecommendations! Published in 2021 at "Frontiers in Neurology"
DOI: 10.3389/fneur.2021.653375
Abstract: Anatomical segmentation of brain scans is highly relevant for diagnostics and neuroradiology research. Conventionally, segmentation is performed on T1-weighted MRI scans, due to the strong soft-tissue contrast. In this work, we report on a comparative… read more here.
Keywords: brain scans; neural networks; segmentation; segmentation brain ... See more keywords
Segmentation of Brain Tumors from MRI Images Using Convolutional Autoencoder
Sign Up to like & getrecommendations! Published in 2021 at "Applied Sciences"
DOI: 10.3390/app11094317
Abstract: The use of machine learning algorithms and modern technologies for automatic segmentation of brain tissue increases in everyday clinical diagnostics. One of the most commonly used machine learning algorithms for image processing is convolutional neural… read more here.
Keywords: data division; autoencoder; segmentation; segmentation brain ... See more keywords