Brain tumor segmentation based on a hybrid clustering technique
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TLDR
The experimental results clarify the effectiveness of the proposed approach to deal with a higher number of segmentation problems via improving the segmentation quality and accuracy in minimal execution time.About:
This article is published in Egyptian Informatics Journal.The article was published on 2015-03-01 and is currently open access. It has received 316 citations till now. The article focuses on the topics: Scale-space segmentation & Segmentation-based object categorization.read more
Citations
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Journal ArticleDOI
Metrics for evaluating 3D medical image segmentation: analysis, selection, and tool
Abdel Aziz Taha,Allan Hanbury +1 more
TL;DR: An efficient evaluation tool for 3D medical image segmentation is proposed using 20 evaluation metrics based on a comprehensive literature review and guidelines for selecting a subset of these metrics that is suitable for the data and the segmentation task are provided.
Journal ArticleDOI
Image Analysis for MRI Based Brain Tumor Detection and Feature Extraction Using Biologically Inspired BWT and SVM
TL;DR: Berkeley wavelet transformation (BWT) based brain tumor segmentation is investigated to improve the accuracy and quality rate of the support vector machine (SVM) based classifier, relevant features are extracted from each segmented tissue.
Journal ArticleDOI
MRI based medical image analysis: Survey on brain tumor grade classification
Geethu Mohan,M. Monica Subashini +1 more
TL;DR: The current trends in segmentation and classification relevant to tumor infected human brain MR images with a target on gliomas which include astrocytoma are retrospected.
Journal ArticleDOI
A distinctive approach in brain tumor detection and classification using MRI
TL;DR: An automated method is proposed to easily differentiate between cancerous and non-cancerous Magnetic Resonance Imaging (MRI) of the brain and can be used to identify the tumor more accurately in less processing time as compared to existing methods.
Journal ArticleDOI
A review on brain tumor segmentation of MRI images.
TL;DR: Through the entire review process, it has been observed that the combination of Conditional Random Field (CRF) with Fully Convolutional Neural Network (FCNN) and CRF with DeepMedic or Ensemble are more effective for the segmentation of tumor from the brain MRI images.
References
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Snakes : Active Contour Models
TL;DR: This work uses snakes for interactive interpretation, in which user-imposed constraint forces guide the snake near features of interest, and uses scale-space continuation to enlarge the capture region surrounding a feature.
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Does median filtering truly preserve edges better than linear filtering
Ery Arias-Castro,David L. Donoho +1 more
TL;DR: It is shown that median filtering and linear filtering have similar asymptotic worst-case mean-squared error when the signal-to-noise ratio (SNR) is of order 1, which corresponds to the case of constant per-pixel noise level in a digital signal.
Image Segmentation Techniques
Rajeshwar Dass,Swapna Devi +1 more
TL;DR: The different segmentation techniques used in the field of ultrasound and SAR Image Processing are described and general tendencies in image segmentation are presented.
Proceedings Article
A new evaluation measure for imbalanced datasets
Cheng G. Weng,Josiah Poon +1 more
TL;DR: This paper introduces a novel measure as a better alternative for evaluating imbalanced dataset and provides a theoretical background for the new evaluation technique that is designed to cope with cost biases, which changes the previous view about class independent evaluation methods cannot deal with costs.
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Segmentation of Bone Structure in X-ray Images using Convolutional Neural Network
TL;DR: The segmentation process represents a first step necessary for any automatic method of extracting information from an image, and in the case of X-ray images, through segmentation it can be used to extract information from X-rays.
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