Improved Edge Detection Algorithm for Brain Tumor Segmentation

Aslam, Asra; Khan, E.; Beg, M. M. Sufyan

doi:10.1016/j.procs.2015.08.057

Cited by 169 publications

(75 citation statements)

References 9 publications

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“…Aslam et al [18] built up an enhanced sobel edge detection system for brain tumor origin extraction. The improved sobel edge detection technique is used with dependent thresholding to finds different regions in MRI images using closed contour algorithm.…”

Section: Literaturementioning

confidence: 99%

Segmentation of Brain Tumor in Multimodal MRI using Histogram Differencing & KNN

Nida-Ur-Rehman¹,

Ahmed²,

Masood³

et al. 2017

ijacsa

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Section: Literaturementioning

confidence: 99%

Segmentation of Brain Tumor in Multimodal MRI using Histogram Differencing & KNN

Nida-Ur-Rehman¹,

Ahmed²,

Masood³

et al. 2017

ijacsa

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“…According to Aslam, Khan & Beg [33], who proposed an algorithm which can be used for edge detection for brain tumor segmentation. The proposed segmentation algorithm uses the following four steps and is based on automatic threshold calculations:…”

Section: Improved Edge Detection Algorithm For Brain Tumor Segmentationmentioning

confidence: 99%

“…Gopal & Karnan [37] suggested an algorithm which used multi-scale image segmentation, based on fuzzy c-mean algorithm for the detection of brain tumor. Joshi, Rana, & Misra [38] 6 Proposed method for segmentation [33].…”

Section: An Efficient Brain Tumor Detection Algorithm Using Watershedmentioning

confidence: 99%

Brain Tumor Detection from Medical Images: A Survey

Aslam¹,

Cui²

2017

Nano BioMed ENG

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He has published over 280 papers in international peer-reviewed journals, with a high-index of 45. His research interests include controlled synthesis and biosafety evaluation of nanomaterials, nanoparticles-labeling and nano-effects-based tumor theranostic technologies, high efficient drug delivery system and RNA nano-drug. AbstractNowadays, medical image processing has been one of the most challenging emerging field. Magnetic resonance imaging (MRI) technique is now widely used to detect brain tumor. This survey provides different strategies to detect and extract the brain tumor signal. The strategy for detecting and extracting the brain tumor signals is based on the MRI scanned images of the cerebrum. These methods incorporate some noise removal functions, segmentations and morphological operations which are the fundamental concepts of image processing. Detection and extraction of tumor signal from MRI scanned images of the cerebrum are carried out by MATLAB.

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“…Image segmentation is used to separate objects from the background, and thus it has proved to be a powerful tool in bio-medical imaging. [8]. Tumor segmentation from magnetic resonance imaging (MRI) process is an important but time ingesting manual project performed by doctors.…”

Section: Related Workmentioning

confidence: 99%