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Article
A novel context-sensitive attitude entropy-based multiclass segmentation method for brain MR images using enhanced flow directional algorithm
Computer vision techniques, aided by artificial intelligence, in medical image analysis, are currently encouraged for precise and speedy diagnosis of brain disorders. The brain MR image shows an intensity vari...
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Article
Exponential entropy-based multilevel thresholding using enhanced barnacle mating optimization
Multilevel Thresholding (MLT) is a prominent image segmentation research field that can effectively handle problems encountered while collecting meaningful information from a digital image. Most of the existin...
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Article
Pathological brain classification using multiple kernel-based deep convolutional neural network
Conventionally, fine-tuning or transfer learning using a pre-trained convolutional network is adopted to design a classifier. However, when the dataset is small this can deteriorate the classifier generalizati...
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Article
A non-entropy-based optimal multilevel threshold selection technique for COVID-19 X-ray images using chance-based birds’ intelligence
Recently, image thresholding methods based on various entropy functions have been found popularity. Nonetheless, entropic-based methods depend on the spatial distribution of the grey level values in an image. ...
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Article
Molecular imaging analysis in cancer using deep learning: a review
Molecular imaging (MI) empowers the representation and quantitative investigation of the methodologies at molecular as well as cellular levels. It is important for the early discovery of malignant growth. This...
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Chapter and Conference Paper
An Efficient Deep Learning-Based Breast Cancer Detection Scheme with Small Datasets
Breast cancer is the second major reason of cancer death among women. Automatic and accurate detection of cancer at an early stage, allow proper treatment to the patients and drastically reduces the death rate...
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Chapter and Conference Paper
An Error Sensitive Fuzzy Clustering Technique for Mammogram Image Segmentation
Mammogram image segmentation plays a crucial role in detecting the lesion region in the breast masses. In this context, the key challenging issue is the false positive detection of pectoral muscles or fatty ti...
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Article
Data science methodologies in smart healthcare: a review
Data Science methodologies empower the representation and quantitative investigation in the field of smart healthcare. It is of extraordinary noteworthiness for early detection/classification of diseases for t...
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Chapter and Conference Paper
Adaptive Grey wolf Optimization Algorithm with Gaussian Mutation
Grey wolf optimizer is a well-known optimization algorithm and is still being investigated by the researcher to improve its performance for applying in complex optimization problems. This paper introduced an a...
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Article
A leader Harris hawks optimization for 2-D Masi entropy-based multilevel image thresholding
The multilevel image thresholding is one of the important steps in multimedia tools to understand and interpret the object in the real world. Nevertheless, 1-D Masi entropy is quite new in the thresholding app...
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Article
Adaptive opposition slime mould algorithm
Recently, the slime mould algorithm (SMA) has become popular in function optimization, because it effectively uses exploration and exploitation to reach an optimal solution or near-optimal solution. However, t...
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Chapter and Conference Paper
Multilevel Thresholding Using Black Widow Optimization
The key objective of any multilevel thresholding method is to obtain the optimal thresholds on a target image for the region of interest. Traditional methods of multilevel thresholding suffer from poor accurac...
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Chapter and Conference Paper
A Nonlocal Spatial Coherent Fuzzy C-Means Clustering for Bias Field Correction in Brain MR Images
Bias field in magnetic resonance (MR) images is caused due to the varying gradient driven eddy current in the MR image scanner. This results in intensity inhomogeneity (IIH) in the MR image. Therefore, bias fi...
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Chapter and Conference Paper
A Differential Squirrel Search Algorithm
This paper presents a new hybrid differential squirrel search algorithm optimization algorithm (DSSE) by combining the searching methods of a squirrel search algorithm and differential evolution optimization p...
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Article
Design of optimal low-pass filter by a new Levy swallow swarm algorithm
The swallow swarm optimization (SS) is a challenging method of optimization, which has a quicker convergence speed, not getting caught in the local extreme points. However, the SS suffers from a few shortcomin...
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Chapter and Conference Paper
Medical Image Denoising Using Spline Based Fuzzy Wavelet Shrink Technique
Denoising is a fundamental requirement in the field of medical image processing. It is the process of reducing the additive noise from a noisy medical image, while preserving the information from the clinical...
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Chapter
A New Hybrid Adaptive Cuckoo Search-Squirrel Search Algorithm for Brain MR Image Analysis
This chapter presents a new hybrid adaptive cuckoo search-squirrel search ( ) algorithm for brain magnetic resonance (MR) image analysis. Thresholding is one of the popular methods utilized for brain image seg...
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Chapter and Conference Paper
A Novel Optimal Gabor Algorithm for Face Classification
Over the past decade, most of the research in the area of pattern classification has emphasized the use of Gabor filter (GF) banks for extracting features. Typically, the design and the choice of GF banks are ...
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Chapter and Conference Paper
Gauss-Newton Representation Based Algorithm for Magnetic Resonance Brain Image Classification
Brain tumor is a harmful disease worldwide. Every year, a majority of adults as well as children dies due to brain tumor. Early detection of the tumor can enhance the survival rate. Many brain image classifica...
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Chapter and Conference Paper
Study of a Multiuser Kurtosis Algorithm and an Information Maximization Algorithm for Blind Source Separation
An attempt is made in this study to use two distinct algorithms to inspect blind source separation (BSS). In this paper, we have used multiuser Kurtosis (MUK) algorithm for BSS and an information maximization ...
