Soft computing approaches for image segmentation: a survey
Image segmentation is the method of partitioning an image into a group of pixels that are
homogenous in some manner. The homogeneity dependents on some attributes like …
homogenous in some manner. The homogeneity dependents on some attributes like …
A review of image processing techniques common in human and plant disease diagnosis
N Petrellis - Symmetry, 2018 - mdpi.com
Image processing has been extensively used in various (human, animal, plant) disease
diagnosis approaches, assisting experts to select the right treatment. It has been applied to …
diagnosis approaches, assisting experts to select the right treatment. It has been applied to …
Image segmentation using computational intelligence techniques
Image segmentation methodology is a part of nearly all computer schemes as a pre-
processing phase to excerpt more meaningful and useful information for analysing the …
processing phase to excerpt more meaningful and useful information for analysing the …
Early diagnosis of Parkinson's disease using EEG, machine learning and partial directed coherence
APS De Oliveira, MA De Santana… - Research on Biomedical …, 2020 - Springer
Background Parkinson's disease (PD) is a neurodegenerative disease, which has an
upward progression. In advanced stages, motor symptoms cause functional impairment to …
upward progression. In advanced stages, motor symptoms cause functional impairment to …
Role of AI techniques and deep learning in analyzing the critical health conditions
The role of a healthcare practitioner is to diagnose a disease and find an optimum means for
suitable treatment. This has been the most challenging task over the years. The researchers …
suitable treatment. This has been the most challenging task over the years. The researchers …
Deep-wavelet neural networks for breast cancer early diagnosis using mammary termographies
In this chapter, we introduce the deep-wavelet neural network (DWNN) as a features
extraction method for image representation. DWNN is a deep learning tool based on the …
extraction method for image representation. DWNN is a deep learning tool based on the …
Detection and classification of mammary lesions using artificial neural networks and morphological wavelets
TN Cruz, TM Cruz, WP Santos - IEEE Latin America …, 2018 - ieeexplore.ieee.org
Breast cancer is a worldwide public health problem, with a high rate of incidence and
mortality. The most widely used to perform early on possible abnormalities in breast tissue is …
mortality. The most widely used to perform early on possible abnormalities in breast tissue is …
The Progress of Medical Image Semantic Segmentation Methods for Application in COVID‐19 Detection
Image medical semantic segmentation has been employed in various areas, including
medical imaging, computer vision, and intelligent transportation. In this study, the method of …
medical imaging, computer vision, and intelligent transportation. In this study, the method of …
Detection of breast cancer mass using MSER detector and features matching
SA Hassan, MS Sayed, MI Abdalla… - Multimedia Tools and …, 2019 - Springer
Detection of breast cancer masses in mammogram images is an essential step in any
computer-aided system for breast cancer diagnosis. In this paper, we propose a novel …
computer-aided system for breast cancer diagnosis. In this paper, we propose a novel …
COVID-19's influence on cardiac function: a machine learning perspective on ECG analysis
In December 2019, the spread of the SARS-CoV-2 virus to the world gave rise to probably
the biggest public health problem in the world: the COVID-19 pandemic. Initially seen only …
the biggest public health problem in the world: the COVID-19 pandemic. Initially seen only …