[HTML][HTML] Computer-aided breast cancer detection and classification in mammography: A comprehensive review
Cancer is the second cause of mortality worldwide and it has been identified as a perilous
disease. Breast cancer accounts for∼ 20% of all new cancer cases worldwide, making it a …
disease. Breast cancer accounts for∼ 20% of all new cancer cases worldwide, making it a …
Opposition based learning: A literature review
Opposition-based Learning (OBL) is a new concept in machine learning, inspired from the
opposite relationship among entities. In 2005, for the first time the concept of opposition was …
opposite relationship among entities. In 2005, for the first time the concept of opposition was …
Benign and malignant breast tumors classification based on region growing and CNN segmentation
Breast cancer is regarded as one of the most frequent mortality causes among women. As
early detection of breast cancer increases the survival chance, creation of a system to …
early detection of breast cancer increases the survival chance, creation of a system to …
Zernike polynomials and their applications
K Niu, C Tian - Journal of Optics, 2022 - iopscience.iop.org
The Zernike polynomials are a complete set of continuous functions orthogonal over a unit
circle. Since first developed by Zernike in 1934, they have been in widespread use in many …
circle. Since first developed by Zernike in 1934, they have been in widespread use in many …
Radiomics and machine learning of multisequence multiparametric prostate MRI: Towards improved non-invasive prostate cancer characterization
J Toivonen, I Montoya Perez, P Movahedi, H Merisaari… - PloS one, 2019 - journals.plos.org
Purpose To develop and validate a classifier system for prediction of prostate cancer (PCa)
Gleason score (GS) using radiomics and texture features of T2-weighted imaging (T2w) …
Gleason score (GS) using radiomics and texture features of T2-weighted imaging (T2w) …
Breast mass classification in digital mammography based on extreme learning machine
This paper presents a novel computer-aided diagnosis (CAD) system for the diagnosis of
breast cancer based on extreme learning machine (ELM). In view of a mammographic …
breast cancer based on extreme learning machine (ELM). In view of a mammographic …
Conventional machine learning versus deep learning for magnification dependent histopathological breast cancer image classification: A comparative study with …
Breast cancer is a serious threat to women. Many machine learning-based computer-aided
diagnosis (CAD) methods have been proposed for the early diagnosis of breast cancer …
diagnosis (CAD) methods have been proposed for the early diagnosis of breast cancer …
A hybrid artificial bee colony with whale optimization algorithm for improved breast cancer diagnosis
Breast cancer is the most common among women that leads to death if not diagnosed at
early stages. Early diagnosis plays a vital role in decreasing the mortality rate globally …
early stages. Early diagnosis plays a vital role in decreasing the mortality rate globally …
A convolutional neural network with feature fusion for real-time hand posture recognition
SF Chevtchenko, RF Vale, V Macario… - Applied Soft Computing, 2018 - Elsevier
Gesture based human–computer interaction is both intuitive and versatile, with diverse
applications such as in smart houses, operating theaters and vehicle infotainment systems …
applications such as in smart houses, operating theaters and vehicle infotainment systems …
Automatic target recognition of synthetic aperture radar (SAR) images based on optimal selection of Zernike moments features
M Amoon, G Rezai‐rad - IET Computer Vision, 2014 - Wiley Online Library
In the present study, a new algorithm for automatic target detection (ATR) in synthetic
aperture radar (SAR) images has been proposed. First, moving and stationary target …
aperture radar (SAR) images has been proposed. First, moving and stationary target …