Current methods in medical image segmentation
▪ Abstract Image segmentation plays a crucial role in many medical-imaging applications, by
automating or facilitating the delineation of anatomical structures and other regions of …
automating or facilitating the delineation of anatomical structures and other regions of …
Ultrasound image segmentation: a survey
JA Noble, D Boukerroui - IEEE Transactions on medical …, 2006 - ieeexplore.ieee.org
This paper reviews ultrasound segmentation methods, in a broad sense, focusing on
techniques developed for medical B-mode ultrasound images. First, we present a review of …
techniques developed for medical B-mode ultrasound images. First, we present a review of …
Symtosis: A liver ultrasound tissue characterization and risk stratification in optimized deep learning paradigm
Abstract Background and Objective Fatty Liver Disease (FLD)-a disease caused by
deposition of fat in liver cells, is predecessor to terminal diseases such as liver cancer. The …
deposition of fat in liver cells, is predecessor to terminal diseases such as liver cancer. The …
Deep learning cascaded feature selection framework for breast cancer classification: Hybrid CNN with univariate-based approach
With the help of machine learning, many of the problems that have plagued mammography
in the past have been solved. Effective prediction models need many normal and tumor …
in the past have been solved. Effective prediction models need many normal and tumor …
Machine learning based liver disease diagnosis: A systematic review
The computer-based approach is required for the non-invasive detection of chronic liver
diseases that are asymptomatic, progressive, and potentially fatal in nature. In this study, we …
diseases that are asymptomatic, progressive, and potentially fatal in nature. In this study, we …
An automatic computer-aided diagnosis system for breast cancer in digital mammograms via deep belief network
Computer-aided diagnosis (CAD) offers assistance to radiologists in the interpretation of
medical images. A CAD system learns the nature of different tissues and uses this …
medical images. A CAD system learns the nature of different tissues and uses this …
Texture-based classification of atherosclerotic carotid plaques
CI Christodoulou, CS Pattichis… - IEEE transactions on …, 2003 - ieeexplore.ieee.org
There are indications that the morphology of atherosclerotic carotid plaques, obtained by
high-resolution ultrasound imaging, has prognostic implications. The objective of this study …
high-resolution ultrasound imaging, has prognostic implications. The objective of this study …
A hybrid deep transfer learning of CNN-based LR-PCA for breast lesion diagnosis via medical breast mammograms
One of the most promising research areas in the healthcare industry and the scientific
community is focusing on the AI-based applications for real medical challenges such as the …
community is focusing on the AI-based applications for real medical challenges such as the …
Study of features based on nonlinear dynamical modeling in ECG arrhythmia detection and classification
MI Owis, AH Abou-Zied, ABM Youssef… - IEEE transactions on …, 2002 - ieeexplore.ieee.org
We present a study of the nonlinear dynamics of electrocardiogram (ECG) signals for
arrhythmia characterization. The correlation dimension and largest Lyapunov exponent are …
arrhythmia characterization. The correlation dimension and largest Lyapunov exponent are …
Extreme learning machine framework for risk stratification of fatty liver disease using ultrasound tissue characterization
Abstract Fatty Liver Disease (FLD) is caused by the deposition of fat in liver cells and leads
to deadly diseases such as liver cancer. Several FLD detection and characterization …
to deadly diseases such as liver cancer. Several FLD detection and characterization …