Breast tumor localization and segmentation using machine learning techniques: Overview of datasets, findings, and methods

R Ranjbarzadeh, S Dorosti, SJ Ghoushchi… - Computers in Biology …, 2023 - Elsevier
Abstract The Global Cancer Statistics 2020 reported breast cancer (BC) as the most
common diagnosis of cancer type. Therefore, early detection of such type of cancer would …

Lung Infection Segmentation for COVID‐19 Pneumonia Based on a Cascade Convolutional Network from CT Images

R Ranjbarzadeh… - BioMed Research …, 2021 - Wiley Online Library
The COVID‐19 pandemic is a global, national, and local public health concern which has
caused a significant outbreak in all countries and regions for both males and females …

[HTML][HTML] Nerve optic segmentation in CT images using a deep learning model and a texture descriptor

R Ranjbarzadeh, S Dorosti… - Complex & Intelligent …, 2022 - Springer
The increased intracranial pressure (ICP) can be described as an increase in pressure
around the brain and can lead to serious health problems. The assessment of ultrasound …

TPCNN: two-path convolutional neural network for tumor and liver segmentation in CT images using a novel encoding approach

A Aghamohammadi, R Ranjbarzadeh, F Naiemi… - Expert Systems with …, 2021 - Elsevier
Automatic liver and tumour segmentation in CT images are crucial in numerous clinical
applications, such as postoperative assessment, surgical planning, and pathological …

Investigation of Effectiveness of Shuffled Frog‐Leaping Optimizer in Training a Convolution Neural Network

S Baseri Saadi, N Tataei Sarshar… - Journal of …, 2022 - Wiley Online Library
One of the leading algorithms and architectures in deep learning is Convolution Neural
Network (CNN). It represents a unique method for image processing, object detection, and …

[HTML][HTML] A novel image processing approach to enhancement and compression of X-ray images

Y Pourasad, F Cavallaro - … Journal of Environmental Research and Public …, 2021 - mdpi.com
At present, there is an increase in the capacity of data generated and stored in the medical
area. Thus, for the efficient handling of these extensive data, the compression methods need …

A feature selection approach for fall detection using various machine learning classifiers

TM Le, L Van Tran, SVT Dao - IEEE Access, 2021 - ieeexplore.ieee.org
Falls are one of the most serious dangers for elderly people who live alone at home. It has
become a widespread issue all across the world. Reliable fall detection systems can help to …

Car detection and damage segmentation in the real scene using a deep learning approach

M Parhizkar, M Amirfakhrian - International Journal of Intelligent Robotics …, 2022 - Springer
Automatically detecting the outer car surface damage can considerably reduce the cost of
processing premium assertion, and provide satisfaction for vehicle users. Since computer …

Fall detection using human skeleton features

H Ramirez, SA Velastin, E Fabregas, I Meza, D Makris… - 2021 - IET
Falls are one of the leading causes of death and serious injury in people, especially for the
elderly. In addition, falls accidents have a direct financial cost for health systems and …

[HTML][HTML] A multimodal approach of machine and deep learnings to enhance the fall of elderly people

S Al Meraikhi, M Al-Rajab - Journal of Information Technology …, 2022 - jitm.ut.ac.ir
Falls are a serious concern among the elderly due to being a major cause of harm to their
physical and mental health. Despite their potential for harm, they can be prevented with …