Skin lesion analysis and cancer detection based on machine/deep learning techniques: A comprehensive survey

M Zafar, MI Sharif, MI Sharif, S Kadry, SAC Bukhari… - Life, 2023 - mdpi.com
The skin is the human body's largest organ and its cancer is considered among the most
dangerous kinds of cancer. Various pathological variations in the human body can cause …

[HTML][HTML] Artificial intelligence for visually impaired

J Wang, S Wang, Y Zhang - Displays, 2023 - Elsevier
The eyes are an essential tool for human observation and perception of the world, helping
people to perform their tasks. Visual impairment causes many inconveniences in the lives of …

BTS-ST: Swin transformer network for segmentation and classification of multimodality breast cancer images

A Iqbal, M Sharif - Knowledge-Based Systems, 2023 - Elsevier
Breast cancer is considered the most commonly diagnosed cancer globally and falls second
to lung cancer. For the early detection of breast tumors in women, breast cancer analysis …

A survey and taxonomy of 2.5 D approaches for lung segmentation and nodule detection in CT images

RJ Suji, SS Bhadauria, WW Godfrey - Computers in Biology and Medicine, 2023 - Elsevier
CAD systems for lung cancer diagnosis and detection can significantly offer unbiased,
infatiguable diagnostics with minimal variance, decreasing the mortality rate and the five …

An efficient deep learning-based framework for tuberculosis detection using chest X-ray images

A Iqbal, M Usman, Z Ahmed - Tuberculosis, 2022 - Elsevier
Early diagnosis of tuberculosis (TB) is an essential and challenging task to prevent disease,
decrease mortality risk, and stop transmission to other people. The chest X-ray (CXR) is the …

UNet: A semi-supervised method for segmentation of breast tumor images using a U-shaped pyramid-dilated network

A Iqbal, M Sharif - Expert Systems with Applications, 2023 - Elsevier
Rapid and precise segmentation of breast tumors is a severe challenge for the global
research community to diagnose breast cancer in younger females. An ultrasound system is …

Integration-and separation-aware adversarial model for cerebrovascular segmentation from TOF-MRA

C Chen, K Zhou, T Lu, H Ning, R Xiao - Computer Methods and Programs …, 2023 - Elsevier
Purpose Cerebrovascular segmentation from time-of-flight magnetic resonance angiography
(TOF-MRA) is important but challenging for the simulation and measurement of …

A Comprehensive Survey of Multi-Level Thresholding Segmentation Methods for Image Processing

M Amiriebrahimabadi, Z Rouhi, N Mansouri - Archives of Computational …, 2024 - Springer
In image processing, multi-level thresholding is a sophisticated technique used to delineate
regions of interest in images by identifying intensity levels that differentiate different …

EOSA-GAN: Feature enriched latent space optimized adversarial networks for synthesization of histopathology images using Ebola optimization search algorithm

ON Oyelade, AE Ezugwu - Biomedical Signal Processing and Control, 2023 - Elsevier
Generative adversarial networks (GAN) represent two deep learning (DL) models positioned
in an adversarial manner to generate and evaluate images. This area of research promises …

3d brain and heart volume generative models: A survey

Y Liu, G Dwivedi, F Boussaid, M Bennamoun - ACM Computing Surveys, 2024 - dl.acm.org
Generative models such as generative adversarial networks and autoencoders have gained
a great deal of attention in the medical field due to their excellent data generation capability …