Brain tumor detection and classification using machine learning: a comprehensive survey

J Amin, M Sharif, A Haldorai, M Yasmin… - Complex & intelligent …, 2022 - Springer
Brain tumor occurs owing to uncontrolled and rapid growth of cells. If not treated at an initial
phase, it may lead to death. Despite many significant efforts and promising outcomes in this …

A comprehensive review on multi-organs tumor detection based on machine learning

MI Sharif, JP Li, J Naz, I Rashid - Pattern Recognition Letters, 2020 - Elsevier
Tumor is comprised of abnormally growing regions that is dangerous for human survival.
Therefore, early stage tumor detection is useful for increase of survival rate although it is …

Contrast enhanced medical MRI evaluation using Tsallis entropy and region growing segmentation

NSM Raja, SL Fernandes, N Dey, SC Satapathy… - Journal of Ambient …, 2024 - Springer
In medical domain, diseases in critical internal organs are generally inspected using
invasive/non-invasive imaging techniques. Magnetic resonance imaging (MRI) is one of the …

An improved emperor penguin optimization based multilevel thresholding for color image segmentation

Z Xing - Knowledge-Based Systems, 2020 - Elsevier
This paper proposes a multi-threshold image segmentation method based on improved
emperor penguin optimization (EPO). The calculation complexity of multi-thresholds …

Breast-cancer detection using thermal images with marine-predators-algorithm selected features

V Rajinikanth, S Kadry, D Taniar… - … conference on bio …, 2021 - ieeexplore.ieee.org
Breast-cancer (BC) is one of the major diseases in women group and the early diagnosis
and treatment is necessary to cure the disease. Early detection of BC is very essential to …

Quantum marine predators algorithm for addressing multilevel image segmentation

M Abd Elaziz, D Mohammadi, D Oliva… - Applied Soft Computing, 2021 - Elsevier
This paper proposes a modified marine predators algorithm based on quantum theory to
handle the multilevel image segmentation problem. The main aims of using quantum theory …

Development of a machine-learning system to classify lung CT scan images into normal/COVID-19 class

S Kadry, V Rajinikanth, S Rho, NSM Raja… - arXiv preprint arXiv …, 2020 - arxiv.org
Recently, the lung infection due to Coronavirus Disease (COVID-19) affected a large human
group worldwide and the assessment of the infection rate in the lung is essential for …

Stomach deformities recognition using rank-based deep features selection

MA Khan, M Sharif, T Akram, M Yasmin… - Journal of medical …, 2019 - Springer
Doctor utilizes various kinds of clinical technologies like MRI, endoscopy, CT scan, etc., to
identify patient's deformity during the review time. Among set of clinical technologies …

An integrated framework for COVID‐19 classification based on classical and quantum transfer learning from a chest radiograph

MJ Umer, J Amin, M Sharif, MA Anjum… - Concurrency and …, 2022 - Wiley Online Library
COVID‐19 is a quickly spreading over 10 million persons globally. The overall number of
infected patients worldwide is estimated to be around 133,381,413 people. Infection rate is …

Fractured elbow classification using hand-crafted and deep feature fusion and selection based on whale optimization approach

S Malik, J Amin, M Sharif, M Yasmin, S Kadry, S Anjum - Mathematics, 2022 - mdpi.com
The fracture of the elbow is common in human beings. The complex structure of the elbow,
including its irregular shape, border, etc., makes it difficult to correctly recognize elbow …