Digital well-being records are multimodal and high-dimensional (HD). Better theradiagnostics stem from new computationally thorough and edgy technologies, i.e., hyperspectral (HSI) imaging, super-resolution, and nanoimaging, but advance mess data por...
BACKGROUND: Cancer is a deadly disease. It is crucial to diagnose cancer in its early stages. This can be done with medical imaging. Medical imaging helps us scan and view internal organs. The analysis of these images is a very important task in the ...
Machine Learning (ML) plays an essential part in the research area of medical image processing. The advantages of ML techniques lead to more intelligent, accurate, and automatic computeraided detection (CAD) systems with improved learning capability....
OBJECTIVES: To differentiate the primary small-cell lung cancer (SCLC) and non-small-cell lung cancer (NSCLC) for patients with brain metastases (BMs) based on a deep learning (DL) model using contrast-enhanced magnetic resonance imaging (MRI) T1 wei...
BACKGROUND: Lung cancer has the highest mortality rate among cancers. Radiation therapy (RT) is one of the most effective therapies for lung cancer. The correct segmentation of lung tumors (LTs) and organs at risk (OARs) is the cornerstone of success...
BACKGROUND: The techniques differed in many of the literature on the detection of Acute Lymphocytic Leukemia from the blood smear pictures, as the cases of infection in the world and the Kingdom of Saudi Arabia were increasing and the causes of this ...
BACKGROUND: 8% of women are diagnosed with breast cancer. (BC) BC is the second most common cause of death in both developed and undeveloped countries. BC is characterized by the mutation of genes, constant pain, changes in the size, color (redness),...
Deep learning is a prominent method for automatic detection of COVID-19 disease using a medical dataset. This paper aims to give a perspective on the data insufficiency issue that exists in COVID-19 detection associated with deep learning. The extens...