[HTML][HTML] Deep learning for medical image segmentation: State-of-the-art advancements and challenges
Image segmentation, a crucial process of dividing images into distinct parts or objects, has
witnessed remarkable advancements with the emergence of deep learning (DL) techniques …
witnessed remarkable advancements with the emergence of deep learning (DL) techniques …
Computational Intelligence-Based Disease Severity Identification: A Review of Multidisciplinary Domains
Disease severity identification using computational intelligence-based approaches is
gaining popularity nowadays. Artificial intelligence and deep-learning-assisted approaches …
gaining popularity nowadays. Artificial intelligence and deep-learning-assisted approaches …
[HTML][HTML] SwinUNeLCsT: Global–local spatial representation learning with hybrid CNN–transformer for efficient tuberculosis lung cavity weakly supervised semantic …
Radiological diagnosis of lung cavities (LCs) is the key to identifying tuberculosis (TB).
Conventional deep learning methods rely on a large amount of accurate pixel-level data to …
Conventional deep learning methods rely on a large amount of accurate pixel-level data to …
Enhancing the detection of airway disease by applying deep learning and explainable artificial intelligence
Airway diseases cause significant challenges while diagnosing it accurately as well as
timely. In current years, the combination of deep learning techniques with Explainable …
timely. In current years, the combination of deep learning techniques with Explainable …
Deep Learning-Based Classification of Chest Diseases Using X-rays, CT Scans, and Cough Sound Images
Chest disease refers to a variety of lung disorders, including lung cancer (LC), COVID-19,
pneumonia (PNEU), tuberculosis (TB), and numerous other respiratory disorders. The …
pneumonia (PNEU), tuberculosis (TB), and numerous other respiratory disorders. The …
DeepPulmoTB: A benchmark dataset for multi-task learning of tuberculosis lesions in lung computerized tomography (CT)
Tuberculosis (TB) remains a significant global health challenge, characterized by high
incidence and mortality rates on a global scale. With the rapid advancement of computer …
incidence and mortality rates on a global scale. With the rapid advancement of computer …
Defending Data Poisoning Attack through Watermarked Friendly Noise Luminosity Activated Dense Layered UNet for Classification of Lung Disease
An accurate and prompt diagnosis is essential since lung illnesses are a major global cause
of chronic illness and mortality. Conventional techniques for lung disease diagnosis …
of chronic illness and mortality. Conventional techniques for lung disease diagnosis …
Advances in medical image analysis: A comprehensive survey of lung infection detection
S Kordnoori, M Sabeti, H Mostafaei… - IET Image …, 2024 - Wiley Online Library
This research investigates advanced approaches in medical image analysis, specifically
focusing on segmentation and classification techniques, as well as their integration into multi …
focusing on segmentation and classification techniques, as well as their integration into multi …
Enhanced 3D-OTSU Algorithm for Robust Tuberculosis and COVID-19 CT Scans Segmentation
DO Alebiosu, CH Lim… - 2023 IEEE International …, 2023 - ieeexplore.ieee.org
While tuberculosis (TB) is a deadly disease, the coronavirus (COVID-19) has caused more
rapid death since its discovery in 2019. Studies have shown that the recovery rate of COVID …
rapid death since its discovery in 2019. Studies have shown that the recovery rate of COVID …
Computational intelligence on medical imaging with artificial neural networks
Computer-aided diagnosis systems based on artificial intelligence is widely utilized recently
by clinicians, particularly on medical imaging. In artificial intelligence, artificial neural …
by clinicians, particularly on medical imaging. In artificial intelligence, artificial neural …