This study presents a comprehensive systematic review focusing on the applications of deep
learning techniques in lung cancer radiomics. Through a rigorous screening process of 589 …

Image fusion is a technique used to merge two or more source images into a single image
that incorporates more details than the originals and still offering an accurate depiction …

The efforts made to prevent the spread of COVID-19 face specific challenges in diagnosing
COVID-19 patients and differentiating them from patients with pulmonary edema. Although …

Accurate lung tumor identification is crucial for radiation treatment planning. Due to the low
contrast of the lung tumor in computed tomography (CT) images, segmentation of the tumor …

Lung cancer is one of the major causes of death in the world, according to radiologists.
However, a constant flow of medical images to hospitals is forcing radiologists to focus on …

Radiologists possess diverse training and clinical experiences, leading to variations in the
segmentation annotations of lung nodules and resulting in segmentation uncertainty …

Precise and unambiguous segmentation of pulmonary nodules from the CT images is
imperative for a CAD framework implementation delineated for the prognosis of lung cancer …

Precise segmentation of lung nodules from the surrounding tissues provides radiologists
with distinct boundary details, instrumental to the meticulous diagnosis and subsequent …

Nanoparticles (NPs) serve as the contrasting agent in the computed tomography (CT)
guided interventional devices and processes. The high contrast imaging of the patient is …

Lung cancer is a critical health issue that demands swift and accurate diagnosis for effective
treatment. In medical imaging, segmentation is crucial for identifying and isolating regions of …