Computer vision is a branch of computer science that studies how computers can 'see'. It is a
field that provides significant value for advancements in academia and artificial intelligence …

Recent advancements in biomedical image analysis have been significantly driven by the
Segment Anything Model (SAM). This transformative technology, originally developed for …

Purpose Among the different available methods for synthetic CT generation from MR images
for the task of MR-guided radiation planning, the deep learning algorithms have and do …

Automated medical image segmentation is an essential task to aid/speed up diagnosis and
treatment procedures in clinical practices. Deep convolutional neural networks have …

The vertebrate respiratory system is challenging to study. The complex relationship between
the lungs and adjacent tissues, the vast structural diversity of the respiratory system both …

The adoption of “artificial intelligence (AI) in drug discovery”, where AI is used in the process
of pharmaceutical research and development, is progressing. By using the ability to process …

This study aimed to evaluate the performance of a novel unsupervised deep learning-based
framework for automated infections lesion segmentation from CT images of Covid patients …

Background In diagnostic X-ray computed tomography (CT) imaging, some applications,
such as dose measurement using the Monte Carlo method and material decomposition …

Image segmentation plays a significant role in quantitative image analysis. Lung
segmentation of CT images has received more importance in fighting against COVID-19. In …

Automated segmentation of COVID-19 lesions from CT images is a prerequisite for
quantitative assessment of the infections, enabling accurate and timely screening of the …