Organs-on-chips (OoCs) are miniature microfluidic systems that have arguably become a
class of advanced in vitro models. Deep learning, as an emerging topic in machine learning …

Segmenting medical images is a necessary prerequisite for disease diagnosis and
treatment planning. Among various medical image segmentation tasks, U-Net-based …

Cracks are one of the safety-evaluation indicators for structures, providing a maintenance
basis for the health and safety of structures in service. Most structural inspections rely on …

Cervical cancer poses a significant global health burden, affecting women worldwide.
Timely and accurate detection is crucial for effective treatment and improved patient …

Image segmentation is a crucial aspect of clinical decision making in medicine, and as such,
it has greatly enhanced the sustainability of medical care. Consequently, biomedical image …

Measuring bathymetry has always been a major scientific and technological challenge. In
this work, we used a deep learning technique for inferring bathymetry from the depth …

Computer-assisted technologies have made significant progress in fetoscopic laser surgery,
including placental vessel segmentation. However, the intra-and inter-procedure variabilities …

The manual segmentation of retinal layers from OCT scan images is time-consuming and
costly. The deep learning approach has potential for the automatic delineation of retinal …

Background: Chronic obstructive pulmonary disease (COPD) typically causes airflow
blockage and breathing difficulties, which may result in the abnormal morphology and …

Background: Image analysis applications in digital pathology include various methods for
segmenting regions of interest. Their identification is one of the most complex steps and …