Adapting an existing convolutional neural network architecture to a specific dataset for
medical image segmentation remains a challenging task that requires extensive expertise …

In today's medical practice clinicians need to struggle with a huge amount of data to improve
the outcomes of the patients. Sometimes one clinician needs to deal with thousands of …

Over the past decade, the enthusiasm for AI has been rising exponentially. Machine learning
was well known, but the increasing power of processors and the amount of data available …

In pelvic organ prolapse (POP), the organs are pushed downward along the lines of gravity,
so measurements along this longitudinal body axis are desirable. We propose a universally …

(57) ABSTRACT A system and methodology for the automated localization, extraction, and
analysis of MRI-based features with clinical information to improve the diagnosis of pelvic …

Artificial intelligence has yielded remarkably promising results in several medical fields,
namely those with a strong imaging component. Gynecology relies heavily on imaging since …

Unmanned Aerial Systems (UAS) are now capable of gathering high-resolution data,
therefore, landslides can be explored in detail at larger scales. In this research, 132 aerial …

Introduction and hypothesis Magnetic resonance imaging (MRI) plays an important role in
assessing pelvic organ prolapse (POP), and automated pelvic floor landmark localization …

Background Synthetic meshes are frequently used to reinforce soft tissues. The aim of this
translational study is to evaluate tolerance and long-term MRI visibility of two recently …

The automatic extraction of the vertebra's shape from dynamic magnetic resonance imaging
(MRI) could improve understanding of clinical conditions and their diagnosis. It is …