Biological images provide a wealth of information for various applications, enabling us to gain valuable insights into disease, understand biological processes, and drive advancements in research and development. For example, histological tissue sections play a critical role in disease diagnosis, understanding, and assessing therapies in drug discovery and development. Within these sections, crucial prognostic data is embedded, offering valuable insights into disease aggressiveness and patient outcomes. At Visikol, we leverage the power of machine learning to offer cutting-edge segmentation services tailored to your specific needs, regardless of the type of biological image you’re working with.
With significant advancements in computer software and hardware, machine learning has become an essential tool in a wide range of disciplines. Within the field of bio-imaging, major breakthroughs in computer vision and image processing techniques have revolutionized our ability to analyze and extract information from biological images.
Our Machine Learning Segmentation Services utilize classical or deep learning techniques based on supervised machine learning. Supervised machine learning involves training our algorithms on annotated datasets, where human experts carefully annotate the objects of interest to guide the learning process. This approach allows our algorithms to recognize and segment specific structures, patterns, or biomarkers within your biological images accurately.