Anatomical localization of findings, as well as the assessment of organ and tissue size and structure, are critical steps in the analysis of medical images. Segmentation of organs and tissues is, therefore, a natural and essential first step in many AI applications.
Introducing Organ Finder: A Cutting-Edge AI Tool
SliceVault has developed the advanced AI tool Organ Finder, which excels at accurately segmenting organs in CT studies. Building on Organ Finder's powerful capabilities, we have also created specialized tools for quality checks in CT studies used in clinical trials, as well as diagnostic tools for analyzing PET/CT studies in oncological patients.
Leveraging Deep-Learning Techniques for Precision
Organ Finder utilizes sophisticated deep-learning techniques, trained on an extensive database of CT studies with manually segmented organs and tissues. To achieve this level of precision, we developed a comprehensive AI pipeline, featuring efficient tools for managing images and manual segmentations, as well as cloud-based tools for AI training.
Rigorous Training and Expert Quality Control
The training of Organ Finder is based on a robust database of over 1,250 CT studies, which includes the manual segmentation of more than 10,000 organs and tissues. All segmentations have undergone rigorous quality control by leading experts in the field. The latest version of Organ Finder, version 5.1.8, significantly expands its capabilities by including the segmentation of 25 soft tissue organs and 24 bones.
Transforming Organ Segmentation and Diagnostic Accuracy
By leveraging the power of Organ Finder, we are enhancing the precision and efficiency of medical image analysis. This advancement paves the way for improved diagnostic accuracy and stringent quality control in clinical trials. Stay tuned for more updates on our AI innovations and how they are transforming healthcare.
Reach out to discover how SliceVault's AI tools and expertise can revolutionize your research and clinical practices, ensuring you stay at the cutting edge of medical technology.
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