Koos Classification

Koos classification is a system for grading vestibular schwannomas (tumors affecting the balance nerve), guiding treatment decisions based on tumor size and proximity to critical brain structures. Current research focuses on improving the accuracy and efficiency of Koos classification using medical imaging, particularly leveraging techniques like unsupervised cross-modality domain adaptation to translate between different MRI scan types (e.g., T1-weighted and T2-weighted) and improve classification performance with limited labeled data. These advancements, often employing machine learning algorithms such as random forests, aim to enhance diagnostic capabilities and optimize treatment planning for patients with vestibular schwannomas.