--- title: Object Detection with Bounding Boxes for Medical Imaging type: templates hide_menu: true category: Computer Vision cat: computer-vision order: 1103 meta_description: Template for using Label Studio to perform object detection with rectangular bounding boxes for medical imaging. --- ![Screenshot of labeling interface with medical image](/images/templates-misc/bbox-medical.png) Object Detection with Bounding Boxes is critical in medical imaging as it enables AI models to accurately identify and localize abnormalities, such as tumors or lesions, in imaging scans like X-rays and MRIs. High-quality labeled data is necessary for training these models to perform tasks that directly influence diagnostic accuracy and treatment decisions. However, the data labeling process in medical imaging is fraught with significant challenges, including the time-intensive nature of manual annotations, risks of inconsistency in labeling across different annotators, and the requirement for extensive domain expertise to ensure accuracy. Label Studio effectively addresses these challenges through a hybrid AI-assisted approach, leveraging pre-labeling capabilities to accelerate the initial labeling process while ensuring that specialized expert reviewers validate the annotations. The platform’s collaborative tools facilitate seamless communication among annotators and domain experts, and its customizable templates allow for tailored workflows that enhance labeling efficiency and scalability. By combining automation with human oversight, Label Studio not only reduces labeling time but also significantly improves the overall quality of the labeled data, leading to superior model performance in critical medical applications. Open in Label Studio ## Labeling interface ```html ``` All labeling configurations must be wrapped in View tags. Use the Image object tag to specify the medical imaging scan to label: ```xml ``` Use the RectangleLabels control tag to add labels and rectangular bounding boxes to your medical images at the same time. Use the Label tag to control the color of the boxes: ```xml ``` If you want to add further context to object detection tasks with bounding boxes in medical imaging, you can add some per-region conditional labeling parameters to your labeling configuration. For example, to prompt annotators to add descriptions to detected abnormalities, you can add the following to your labeling configuration: ```html