> For the complete documentation index, see [llms.txt](https://medomicslab.gitbook.io/mediml-app-docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://medomicslab.gitbook.io/mediml-app-docs/radiomics/feature-extraction/single-scan.md). # Single Scan {% hint style="success" %} A tutorial video is available at the bottom of the page. {% endhint %} Contrary to the Batch Extraction implementation, the single-scan feature extraction provides great flexibility through a drag-and-drop design. This enables users to customize their Radiomics analysis for a specific image. In this mode, users have control over the processing steps and the features to be extracted. Moreover, additional features such as 3D image visualization are available. The following image summarizes the available resources in the single scan interface:

Single image feature extraction interface

Having gained an understanding of the various components of the extraction interface, the following section illustrates the available nodes, highlighting their individual functionalities, inputs, and outputs.

Description	Input	Output
The input node handles the loading of data into memory, supporting both DICOM files and MEDscan objects. Additionally, it provides 3D visualization of the images.	None	MEDscan binary object
The segmentation node is used to define the regions in which features are calculated. These regions are automatically identified from the loaded scan. More details in IBSI section 2.3.	Input node (With loaded file)	Imaging Volume & Mask
The interpolation node is used to interpolate to isotropic voxel spacing. Many features require interpolation prior to their extraction. More detail in IBSI section 2.4.	Imaging Volume & Mask	Interpolated Imaging Volume & Mask
The re-segmentation process is performed to exclude voxels from a previously segmented ROI, and is performed after interpolation. More details in IBSI section 2.5.	Binary Mask	Segmented Binary Mask
ROI extraction node replaces voxels outside the ROI by a placeholder value, often NaN. More details in IBSI section 2.6.	Imaging Volume	Imaging Volume
Filtering is conducted after image interpolation. A set of linear filters is available for use. More details in IBSI-2.	Imaging Volume	Filtered Imaging Volume
Discretization or quantization of image intensities inside the ROI is required for the calculation of texture features. More details in IBSI section 2.7.	Imaging Volume with ROI voxels only	Discretized Imaging Volume with ROI voxels only
Feature calculation is the final processing step. Upon clicking, a page will appear, allowing you to select the features for extraction.	The input depends on features type. Usually Imaging volume and ROI mask.	Features dictionary

To select the features to extract, click on the extraction node, a page will appear (see figure below) and you will be able to select feature families and features to extract for your analysis.

### Tutorial video {% embed url="" %}