## 2 Materials and Methods
The process of reconstructing and visualising vascular structures from the aforementioned 3D stack mode comprises three primary steps (Figure 1):(1) To improve the visibility of the vascular structures within the 3D image stack, the original stack is first converted into a \"negative\" image. In this context, the term \"negative\" refers to the inversion of pixel intensities, whereby structures that were originally darker become lighter and vice versa. This conversion is crucial as it allows vessels that may have appeared darker in the original stack to become more prominent and easier to recognize in the subsequent steps. (2) After converting the image stack to a negative, the next step is to manually trace the vessel structures. The Simple Neurite Tracer (SNT) plugin in the ImageJ software (1.54k) used for this purpose. The SNT plugin is a versatile tool designed for tracing and analyzing tubular structures in 3D images, making it ideal for this application. The manual tracing process is performed in three different orientations of the image stack to ensure comprehensive coverage of the vascular network (sagittal, frontal, and horizontal). The stack is viewed from the side, providing a vertical cross-section. From the front, it provides a vertical cross-section in the coronal plane and it is viewed from above, providing a horizontal cross-section in the transverse plane. In each projection, the skeleton of each vessel is drawn manually by carefully following the course of the vessels throughout the 3D volume. This process is repeated for each vessel within the stack to ensure that the entire vascular network is accurately traced. (3) Once manual tracing is completed in all three projections, the traced vessel skeletons are used to create a binary mask. This binary mask represents the vessel structures as a binary image in which the vessels are mapped as white pixels (value 1) against a black background (value 0). The binary mask is then smoothed to refine the representation of the vessels and remove any irregularities or artifacts that may have occurred during manual tracing. This smoothing step is crucial for a clean and accurate 3D representation of the vessel architecture. Figure 1: Schematic reconstruction process. 1: Original LC-OCT image (vertical). 2: Negative LC-OCT image (vertical). 3: Segmentation drawn on LC-OCT images (vertical). 4: Final skeleton after segmentation applied in all 3 orientations (vertical, coronal, horizontal). 5: 3D reconstruction example. Finally, the smoothed binary mask is used to reconstruct a 3D model of the vascular network. This 3D architecture provides a detailed and comprehensive visualization of the vessels that can be further analyzed or used for various applications such as the study of vessel morphology or the quantification of vessel parameters. One 3D corresponds to 1200 coronal images + 500 vertical images + \(\sim\)400 horizontal images (the number of horizontal images depends on how deep the 3D was taken). The full process takes approximately 1h per stack, depending on the complexity of the vascular structure. A total of 235 patients (115 women, 120 men; medium age: 75 years) with different skin tumors were examined as part of the study. Patients were mainly recruited during surgical consultations, in individual cases, also during conservative consultations of the outpatient clinic of the Department of Dermatology and Allergology at the University Hospital Augsburg. The tumors analyzed included 51 melanomas, 13 melanoma metastases, 25 squamous cell carcinomas, 110 basal cell carcinomas, 13 cases of [PERSON]'s disease, and 23 benign or rare skin lesions. The segmented vascular structures originated exclusively from skin tumors on the extremities, with the lower extremities being predominantly affected. The images displayed in the results are examples of tumors that were manually segmented by an employee of DAMAE Medical and are now used to train an automatic artificial intelligence for vessels.