Hyperspectral imaging (HSI) has a crucial role in material classification tasks. The primary type of sensors in this field are linescan sensors, offering a high spatial and spectral resolution and improving the quality of the captured hypercubes. However, these cameras have inherent problems such as the need of dedicated hardware to move the camera over the scene and the necessity of pre-processing the raw captures in order to obtain the actual hypercube. This work makes an analysis and an adaptation of stitching techniques to apply them to the medical area. Also, it includes different methods to post-process the hypercubes obtained and it analyzes the SURF algorithm to improve processing times. The results obtained show that a stitching technique based on SURF is suitable for the medical area.