Intraoperative radiographs are used in image-guided spine surgery (IGSS) for vertebrae planning and other processes like 2D/3D registration, single image tomography, and 3D reconstruction. Since preoperative CT is also a prerequisite for the majority of these techniques, computationally connecting the intraoperative radiographs and preoperative CT aids in the extraction of 3D data and improving accuracy. However, since the CT and radiograph modalities have different imaging attributes, Digitally Reconstructed Radiographs (DRR) produced from the CTs must be domain-adjusted with radiographs before computationally linking the two modalities. The proposed research focuses on the domain-adjusting algorithm SpineStyle, which is a unique style transfer algorithm meant to transfer DRR style attributes to intraoperative radiographs. SpineStyle implements a customized VGG-19 architecture capable of dealing with spine anatomy and producing anatomically accurate style-transferred images from a small dataset. Because the preservation of anatomy is critical for IGSS, this work additionally provides a Semantic Content Loss Measure (SCLM) evaluation metric to measure anatomy preservation during style transfer. Experimental studies show that SpineStyle outperforms other standard CNNs while also preserving anatomical content. The implementation of the project can be found in this repository: .