Objective: Pathomorphological diagnosis (PD) is important for estimation of clinical trials and new medical equipment such as elastography. However, interpretation of pathomorphological findings is often subjective, and pathology publications show only a limited number of photographs. Because pathomorphological changes occur in succession, we attempted to construct PD spectra to improve PD accuracy. Method: PD spectra are defined as the series of pathomorphological images arranged in the order of disease progression or cell cycle procession. The images from the whole slide imaging (WSI) server were arranged in order in Power Point files at a fixed magnification, and 4 PD spectra were constructed: chronic hepatitis staging, nuclear grading of hepatocellular carcinoma, nuclear grading of breast cancer, and Ki-67 labelling index (LI). The numbering of all images in the PD spectra corresponded with that of the WSI images so that the whole slides could be viewed alongside. Next, these tools were tried out by 6 people. Results: These tools brought on perfect accuracy with regard to staging and grading, and very high precision of Ki-67 LI for breast cancer. Conclusion: PD spectra are valuable not only for PD but also as learning tools and have a worldwide applicability for measuring PD online.