**3. Future Perspectives**

The research fields of biomedical image processing and classification have reached high levels of insight. Their integration into CAD systems can greatly contribute to supporting medical doctors to refine their clinical picture. In the near future, further growth in contributions to this field is expected; for example, taking advantage of increasing digitalization, deep learning has the potential to provide efficient solutions to many medical problems.

However, the real challenge is to bring an increasing number of systems into the hands of doctors, so that they can be applied to patients. This requires leaving the laboratory, engineering the systems, certifying the products, and identifying the correct target market that can accommodate the new devices and allow adequate support for these activities. In order to speed up this innovation process, the collaboration between researchers, institutions, funders, and entrepreneurs is always more important. The "do-it-all-yourself" approach only makes sense in a world of scarce external knowledge, but today knowledge is spread as it has never been before. Thus, in order to improve the wellness of the whole community [32], a dynamic environment in which new high-impact solutions can be created will be able to grow only if there is collaboration among organizations.

**Funding:** This research was carried out as part of the project "Method and apparatus to characterize non-invasive images containing venous blood vessels", funded through the PoC Instrument initiative, implemented by LINKS, with the support of LIFFT, with funds from Campagnia di San Paolo.

**Acknowledgments:** I would like to thank all authors who contributed to this Special Issue, the reviewers for their help in refining the papers and the MDPI editorial board and sta ff for the opportunity to be guest-editor.

**Conflicts of Interest:** The author declares no conflict of interest.
