This guide presents a comprehensive resource for veterinary professionals, bridging cutting-edge computational techniques with the practical applications needed in the field of veterinary pathology.
As digital pathology gains traction, the demand for veterinary experts to effectively utilize these computational methods while improving diagnostic accuracy is on the rise. This book addresses that need, offering accessible content suitable for beginners, technicians, and seasoned pathologists alike. Authored by an experienced veterinary pathologist, it ensures the techniques highlighted are both relevant and applicable.
The first section introduces the essentials of microscopy, including sample preparation, staining, and slide digitization. From there, readers will delve into computational image analysis, learning about image processing fundamentals, tools, and software needed for successful integration into veterinary practice. Furthermore, advanced concepts such as image enhancement, reconstruction, quantitative analysis, and the role of machine learning and AI in microscopy image analysis are thoroughly explored. The guide also showcases innovative imaging techniques, including fluorescence and confocal microscopy, as well as electron microscopy, covering advances that span from nano to macro scales.
Featuring case studies and practical workflows, this work illustrates the tangible benefits of computational image analysis within veterinary medicine, enhancing both diagnostic accuracy and operational efficiency. It serves as a vital learning tool for ongoing professional development, empowering veterinary pathologists to remain informed about the latest technology in image analysis. Whether you’re a veterinary professional, pathologist, researcher, or computational biologist, this book is an indispensable asset for anyone eager to embrace the potential of computational tools and AI within veterinary medicine.
