LEADER 02709nam 2200469 450 001 9910816437103321 005 20181218120625.0 010 $a1-4758-3937-5 035 $a(CKB)4100000005465572 035 $a(MiAaPQ)EBC5432358 035 $a(EXLCZ)994100000005465572 100 $a20180917d2018 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aOnline teaching $etools and techniques to achieve success with learners /$fMike Casey, [and three others] 210 1$aLanham :$cRowman & Littlefield,$d[2018] 210 4$dİ2018 215 $a1 online resource (109 pages) 311 $a1-4758-3935-9 327 $aOnline teaching and learning: how this book will help you become a better online instructor -- Foundations and formats of online teaching and learning: exploring the extraordinary benefits and possible pitfalls of online teaching and learning -- Course organization and learning management: developing a course with student learning in mind -- Building community and effective communication: closing the gap between the online instructor and online students -- Course layout and instructional design: designing a visually engaging and accessible online course -- Course information and learner support: providing students with appropriate learning support resources -- Course goals and performance assessments: aligning to course goals and developing engaging assessments -- Data analysis and course improvement: recording outcomes, analyzing data, and interpreting findings. 330 $a"The purpose of this book is to equip online educators with tools, techniques, and tips to conduct a successful online learning experience, encompassing preparation, design, and facilitation of effective outcomes that benefit learners and educators. It is structured to guide and support the online educator from design and development to delivery" --$cProvided by publisher. 606 $aWeb-based instruction$xStudy and teaching 606 $aEducational technology$xStudy and teaching 606 $aEducation, Higher$xComputer-assisted instruction 615 0$aWeb-based instruction$xStudy and teaching. 615 0$aEducational technology$xStudy and teaching. 615 0$aEducation, Higher$xComputer-assisted instruction. 676 $a371.33/44678 700 $aCasey$b K. Michael$01697504 702 $aShaw$b Erin 702 $aWhittingham$b Jeff 702 $aGallavan$b Nancy P. 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910816437103321 996 $aOnline teaching$94078263 997 $aUNINA LEADER 04381nam 22006255 450 001 9911015864603321 005 20250702130308.0 010 $a9783031862700$b(electronic bk.) 010 $z9783031862694 024 7 $a10.1007/978-3-031-86270-0 035 $a(MiAaPQ)EBC32189538 035 $a(Au-PeEL)EBL32189538 035 $a(CKB)39567932100041 035 $a(OCoLC)1526861652 035 $a(DE-He213)978-3-031-86270-0 035 $a(EXLCZ)9939567932100041 100 $a20250702d2025 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aComputational Analysis of Microscopy Images $eA Veterinary Medicine Perspective /$fby Elvira Gagniuc 205 $a1st ed. 2025. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2025. 215 $a1 online resource (180 pages) 311 08$aPrint version: Gagniuc, Elvira Computational Analysis of Microscopy Images Cham : Springer,c2025 9783031862694 327 $aChapter 1. Computational Analysis in Veterinary Medicine -- Chapter 2. Fundamentals of Microscopy in Veterinary Pathology -- Chapter 3. Computational Image Analysis -- Chapter 4. Image Preprocessing Techniques -- Chapter 5. Image Segmentation and Feature Extraction -- Chapter 6. Quantitative Image Analysis in Veterinary Medicine -- Chapter 7. Machine Learning and AI in Microscopy Image Analysis. 330 $aThis application-based guide fills a unique niche in the veterinary medical field by merging advanced computational techniques with the practical needs of veterinary pathology. With increasing prevalence of digital pathology, there is a burgeoning requirement to navigate veterinary professionals in the utilization of computational methods and the enhancement of diagnostic accuracy. This book caters to this demand, presenting the material in an accessible way to novices, technologists, and pathologists. Written from the perspective of a seasoned veterinary pathologist, it ensures that the techniques described are relevant and directly usable. Beginning with an exploration of microscopy fundamentals, the first part includes sample preparation, staining, and slide digitization. Subsequent chapters introduce readers to computational image analysis and the basics of image processing, tools, software, and successful integration of computational analysis into veterinary practice. Moreover, the book covers advanced topics such as image enhancement, reconstruction, quantitative analysis, and the application of machine learning and AI in microscopy image analysis. It provides insight into state-of-the-art imaging techniques like fluorescence and confocal microscopy, electron microscopy, and explores the innovations from nano to macro scales. The incorporation of case studies and sample workflows allows this work to demonstrate the practical benefits of computational image analysis in veterinary medicine, with improvements in diagnostic accuracy and workflow efficiency. It serves as a learning resource for continuous professional development, helping veterinary pathologists stay abreast of technological advances in image analysis. Serving veterinary professionals, pathologists, researchers, and computational biologists alike, this book is an essential resource for anyone looking to harness the power of computational tools and AI in veterinary medicine. 606 $aVeterinary medicine 606 $aImaging systems in biology 606 $aAnatomy, Comparative 606 $aVeterinary microbiology 606 $aVeterinary Science 606 $aBiological Imaging 606 $aAnimal Anatomy 606 $aVeterinary Microbiology 606 $aVeterinary Clinical Medicine 615 0$aVeterinary medicine. 615 0$aImaging systems in biology. 615 0$aAnatomy, Comparative. 615 0$aVeterinary microbiology. 615 14$aVeterinary Science. 615 24$aBiological Imaging. 615 24$aAnimal Anatomy. 615 24$aVeterinary Microbiology. 615 24$aVeterinary Clinical Medicine. 676 $a636.089 700 $aGagniuc$b Elvira$01833388 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 912 $a9911015864603321 996 $aComputational Analysis of Microscopy Images$94408317 997 $aUNINA