This program is intended only for educational purposes and not for diagnostic, research, or therapeutic purposes. Copy rights reserved. Case K S QZ. Case W S. Case W S QZ. Case W R. Case B S. Case B 2 S. Case B 5 S.
Case B 6 R. Case B 7 S. Case B 8 R. Case N S. Case N R. Case N R QZ. Case A S. Case A S QZ. Case A 8 S. Case A R. Case L R. Case L S. Case G S. Case K S. Case F S. Case D S. Case D R. Case C 5 S. Case C 6 S. Case C 7 S. Case C S. Case C 9 S. Case C 4 S.Skip to content. Access to the supplemental resources for this session is password-protected and restricted to University of Michigan students. If you are a University of Michigan student enrolled in a histology course at the University of Michigan, please click on the following link and use your Kerberos-password for access to download lecture handouts and the other resources.
Browse the complete collection of the UM slides more than the histology course collection compiled by Kent Christensen, Ph. Matthew Velkey, Ph. Stoolman, M. If you have questions or comments regarding the University of Michigan virtual slide collection, please contact Dr.
Pathology, Lecture 1 Introduction to Pathology (Slides)
Hortsch at hortsch umich. Some items in the list contain numbers in brackets that give coordinates where you can find a good example of a specified structure on that slide.
These X, Y coordinates can be read at the bottom of the computer screen when you view a virtual slide with the ImageScope. The coordinates indicate the exact location of the mouse pointer at a given moment. To view a structure indicated by the bracketed XY coordinate numbers in the list, go to the Tools or Image menu, click "Go To Click "Go To: Center," and then "Close," The item will be in the center of the screen, and you can view it at any magnification you please.
Blood and Bone Marrow. Cardiovascular System. Cartilage, Bone and Bone Development. Central Nervous System. Human blood smear, Giemsa stain, 40X red blood cell, neutrophil, lymphocytes, monocytes [ x ], eosinophils [ xx ], basophil, platelet.
Human blood smear, Giemsa stain, 40X red blood cell, neutrophil, lymphocyte, monocyte, eosinophil [ x ], basophil, platelet. Human blood smear, Giemsa stain, 40X red blood cell, neutrophil, lymphocyte, monocyte [ x ], eosinophil [ xx ], basophil, platelet.
Human blood smear, Giemsa stain, 63x scan from hematopathology normals collection. Human blood smear, Giemsa stain, 86x scan from hematopathology normals collection. Aortastained for elastin, 20X extensive elastin in wall. Muscular or medium sized artery and companion vein, Masson, 20X. Small arteries and veins, Masson, 40X. Right heart wall, Masson, 40X heart wall, ventricle, atrium, atrioventricular valve, capillaries in heart muscle, coronary artery.
Heart, interventricular septum, Mallory, 20X septum, aortic valve, A V valve, chorda tendinae [ x ], Purkinje fibers [ x ], cardiac skeleton, atrioventricular bundle of His [ x ]. Heart, interventricular septum, Mallory, 20X septum, wall of aorta, aortic valve, A V valve, chorda tendinae [ x ], Purkinje fibers [ x ], cardiac skeleton [ x ], atrioventricular bundle of His [ x ].
Heart wall and aortic valve, Masson, 40X ventricle, aortic valve, aorta wall, Purkinje cells [ x ].
Head & Neck
Heart wall and aortic valve, Aldehyde fuchsin, 20X ventricle, aortic valve, aorta, elastin stain.Follow us:. Developmental Anomalies. Epithelial Pathology. Salivary Gland Pathology. Melanocytic Tumors. Soft Tissue Tumors. Oral Manifestations of Systemic Diseases.
Inflammatory Lesions. Giant Cell Granuloma. Fibrous Dysplasia. Epithelial Cysts. Calcifying Epithelial Odontogenic Tumor. Ameloblastic Fibroma. Odontogenic Myxoma. Ameloblastic Carcinoma. Salivary Glands. Normal Histology. Non-Neoplastic Lesions - I. Non-Neoplastic Lesions - II. Benign Neoplasms of Salivary Glands - I. Malignant Neoplasms of Salivary Glands - I.
Malignant Lymphoma of Salivary Glands. Mesenchymal Tumors. Metastatic Tumors in Salivary Glands. Inflammatory Lesions of Nose.
Sinonasal Papilloma. Sinonasal Carcinoma. Nasopharyngeal Carcinoma. Salivary Gland-Type Tumors. Melanoma of Nasal Cavity. Lymphoma of Sinonasal Region.PURPOSE: Digital pathology DPreferring to the digitization of tissue slides, is beginning to change the landscape of clinical diagnostic workflows and has engendered active research within the area of computational pathology.
One of the challenges in DP is the presence of artefacts and batch effects, unintentionally introduced during both routine slide preparation eg, staining, tissue folding and digitization eg, blurriness, variations in contrast and hue.
Manual review of glass and digital slides is laborious, qualitative, and subject to intra- and inter-reader variability.
Therefore, there is a critical need for a reproducible automated approach of precisely localizing artefacts to identify slides that need to be reproduced or regions that should be avoided during computational analysis.
METHODS: Here we present HistoQC, a tool for rapidly performing quality control to not only identify and delineate artefacts but also discover cohort-level outliers eg, slides stained darker or lighter than others in the cohort.
This open-source tool employs a combination of image metrics eg, color histograms, brightness, contrastfeatures eg, edge detectorsand supervised classifiers eg, pen detection to identify artefact-free regions on digitized slides. These regions and metrics are presented to the user via an interactive graphical user interface, facilitating artefact detection through real-time visualization and filtering. These same metrics afford users the opportunity to explicitly define acceptable tolerances for their workflows.Digital pathology is a sub-field of pathology that focuses on data management based on information generated from digitized specimen slides.
Through the use of computer-based technology, digital pathology utilizes virtual microscopy. Glass slides are converted into digital slides that can be viewed, managed, shared and analyzed on a computer monitor.
With the practice of Whole-Slide Imaging WSIwhich is another name for virtual microscopy,  the field of digital pathology is growing and has applications in diagnostic medicine, with the goal of achieving efficient and cheaper diagnosesprognosisand prediction of diseases.
The roots of digital pathology go back to the s, when first telepathology experiments took place. Later in the s the principle of virtual microscopy  appeared in several life science research areas. However in the technical requirements scanner, storage, network were still a limited factor for a broad dissemination of digital pathology concepts. The field of Radiology has undergone the digital transformation almost 15 years ago, not because radiology is more advanced, but there are fundamental differences between digital images in radiology and digital pathology: The image source in radiology is the alive patient, and today in most cases the image is even primarily captured in digital format.
In pathology the scanning is done from preserved and processed specimens, for retrospective studies even from slides stored in a biobank.
Besides this difference in pre-analytics and metadata content, the required storage in digital pathology is two to three orders of magnitude higher than in radiology. However, the advantages anticipated through digital pathology are similar to those in radiology:. Digital pathology is today widely used for educational purposes  in telepathology and teleconsultation as well as in research projects.
Digital pathology allows to share and annotate slides in a much easier way and to download annotated lecture sets generates new opportunities for e-learning and knowledge sharing in pathology. Digital pathology in diagnostics is an emerging and upcoming field. Digital slides are created from glass slides using specialized scanning machines.
All high quality scans must be free of dust, scratches, and other obstructions. Digital slides are accessible for viewing via a computer monitor and viewing software either locally or remotely via the Internet. Digital slides are maintained in an information management system that allows for archival and intelligent retrieval.
Digital slides are often stored and delivered over the Internet or private networks, for viewing and consultation. Image analysis tools are used to derive objective quantification measures from digital slides.
Image segmentation and classification algorithms are used to identify medically significant regions and objects on digital slides. Recent developments in machine learning ML using deep learning methods have also emerged to make information hidden in integrated pathological data images, patient history and - omics data in arbitrarily high-dimensional spaces, both accessible and quantifiable. Thus, generating a novel source of information which is not yet available to the expert and not exploited in current Digital Pathology settings.
Digital pathology workflow is integrated into the institution's overall operational environment. Slide digitization is expected to reduce the number of routine, manually reviewed slides, maximizing workload efficiency. Digital pathology also allows internet information sharing for education, diagnostics, publication and research.
The Virtual Pathology Slide Library is a collection of slides which have been digitised and curated by a trained pathologist. These slides are stored with their annonymised clinical information, which can be used for teaching and training. If you have glass slides that you would like digitising for your research project, we offer a range of scanning services that can be tailored to your needs.
For researchers based on the University of Leeds St James's site, simply bring your slides to the Wellcome Trust Brenner building, room 4. Slide scanning for external users is available upon request, as we have strict guidelines for sending slides through a courier. To request further information, please contact the Slide Scanning Team. Virtual Pathology at the University of Leeds. Slide Library.
Surgical Pathology Images
Virtual Pathology Slides. Total Storage Space Used by Slides Gastrointestinal Selective a categories under the Gastrointestinal focus Advertisement. Follow us:.Endocarditis - causes, symptoms, diagnosis, treatment, pathology
Home Gastrointestinal. Barrett Esophagus. Carcinoma in Barrett Esophagus. Squamous Cell Carcinoma of Esophagus. Basaloid Squamous Cell Carcinoma. Sarcomatoid Carcinoma. Mesenchymal Tumors of Esophagus. Normal Histology. Heterotopic Tissues. Inflammatory Disorders. Non-Neoplastic Lesions. Gastric Polyps. Gastric Carcinomas. Neuroendocrine Tumors. Gastrointestinal Stromal Tumors.
Metastases to Stomach. Small Bowel. Congenital Defects. Infectious Disorders.